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1208.6231
Beyza Ermis Ms
Beyza Ermi\c{s} and Evrim Acar and A. Taylan Cemgil
Link Prediction via Generalized Coupled Tensor Factorisation
null
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This study deals with the missing link prediction problem: the problem of predicting the existence of missing connections between entities of interest. We address link prediction using coupled analysis of relational datasets represented as heterogeneous data, i.e., datasets in the form of matrices and higher-order te...
[ { "version": "v1", "created": "Thu, 30 Aug 2012 16:48:05 GMT" } ]
2012-08-31T00:00:00
[ [ "Ermiş", "Beyza", "" ], [ "Acar", "Evrim", "" ], [ "Cemgil", "A. Taylan", "" ] ]
TITLE: Link Prediction via Generalized Coupled Tensor Factorisation ABSTRACT: This study deals with the missing link prediction problem: the problem of predicting the existence of missing connections between entities of interest. We address link prediction using coupled analysis of relational datasets represented a...
1204.4166
Yandong Guo
Yuan Qi and Yandong Guo
Message passing with relaxed moment matching
null
null
null
null
cs.LG stat.CO stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Bayesian learning is often hampered by large computational expense. As a powerful generalization of popular belief propagation, expectation propagation (EP) efficiently approximates the exact Bayesian computation. Nevertheless, EP can be sensitive to outliers and suffer from divergence for difficult cases. To address...
[ { "version": "v1", "created": "Wed, 18 Apr 2012 19:21:59 GMT" }, { "version": "v2", "created": "Wed, 29 Aug 2012 16:02:21 GMT" } ]
2012-08-30T00:00:00
[ [ "Qi", "Yuan", "" ], [ "Guo", "Yandong", "" ] ]
TITLE: Message passing with relaxed moment matching ABSTRACT: Bayesian learning is often hampered by large computational expense. As a powerful generalization of popular belief propagation, expectation propagation (EP) efficiently approximates the exact Bayesian computation. Nevertheless, EP can be sensitive to out...
1208.5792
Stefano Allesina
Stefano Allesina
Measuring Nepotism Through Shared Last Names: Response to Ferlazzo and Sdoia
17 pages, 1 figure
null
null
null
stat.AP physics.soc-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In a recent article, I showed that in several academic disciplines in Italy, professors display a paucity of last names that cannot be explained by unbiased, random, hiring processes. I suggested that this scarcity of last names could be related to the prevalence of nepotistic hires, i.e., professors engaging in ille...
[ { "version": "v1", "created": "Tue, 28 Aug 2012 20:57:52 GMT" } ]
2012-08-30T00:00:00
[ [ "Allesina", "Stefano", "" ] ]
TITLE: Measuring Nepotism Through Shared Last Names: Response to Ferlazzo and Sdoia ABSTRACT: In a recent article, I showed that in several academic disciplines in Italy, professors display a paucity of last names that cannot be explained by unbiased, random, hiring processes. I suggested that this scarcity of la...
0911.4889
Cms Collaboration
CMS Collaboration
Commissioning of the CMS High-Level Trigger with Cosmic Rays
null
JINST 5:T03005,2010
10.1088/1748-0221/5/03/T03005
CMS-CFT-09-020
physics.ins-det
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The CMS High-Level Trigger (HLT) is responsible for ensuring that data samples with potentially interesting events are recorded with high efficiency and good quality. This paper gives an overview of the HLT and focuses on its commissioning using cosmic rays. The selection of triggers that were deployed is presented a...
[ { "version": "v1", "created": "Wed, 25 Nov 2009 15:49:24 GMT" }, { "version": "v2", "created": "Tue, 19 Jan 2010 14:00:10 GMT" } ]
2012-08-27T00:00:00
[ [ "CMS Collaboration", "", "" ] ]
TITLE: Commissioning of the CMS High-Level Trigger with Cosmic Rays ABSTRACT: The CMS High-Level Trigger (HLT) is responsible for ensuring that data samples with potentially interesting events are recorded with high efficiency and good quality. This paper gives an overview of the HLT and focuses on its commissionin...
1011.6665
Atlas Publications
The ATLAS Collaboration
Studies of the performance of the ATLAS detector using cosmic-ray muons
22 pages plus author list (33 pages total), 21 figures, 2 tables
Eur.Phys.J. C71 (2011) 1593
10.1140/epjc/s10052-011-1593-6
CERN-PH-EP-2010-070
physics.ins-det hep-ex
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Muons from cosmic-ray interactions in the atmosphere provide a high-statistics source of particles that can be used to study the performance and calibration of the ATLAS detector. Cosmic-ray muons can penetrate to the cavern and deposit energy in all detector subsystems. Such events have played an important role in t...
[ { "version": "v1", "created": "Tue, 30 Nov 2010 20:23:11 GMT" } ]
2012-08-27T00:00:00
[ [ "The ATLAS Collaboration", "", "" ] ]
TITLE: Studies of the performance of the ATLAS detector using cosmic-ray muons ABSTRACT: Muons from cosmic-ray interactions in the atmosphere provide a high-statistics source of particles that can be used to study the performance and calibration of the ATLAS detector. Cosmic-ray muons can penetrate to the cavern an...
1208.4429
Tshilidzi Marwala
E. Hurwitz and T. Marwala
Common Mistakes when Applying Computational Intelligence and Machine Learning to Stock Market modelling
5 pages
null
null
null
stat.AP cs.CY q-fin.GN
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
For a number of reasons, computational intelligence and machine learning methods have been largely dismissed by the professional community. The reasons for this are numerous and varied, but inevitably amongst the reasons given is that the systems designed often do not perform as expected by their designers. The reaso...
[ { "version": "v1", "created": "Wed, 22 Aug 2012 06:20:00 GMT" } ]
2012-08-23T00:00:00
[ [ "Hurwitz", "E.", "" ], [ "Marwala", "T.", "" ] ]
TITLE: Common Mistakes when Applying Computational Intelligence and Machine Learning to Stock Market modelling ABSTRACT: For a number of reasons, computational intelligence and machine learning methods have been largely dismissed by the professional community. The reasons for this are numerous and varied, but ine...
1208.4138
Zahoor Khan
Ashraf Mohammed Iqbal, Abidalrahman Moh'd, Zahoor Khan
Semi-supervised Clustering Ensemble by Voting
The International Conference on Information and Communication Systems (ICICS 2009), Amman, Jordan
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Clustering ensemble is one of the most recent advances in unsupervised learning. It aims to combine the clustering results obtained using different algorithms or from different runs of the same clustering algorithm for the same data set, this is accomplished using on a consensus function, the efficiency and accuracy ...
[ { "version": "v1", "created": "Mon, 20 Aug 2012 23:21:10 GMT" } ]
2012-08-22T00:00:00
[ [ "Iqbal", "Ashraf Mohammed", "" ], [ "Moh'd", "Abidalrahman", "" ], [ "Khan", "Zahoor", "" ] ]
TITLE: Semi-supervised Clustering Ensemble by Voting ABSTRACT: Clustering ensemble is one of the most recent advances in unsupervised learning. It aims to combine the clustering results obtained using different algorithms or from different runs of the same clustering algorithm for the same data set, this is accompl...
1208.4238
Enrico Siragusa
Enrico Siragusa, David Weese, Knut Reinert
Fast and sensitive read mapping with approximate seeds and multiple backtracking
null
null
null
null
cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present Masai, a read mapper representing the state of the art in terms of speed and sensitivity. Our tool is an order of magnitude faster than RazerS 3 and mrFAST, 2--3 times faster and more accurate than Bowtie 2 and BWA. The novelties of our read mapper are filtration with approximate seeds and a method for mul...
[ { "version": "v1", "created": "Tue, 21 Aug 2012 11:08:06 GMT" } ]
2012-08-22T00:00:00
[ [ "Siragusa", "Enrico", "" ], [ "Weese", "David", "" ], [ "Reinert", "Knut", "" ] ]
TITLE: Fast and sensitive read mapping with approximate seeds and multiple backtracking ABSTRACT: We present Masai, a read mapper representing the state of the art in terms of speed and sensitivity. Our tool is an order of magnitude faster than RazerS 3 and mrFAST, 2--3 times faster and more accurate than Bowtie ...
1205.3137
Saurabh Singh
Saurabh Singh, Abhinav Gupta, Alexei A. Efros
Unsupervised Discovery of Mid-Level Discriminative Patches
null
European Conference on Computer Vision, 2012
null
null
cs.CV cs.AI cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The goal of this paper is to discover a set of discriminative patches which can serve as a fully unsupervised mid-level visual representation. The desired patches need to satisfy two requirements: 1) to be representative, they need to occur frequently enough in the visual world; 2) to be discriminative, they need to ...
[ { "version": "v1", "created": "Mon, 14 May 2012 18:52:57 GMT" }, { "version": "v2", "created": "Sat, 18 Aug 2012 04:16:13 GMT" } ]
2012-08-21T00:00:00
[ [ "Singh", "Saurabh", "" ], [ "Gupta", "Abhinav", "" ], [ "Efros", "Alexei A.", "" ] ]
TITLE: Unsupervised Discovery of Mid-Level Discriminative Patches ABSTRACT: The goal of this paper is to discover a set of discriminative patches which can serve as a fully unsupervised mid-level visual representation. The desired patches need to satisfy two requirements: 1) to be representative, they need to occur...
1208.3943
Jay Gholap B.Tech.(Computer Engineering)
Jay Gholap
Performance Tuning Of J48 Algorithm For Prediction Of Soil Fertility
5 Pages
Published in Asian Journal of Computer Science and Information Technology,Vol 2,No. 8 (2012)
null
null
cs.LG cs.DB cs.PF stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Data mining involves the systematic analysis of large data sets, and data mining in agricultural soil datasets is exciting and modern research area. The productive capacity of a soil depends on soil fertility. Achieving and maintaining appropriate levels of soil fertility, is of utmost importance if agricultural land...
[ { "version": "v1", "created": "Mon, 20 Aug 2012 08:48:40 GMT" } ]
2012-08-21T00:00:00
[ [ "Gholap", "Jay", "" ] ]
TITLE: Performance Tuning Of J48 Algorithm For Prediction Of Soil Fertility ABSTRACT: Data mining involves the systematic analysis of large data sets, and data mining in agricultural soil datasets is exciting and modern research area. The productive capacity of a soil depends on soil fertility. Achieving and mainta...
1208.3623
Rafi Muhammad
Muhammad Rafi, Sundus Hassan and Mohammad Shahid Shaikh
Content-based Text Categorization using Wikitology
9 pages; IJCSI August 2012
null
null
null
cs.IR cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A major computational burden, while performing document clustering, is the calculation of similarity measure between a pair of documents. Similarity measure is a function that assign a real number between 0 and 1 to a pair of documents, depending upon the degree of similarity between them. A value of zero means that ...
[ { "version": "v1", "created": "Fri, 17 Aug 2012 15:49:38 GMT" } ]
2012-08-20T00:00:00
[ [ "Rafi", "Muhammad", "" ], [ "Hassan", "Sundus", "" ], [ "Shaikh", "Mohammad Shahid", "" ] ]
TITLE: Content-based Text Categorization using Wikitology ABSTRACT: A major computational burden, while performing document clustering, is the calculation of similarity measure between a pair of documents. Similarity measure is a function that assign a real number between 0 and 1 to a pair of documents, depending u...
1112.4133
Hocine Cherifi
Vincent Labatut, Hocine Cherifi (Le2i)
Evaluation of Performance Measures for Classifiers Comparison
null
Ubiquitous Computing and Communication Journal, 6:21-34, 2011
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The selection of the best classification algorithm for a given dataset is a very widespread problem, occuring each time one has to choose a classifier to solve a real-world problem. It is also a complex task with many important methodological decisions to make. Among those, one of the most crucial is the choice of an...
[ { "version": "v1", "created": "Sun, 18 Dec 2011 08:02:49 GMT" } ]
2012-08-16T00:00:00
[ [ "Labatut", "Vincent", "", "Le2i" ], [ "Cherifi", "Hocine", "", "Le2i" ] ]
TITLE: Evaluation of Performance Measures for Classifiers Comparison ABSTRACT: The selection of the best classification algorithm for a given dataset is a very widespread problem, occuring each time one has to choose a classifier to solve a real-world problem. It is also a complex task with many important methodolo...
1009.0881
Nicolas Gillis
Nicolas Gillis, Fran\c{c}ois Glineur
A Multilevel Approach For Nonnegative Matrix Factorization
23 pages, 10 figures. Section 6 added discussing limitations of the method. Accepted in Journal of Computational and Applied Mathematics
Journal of Computational and Applied Mathematics 236 (7), pp. 1708-1723, 2012
10.1016/j.cam.2011.10.002
null
math.OC cs.NA math.NA
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Nonnegative Matrix Factorization (NMF) is the problem of approximating a nonnegative matrix with the product of two low-rank nonnegative matrices and has been shown to be particularly useful in many applications, e.g., in text mining, image processing, computational biology, etc. In this paper, we explain how algorit...
[ { "version": "v1", "created": "Sat, 4 Sep 2010 22:55:34 GMT" }, { "version": "v2", "created": "Sun, 12 Sep 2010 16:47:01 GMT" }, { "version": "v3", "created": "Tue, 4 Oct 2011 00:02:21 GMT" } ]
2012-08-13T00:00:00
[ [ "Gillis", "Nicolas", "" ], [ "Glineur", "François", "" ] ]
TITLE: A Multilevel Approach For Nonnegative Matrix Factorization ABSTRACT: Nonnegative Matrix Factorization (NMF) is the problem of approximating a nonnegative matrix with the product of two low-rank nonnegative matrices and has been shown to be particularly useful in many applications, e.g., in text mining, image...
1107.5194
Nicolas Gillis
Nicolas Gillis, Fran\c{c}ois Glineur
Accelerated Multiplicative Updates and Hierarchical ALS Algorithms for Nonnegative Matrix Factorization
17 pages, 10 figures. New Section 4 about the convergence of the accelerated algorithms; Removed Section 5 about efficiency of HALS. Accepted in Neural Computation
Neural Computation 24 (4), pp. 1085-1105, 2012
10.1162/NECO_a_00256
null
math.OC cs.NA math.NA
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Nonnegative matrix factorization (NMF) is a data analysis technique used in a great variety of applications such as text mining, image processing, hyperspectral data analysis, computational biology, and clustering. In this paper, we consider two well-known algorithms designed to solve NMF problems, namely the multipl...
[ { "version": "v1", "created": "Tue, 26 Jul 2011 12:26:07 GMT" }, { "version": "v2", "created": "Thu, 6 Oct 2011 13:16:20 GMT" } ]
2012-08-13T00:00:00
[ [ "Gillis", "Nicolas", "" ], [ "Glineur", "François", "" ] ]
TITLE: Accelerated Multiplicative Updates and Hierarchical ALS Algorithms for Nonnegative Matrix Factorization ABSTRACT: Nonnegative matrix factorization (NMF) is a data analysis technique used in a great variety of applications such as text mining, image processing, hyperspectral data analysis, computational bio...
1208.1846
Qiang Qian
Guangxu Guo and Songcan Chen
Margin Distribution Controlled Boosting
null
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Schapire's margin theory provides a theoretical explanation to the success of boosting-type methods and manifests that a good margin distribution (MD) of training samples is essential for generalization. However the statement that a MD is good is vague, consequently, many recently developed algorithms try to generate...
[ { "version": "v1", "created": "Thu, 9 Aug 2012 08:53:11 GMT" } ]
2012-08-10T00:00:00
[ [ "Guo", "Guangxu", "" ], [ "Chen", "Songcan", "" ] ]
TITLE: Margin Distribution Controlled Boosting ABSTRACT: Schapire's margin theory provides a theoretical explanation to the success of boosting-type methods and manifests that a good margin distribution (MD) of training samples is essential for generalization. However the statement that a MD is good is vague, conse...
1208.1259
Ping Li
Ping Li and Art Owen and Cun-Hui Zhang
One Permutation Hashing for Efficient Search and Learning
null
null
null
null
cs.LG cs.IR cs.IT math.IT stat.CO stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recently, the method of b-bit minwise hashing has been applied to large-scale linear learning and sublinear time near-neighbor search. The major drawback of minwise hashing is the expensive preprocessing cost, as the method requires applying (e.g.,) k=200 to 500 permutations on the data. The testing time can also be ...
[ { "version": "v1", "created": "Mon, 6 Aug 2012 12:28:06 GMT" } ]
2012-08-08T00:00:00
[ [ "Li", "Ping", "" ], [ "Owen", "Art", "" ], [ "Zhang", "Cun-Hui", "" ] ]
TITLE: One Permutation Hashing for Efficient Search and Learning ABSTRACT: Recently, the method of b-bit minwise hashing has been applied to large-scale linear learning and sublinear time near-neighbor search. The major drawback of minwise hashing is the expensive preprocessing cost, as the method requires applying...
1208.0967
Hema Swetha Koppula
Hema Swetha Koppula, Rudhir Gupta, Ashutosh Saxena
Human Activity Learning using Object Affordances from RGB-D Videos
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Human activities comprise several sub-activities performed in a sequence and involve interactions with various objects. This makes reasoning about the object affordances a central task for activity recognition. In this work, we consider the problem of jointly labeling the object affordances and human activities from ...
[ { "version": "v1", "created": "Sat, 4 Aug 2012 23:44:07 GMT" } ]
2012-08-07T00:00:00
[ [ "Koppula", "Hema Swetha", "" ], [ "Gupta", "Rudhir", "" ], [ "Saxena", "Ashutosh", "" ] ]
TITLE: Human Activity Learning using Object Affordances from RGB-D Videos ABSTRACT: Human activities comprise several sub-activities performed in a sequence and involve interactions with various objects. This makes reasoning about the object affordances a central task for activity recognition. In this work, we cons...
1207.6744
Lluis Pamies-Juarez
Lluis Pamies-Juarez, Anwitaman Datta and Frederique Oggier
RapidRAID: Pipelined Erasure Codes for Fast Data Archival in Distributed Storage Systems
null
null
null
null
cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
To achieve reliability in distributed storage systems, data has usually been replicated across different nodes. However the increasing volume of data to be stored has motivated the introduction of erasure codes, a storage efficient alternative to replication, particularly suited for archival in data centers, where ol...
[ { "version": "v1", "created": "Sun, 29 Jul 2012 04:27:44 GMT" }, { "version": "v2", "created": "Fri, 3 Aug 2012 07:02:25 GMT" } ]
2012-08-06T00:00:00
[ [ "Pamies-Juarez", "Lluis", "" ], [ "Datta", "Anwitaman", "" ], [ "Oggier", "Frederique", "" ] ]
TITLE: RapidRAID: Pipelined Erasure Codes for Fast Data Archival in Distributed Storage Systems ABSTRACT: To achieve reliability in distributed storage systems, data has usually been replicated across different nodes. However the increasing volume of data to be stored has motivated the introduction of erasure cod...
1208.0541
Simon Powers
Simon T. Powers and Jun He
A hybrid artificial immune system and Self Organising Map for network intrusion detection
Post-print of accepted manuscript. 32 pages and 3 figures
Information Sciences 178(15), pp. 3024-3042, August 2008
10.1016/j.ins.2007.11.028
null
cs.NE cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Network intrusion detection is the problem of detecting unauthorised use of, or access to, computer systems over a network. Two broad approaches exist to tackle this problem: anomaly detection and misuse detection. An anomaly detection system is trained only on examples of normal connections, and thus has the potenti...
[ { "version": "v1", "created": "Thu, 2 Aug 2012 16:53:13 GMT" } ]
2012-08-03T00:00:00
[ [ "Powers", "Simon T.", "" ], [ "He", "Jun", "" ] ]
TITLE: A hybrid artificial immune system and Self Organising Map for network intrusion detection ABSTRACT: Network intrusion detection is the problem of detecting unauthorised use of, or access to, computer systems over a network. Two broad approaches exist to tackle this problem: anomaly detection and misuse det...
1208.0075
Yufei Tao
Cheng Sheng, Nan Zhang, Yufei Tao, Xin Jin
Optimal Algorithms for Crawling a Hidden Database in the Web
VLDB2012
Proceedings of the VLDB Endowment (PVLDB), Vol. 5, No. 11, pp. 1112-1123 (2012)
null
null
cs.DB
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A hidden database refers to a dataset that an organization makes accessible on the web by allowing users to issue queries through a search interface. In other words, data acquisition from such a source is not by following static hyper-links. Instead, data are obtained by querying the interface, and reading the result...
[ { "version": "v1", "created": "Wed, 1 Aug 2012 03:43:52 GMT" } ]
2012-08-02T00:00:00
[ [ "Sheng", "Cheng", "" ], [ "Zhang", "Nan", "" ], [ "Tao", "Yufei", "" ], [ "Jin", "Xin", "" ] ]
TITLE: Optimal Algorithms for Crawling a Hidden Database in the Web ABSTRACT: A hidden database refers to a dataset that an organization makes accessible on the web by allowing users to issue queries through a search interface. In other words, data acquisition from such a source is not by following static hyper-lin...
1208.0076
Lu Qin
Lu Qin, Jeffrey Xu Yu, Lijun Chang
Diversifying Top-K Results
VLDB2012
Proceedings of the VLDB Endowment (PVLDB), Vol. 5, No. 11, pp. 1124-1135 (2012)
null
null
cs.DB
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Top-k query processing finds a list of k results that have largest scores w.r.t the user given query, with the assumption that all the k results are independent to each other. In practice, some of the top-k results returned can be very similar to each other. As a result some of the top-k results returned are redundan...
[ { "version": "v1", "created": "Wed, 1 Aug 2012 03:44:46 GMT" } ]
2012-08-02T00:00:00
[ [ "Qin", "Lu", "" ], [ "Yu", "Jeffrey Xu", "" ], [ "Chang", "Lijun", "" ] ]
TITLE: Diversifying Top-K Results ABSTRACT: Top-k query processing finds a list of k results that have largest scores w.r.t the user given query, with the assumption that all the k results are independent to each other. In practice, some of the top-k results returned can be very similar to each other. As a result s...
1208.0082
Harold Lim
Harold Lim, Herodotos Herodotou, Shivnath Babu
Stubby: A Transformation-based Optimizer for MapReduce Workflows
VLDB2012
Proceedings of the VLDB Endowment (PVLDB), Vol. 5, No. 11, pp. 1196-1207 (2012)
null
null
cs.DB
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
There is a growing trend of performing analysis on large datasets using workflows composed of MapReduce jobs connected through producer-consumer relationships based on data. This trend has spurred the development of a number of interfaces--ranging from program-based to query-based interfaces--for generating MapReduce...
[ { "version": "v1", "created": "Wed, 1 Aug 2012 03:49:32 GMT" } ]
2012-08-02T00:00:00
[ [ "Lim", "Harold", "" ], [ "Herodotou", "Herodotos", "" ], [ "Babu", "Shivnath", "" ] ]
TITLE: Stubby: A Transformation-based Optimizer for MapReduce Workflows ABSTRACT: There is a growing trend of performing analysis on large datasets using workflows composed of MapReduce jobs connected through producer-consumer relationships based on data. This trend has spurred the development of a number of interf...
1208.0086
Yu Cao
Yu Cao, Chee-Yong Chan, Jie Li, Kian-Lee Tan
Optimization of Analytic Window Functions
VLDB2012
Proceedings of the VLDB Endowment (PVLDB), Vol. 5, No. 11, pp. 1244-1255 (2012)
null
null
cs.DB
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Analytic functions represent the state-of-the-art way of performing complex data analysis within a single SQL statement. In particular, an important class of analytic functions that has been frequently used in commercial systems to support OLAP and decision support applications is the class of window functions. A win...
[ { "version": "v1", "created": "Wed, 1 Aug 2012 03:52:40 GMT" } ]
2012-08-02T00:00:00
[ [ "Cao", "Yu", "" ], [ "Chan", "Chee-Yong", "" ], [ "Li", "Jie", "" ], [ "Tan", "Kian-Lee", "" ] ]
TITLE: Optimization of Analytic Window Functions ABSTRACT: Analytic functions represent the state-of-the-art way of performing complex data analysis within a single SQL statement. In particular, an important class of analytic functions that has been frequently used in commercial systems to support OLAP and decision...
1208.0090
James Cheng
James Cheng, Zechao Shang, Hong Cheng, Haixun Wang, Jeffrey Xu Yu
K-Reach: Who is in Your Small World
VLDB2012
Proceedings of the VLDB Endowment (PVLDB), Vol. 5, No. 11, pp. 1292-1303 (2012)
null
null
cs.DB
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We study the problem of answering k-hop reachability queries in a directed graph, i.e., whether there exists a directed path of length k, from a source query vertex to a target query vertex in the input graph. The problem of k-hop reachability is a general problem of the classic reachability (where k=infinity). Exist...
[ { "version": "v1", "created": "Wed, 1 Aug 2012 03:55:46 GMT" } ]
2012-08-02T00:00:00
[ [ "Cheng", "James", "" ], [ "Shang", "Zechao", "" ], [ "Cheng", "Hong", "" ], [ "Wang", "Haixun", "" ], [ "Yu", "Jeffrey Xu", "" ] ]
TITLE: K-Reach: Who is in Your Small World ABSTRACT: We study the problem of answering k-hop reachability queries in a directed graph, i.e., whether there exists a directed path of length k, from a source query vertex to a target query vertex in the input graph. The problem of k-hop reachability is a general proble...
1208.0221
Ziyu Guan
Ziyu Guan, Xifeng Yan, Lance M. Kaplan
Measuring Two-Event Structural Correlations on Graphs
VLDB2012
Proceedings of the VLDB Endowment (PVLDB), Vol. 5, No. 11, pp. 1400-1411 (2012)
null
null
cs.DB
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Real-life graphs usually have various kinds of events happening on them, e.g., product purchases in online social networks and intrusion alerts in computer networks. The occurrences of events on the same graph could be correlated, exhibiting either attraction or repulsion. Such structural correlations can reveal impo...
[ { "version": "v1", "created": "Wed, 1 Aug 2012 14:12:02 GMT" } ]
2012-08-02T00:00:00
[ [ "Guan", "Ziyu", "" ], [ "Yan", "Xifeng", "" ], [ "Kaplan", "Lance M.", "" ] ]
TITLE: Measuring Two-Event Structural Correlations on Graphs ABSTRACT: Real-life graphs usually have various kinds of events happening on them, e.g., product purchases in online social networks and intrusion alerts in computer networks. The occurrences of events on the same graph could be correlated, exhibiting eit...
1208.0222
Feifei Li
Jeffrey Jestes, Jeff M. Phillips, Feifei Li, Mingwang Tang
Ranking Large Temporal Data
VLDB2012
Proceedings of the VLDB Endowment (PVLDB), Vol. 5, No. 11, pp. 1412-1423 (2012)
null
null
cs.DB
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Ranking temporal data has not been studied until recently, even though ranking is an important operator (being promoted as a firstclass citizen) in database systems. However, only the instant top-k queries on temporal data were studied in, where objects with the k highest scores at a query time instance t are to be r...
[ { "version": "v1", "created": "Wed, 1 Aug 2012 14:12:21 GMT" } ]
2012-08-02T00:00:00
[ [ "Jestes", "Jeffrey", "" ], [ "Phillips", "Jeff M.", "" ], [ "Li", "Feifei", "" ], [ "Tang", "Mingwang", "" ] ]
TITLE: Ranking Large Temporal Data ABSTRACT: Ranking temporal data has not been studied until recently, even though ranking is an important operator (being promoted as a firstclass citizen) in database systems. However, only the instant top-k queries on temporal data were studied in, where objects with the k highes...
1208.0225
Alexander Hall
Alexander Hall, Olaf Bachmann, Robert B\"ussow, Silviu G\u{a}nceanu, Marc Nunkesser
Processing a Trillion Cells per Mouse Click
VLDB2012
Proceedings of the VLDB Endowment (PVLDB), Vol. 5, No. 11, pp. 1436-1446 (2012)
null
null
cs.DB
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Column-oriented database systems have been a real game changer for the industry in recent years. Highly tuned and performant systems have evolved that provide users with the possibility of answering ad hoc queries over large datasets in an interactive manner. In this paper we present the column-oriented datastore dev...
[ { "version": "v1", "created": "Wed, 1 Aug 2012 14:13:23 GMT" } ]
2012-08-02T00:00:00
[ [ "Hall", "Alexander", "" ], [ "Bachmann", "Olaf", "" ], [ "Büssow", "Robert", "" ], [ "Gănceanu", "Silviu", "" ], [ "Nunkesser", "Marc", "" ] ]
TITLE: Processing a Trillion Cells per Mouse Click ABSTRACT: Column-oriented database systems have been a real game changer for the industry in recent years. Highly tuned and performant systems have evolved that provide users with the possibility of answering ad hoc queries over large datasets in an interactive man...
1208.0276
Farhan Tauheed
Farhan Tauheed, Thomas Heinis, Felix Sh\"urmann, Henry Markram, Anastasia Ailamaki
SCOUT: Prefetching for Latent Feature Following Queries
VLDB2012
Proceedings of the VLDB Endowment (PVLDB), Vol. 5, No. 11, pp. 1531-1542 (2012)
null
null
cs.DB
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Today's scientists are quickly moving from in vitro to in silico experimentation: they no longer analyze natural phenomena in a petri dish, but instead they build models and simulate them. Managing and analyzing the massive amounts of data involved in simulations is a major task. Yet, they lack the tools to efficient...
[ { "version": "v1", "created": "Wed, 1 Aug 2012 16:49:56 GMT" } ]
2012-08-02T00:00:00
[ [ "Tauheed", "Farhan", "" ], [ "Heinis", "Thomas", "" ], [ "Shürmann", "Felix", "" ], [ "Markram", "Henry", "" ], [ "Ailamaki", "Anastasia", "" ] ]
TITLE: SCOUT: Prefetching for Latent Feature Following Queries ABSTRACT: Today's scientists are quickly moving from in vitro to in silico experimentation: they no longer analyze natural phenomena in a petri dish, but instead they build models and simulate them. Managing and analyzing the massive amounts of data inv...
1208.0286
Haohan Zhu
Haohan Zhu, George Kollios, Vassilis Athitsos
A Generic Framework for Efficient and Effective Subsequence Retrieval
VLDB2012
Proceedings of the VLDB Endowment (PVLDB), Vol. 5, No. 11, pp. 1579-1590 (2012)
null
null
cs.DB
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper proposes a general framework for matching similar subsequences in both time series and string databases. The matching results are pairs of query subsequences and database subsequences. The framework finds all possible pairs of similar subsequences if the distance measure satisfies the "consistency" propert...
[ { "version": "v1", "created": "Wed, 1 Aug 2012 17:20:11 GMT" } ]
2012-08-02T00:00:00
[ [ "Zhu", "Haohan", "" ], [ "Kollios", "George", "" ], [ "Athitsos", "Vassilis", "" ] ]
TITLE: A Generic Framework for Efficient and Effective Subsequence Retrieval ABSTRACT: This paper proposes a general framework for matching similar subsequences in both time series and string databases. The matching results are pairs of query subsequences and database subsequences. The framework finds all possible ...
1207.7103
John Whitbeck
John Whitbeck, Marcelo Dias de Amorim, Vania Conan, Jean-Loup Guillaume
Temporal Reachability Graphs
In proceedings ACM Mobicom 2012
null
null
null
cs.NI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
While a natural fit for modeling and understanding mobile networks, time-varying graphs remain poorly understood. Indeed, many of the usual concepts of static graphs have no obvious counterpart in time-varying ones. In this paper, we introduce the notion of temporal reachability graphs. A (tau,delta)-reachability gra...
[ { "version": "v1", "created": "Mon, 30 Jul 2012 21:05:54 GMT" } ]
2012-08-01T00:00:00
[ [ "Whitbeck", "John", "" ], [ "de Amorim", "Marcelo Dias", "" ], [ "Conan", "Vania", "" ], [ "Guillaume", "Jean-Loup", "" ] ]
TITLE: Temporal Reachability Graphs ABSTRACT: While a natural fit for modeling and understanding mobile networks, time-varying graphs remain poorly understood. Indeed, many of the usual concepts of static graphs have no obvious counterpart in time-varying ones. In this paper, we introduce the notion of temporal rea...
1207.6269
Arnau Prat-P\'erez
Arnau Prat-P\'erez, David Dominguez-Sal, Josep M. Brunat, Josep-Lluis Larriba-Pey
Shaping Communities out of Triangles
10 pages, 6 figures, CIKM 2012
null
null
null
cs.SI physics.soc-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Community detection has arisen as one of the most relevant topics in the field of graph data mining due to its importance in many fields such as biology, social networks or network traffic analysis. The metrics proposed to shape communities are generic and follow two approaches: maximizing the internal density of suc...
[ { "version": "v1", "created": "Thu, 26 Jul 2012 13:36:59 GMT" } ]
2012-07-27T00:00:00
[ [ "Prat-Pérez", "Arnau", "" ], [ "Dominguez-Sal", "David", "" ], [ "Brunat", "Josep M.", "" ], [ "Larriba-Pey", "Josep-Lluis", "" ] ]
TITLE: Shaping Communities out of Triangles ABSTRACT: Community detection has arisen as one of the most relevant topics in the field of graph data mining due to its importance in many fields such as biology, social networks or network traffic analysis. The metrics proposed to shape communities are generic and follo...
1207.6329
Sean Chester
Sean Chester and Alex Thomo and S. Venkatesh and Sue Whitesides
Computing optimal k-regret minimizing sets with top-k depth contours
10 pages, 9 figures
null
null
null
cs.DB cs.CG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Regret minimizing sets are a very recent approach to representing a dataset D with a small subset S of representative tuples. The set S is chosen such that executing any top-1 query on S rather than D is minimally perceptible to any user. To discover an optimal regret minimizing set of a predetermined cardinality is ...
[ { "version": "v1", "created": "Thu, 26 Jul 2012 16:59:17 GMT" } ]
2012-07-27T00:00:00
[ [ "Chester", "Sean", "" ], [ "Thomo", "Alex", "" ], [ "Venkatesh", "S.", "" ], [ "Whitesides", "Sue", "" ] ]
TITLE: Computing optimal k-regret minimizing sets with top-k depth contours ABSTRACT: Regret minimizing sets are a very recent approach to representing a dataset D with a small subset S of representative tuples. The set S is chosen such that executing any top-1 query on S rather than D is minimally perceptible to a...
1207.6379
Jose Bento
Jos\'e Bento, Nadia Fawaz, Andrea Montanari, Stratis Ioannidis
Identifying Users From Their Rating Patterns
Winner of the 2011 Challenge on Context-Aware Movie Recommendation (RecSys 2011 - CAMRa2011)
null
null
null
cs.IR cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper reports on our analysis of the 2011 CAMRa Challenge dataset (Track 2) for context-aware movie recommendation systems. The train dataset comprises 4,536,891 ratings provided by 171,670 users on 23,974$ movies, as well as the household groupings of a subset of the users. The test dataset comprises 5,450 rati...
[ { "version": "v1", "created": "Thu, 26 Jul 2012 19:27:03 GMT" } ]
2012-07-27T00:00:00
[ [ "Bento", "José", "" ], [ "Fawaz", "Nadia", "" ], [ "Montanari", "Andrea", "" ], [ "Ioannidis", "Stratis", "" ] ]
TITLE: Identifying Users From Their Rating Patterns ABSTRACT: This paper reports on our analysis of the 2011 CAMRa Challenge dataset (Track 2) for context-aware movie recommendation systems. The train dataset comprises 4,536,891 ratings provided by 171,670 users on 23,974$ movies, as well as the household groupings...
1202.0077
Marco Alberto Javarone
Giuliano Armano and Marco Alberto Javarone
Datasets as Interacting Particle Systems: a Framework for Clustering
13 pages, 5 figures. Submitted to ACS - Advances in Complex Systems
null
null
null
cond-mat.stat-mech cs.SI physics.soc-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper we propose a framework inspired by interacting particle physics and devised to perform clustering on multidimensional datasets. To this end, any given dataset is modeled as an interacting particle system, under the assumption that each element of the dataset corresponds to a different particle and that ...
[ { "version": "v1", "created": "Wed, 1 Feb 2012 01:40:54 GMT" }, { "version": "v2", "created": "Wed, 8 Feb 2012 18:28:45 GMT" }, { "version": "v3", "created": "Thu, 9 Feb 2012 18:31:16 GMT" }, { "version": "v4", "created": "Tue, 24 Jul 2012 22:23:48 GMT" } ]
2012-07-26T00:00:00
[ [ "Armano", "Giuliano", "" ], [ "Javarone", "Marco Alberto", "" ] ]
TITLE: Datasets as Interacting Particle Systems: a Framework for Clustering ABSTRACT: In this paper we propose a framework inspired by interacting particle physics and devised to perform clustering on multidimensional datasets. To this end, any given dataset is modeled as an interacting particle system, under the a...
1205.2822
Zi-Ke Zhang Dr.
Tian Qiu, Zi-Ke Zhang, Guang Chen
Promotional effect on cold start problem and diversity in a data characteristic based recommendation method
null
null
null
null
cs.IR physics.soc-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Pure methods generally perform excellently in either recommendation accuracy or diversity, whereas hybrid methods generally outperform pure cases in both recommendation accuracy and diversity, but encounter the dilemma of optimal hybridization parameter selection for different recommendation focuses. In this article,...
[ { "version": "v1", "created": "Sun, 13 May 2012 02:47:08 GMT" }, { "version": "v2", "created": "Mon, 11 Jun 2012 15:43:06 GMT" }, { "version": "v3", "created": "Tue, 24 Jul 2012 20:17:06 GMT" } ]
2012-07-26T00:00:00
[ [ "Qiu", "Tian", "" ], [ "Zhang", "Zi-Ke", "" ], [ "Chen", "Guang", "" ] ]
TITLE: Promotional effect on cold start problem and diversity in a data characteristic based recommendation method ABSTRACT: Pure methods generally perform excellently in either recommendation accuracy or diversity, whereas hybrid methods generally outperform pure cases in both recommendation accuracy and diversi...
1207.6037
Emilio Ferrara
Giovanni Quattrone, Emilio Ferrara, Pasquale De Meo, Licia Capra
Measuring Similarity in Large-scale Folksonomies
7 pages, SEKE '11: 23rd International Conference on Software Engineering and Knowledge Engineering
SEKE '11: Proceedings of the 23rd International Conference on Software Engineering and Knowledge Engineering, pp. 385-391, 2011
null
null
cs.IR cs.SI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Social (or folksonomic) tagging has become a very popular way to describe content within Web 2.0 websites. Unlike taxonomies, which overimpose a hierarchical categorisation of content, folksonomies enable end-users to freely create and choose the categories (in this case, tags) that best describe some content. Howeve...
[ { "version": "v1", "created": "Wed, 25 Jul 2012 16:01:22 GMT" } ]
2012-07-26T00:00:00
[ [ "Quattrone", "Giovanni", "" ], [ "Ferrara", "Emilio", "" ], [ "De Meo", "Pasquale", "" ], [ "Capra", "Licia", "" ] ]
TITLE: Measuring Similarity in Large-scale Folksonomies ABSTRACT: Social (or folksonomic) tagging has become a very popular way to describe content within Web 2.0 websites. Unlike taxonomies, which overimpose a hierarchical categorisation of content, folksonomies enable end-users to freely create and choose the cat...
1207.5775
Peter Morgan
Peter Morgan
A graphical presentation of signal delays in the datasets of Weihs et al
9 pages, 9 figures (all data visualization)
null
null
null
quant-ph physics.ins-det
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A graphical presentation of the timing of avalanche photodiode events in the datasets from the experiment of Weihs et al. [Phys. Rev. Lett. 81, 5039 (1998)] makes manifest the existence of two types of signal delay: (1) The introduction of rapid switching of the input to a pair of transverse electro-optical modulator...
[ { "version": "v1", "created": "Tue, 24 Jul 2012 19:09:28 GMT" } ]
2012-07-25T00:00:00
[ [ "Morgan", "Peter", "" ] ]
TITLE: A graphical presentation of signal delays in the datasets of Weihs et al ABSTRACT: A graphical presentation of the timing of avalanche photodiode events in the datasets from the experiment of Weihs et al. [Phys. Rev. Lett. 81, 5039 (1998)] makes manifest the existence of two types of signal delay: (1) The in...
1207.3031
Konstantinos Tsianos
Konstantinos I. Tsianos and Michael G. Rabbat
Distributed Strongly Convex Optimization
18 pages single column draftcls format, 1 figure, Submitted to Allerton 2012
null
null
null
cs.DC cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A lot of effort has been invested into characterizing the convergence rates of gradient based algorithms for non-linear convex optimization. Recently, motivated by large datasets and problems in machine learning, the interest has shifted towards distributed optimization. In this work we present a distributed algorith...
[ { "version": "v1", "created": "Thu, 12 Jul 2012 17:38:46 GMT" }, { "version": "v2", "created": "Fri, 20 Jul 2012 03:08:51 GMT" } ]
2012-07-23T00:00:00
[ [ "Tsianos", "Konstantinos I.", "" ], [ "Rabbat", "Michael G.", "" ] ]
TITLE: Distributed Strongly Convex Optimization ABSTRACT: A lot of effort has been invested into characterizing the convergence rates of gradient based algorithms for non-linear convex optimization. Recently, motivated by large datasets and problems in machine learning, the interest has shifted towards distributed ...
1207.4525
Simon Lacoste-Julien
Simon Lacoste-Julien, Konstantina Palla, Alex Davies, Gjergji Kasneci, Thore Graepel, Zoubin Ghahramani
SiGMa: Simple Greedy Matching for Aligning Large Knowledge Bases
10 pages + 2 pages appendix; 5 figures -- initial preprint
null
null
null
cs.AI cs.DB cs.IR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The Internet has enabled the creation of a growing number of large-scale knowledge bases in a variety of domains containing complementary information. Tools for automatically aligning these knowledge bases would make it possible to unify many sources of structured knowledge and answer complex queries. However, the ef...
[ { "version": "v1", "created": "Thu, 19 Jul 2012 00:15:05 GMT" } ]
2012-07-20T00:00:00
[ [ "Lacoste-Julien", "Simon", "" ], [ "Palla", "Konstantina", "" ], [ "Davies", "Alex", "" ], [ "Kasneci", "Gjergji", "" ], [ "Graepel", "Thore", "" ], [ "Ghahramani", "Zoubin", "" ] ]
TITLE: SiGMa: Simple Greedy Matching for Aligning Large Knowledge Bases ABSTRACT: The Internet has enabled the creation of a growing number of large-scale knowledge bases in a variety of domains containing complementary information. Tools for automatically aligning these knowledge bases would make it possible to un...
1207.4567
Rong-Hua Li
Rong-Hua Li, Jeffrey Xu Yu
Efficient Core Maintenance in Large Dynamic Graphs
null
null
null
null
cs.DS cs.DB cs.SI physics.soc-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The $k$-core decomposition in a graph is a fundamental problem for social network analysis. The problem of $k$-core decomposition is to calculate the core number for every node in a graph. Previous studies mainly focus on $k$-core decomposition in a static graph. There exists a linear time algorithm for $k$-core deco...
[ { "version": "v1", "created": "Thu, 19 Jul 2012 06:57:10 GMT" } ]
2012-07-20T00:00:00
[ [ "Li", "Rong-Hua", "" ], [ "Yu", "Jeffrey Xu", "" ] ]
TITLE: Efficient Core Maintenance in Large Dynamic Graphs ABSTRACT: The $k$-core decomposition in a graph is a fundamental problem for social network analysis. The problem of $k$-core decomposition is to calculate the core number for every node in a graph. Previous studies mainly focus on $k$-core decomposition in ...
1201.4639
Vicente Pablo Guerrero Bote Vicente Pablo Guerrero Bote
Vicente P. Guerrero-Bote and Felix Moya-Anegon
A further step forward in measuring journals' scientific prestige: The SJR2 indicator
null
null
null
null
cs.DL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A new size-independent indicator of scientific journal prestige, the SJR2 indicator, is proposed. This indicator takes into account not only the prestige of the citing scientific journal but also its closeness to the cited journal using the cosine of the angle between the vectors of the two journals' cocitation profi...
[ { "version": "v1", "created": "Mon, 23 Jan 2012 07:39:03 GMT" }, { "version": "v2", "created": "Wed, 18 Jul 2012 04:19:07 GMT" } ]
2012-07-19T00:00:00
[ [ "Guerrero-Bote", "Vicente P.", "" ], [ "Moya-Anegon", "Felix", "" ] ]
TITLE: A further step forward in measuring journals' scientific prestige: The SJR2 indicator ABSTRACT: A new size-independent indicator of scientific journal prestige, the SJR2 indicator, is proposed. This indicator takes into account not only the prestige of the citing scientific journal but also its closeness t...
1207.4129
Dragomir Anguelov
Dragomir Anguelov, Daphne Koller, Hoi-Cheung Pang, Praveen Srinivasan, Sebastian Thrun
Recovering Articulated Object Models from 3D Range Data
Appears in Proceedings of the Twentieth Conference on Uncertainty in Artificial Intelligence (UAI2004)
null
null
UAI-P-2004-PG-18-26
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We address the problem of unsupervised learning of complex articulated object models from 3D range data. We describe an algorithm whose input is a set of meshes corresponding to different configurations of an articulated object. The algorithm automatically recovers a decomposition of the object into approximately rig...
[ { "version": "v1", "created": "Wed, 11 Jul 2012 14:48:13 GMT" } ]
2012-07-19T00:00:00
[ [ "Anguelov", "Dragomir", "" ], [ "Koller", "Daphne", "" ], [ "Pang", "Hoi-Cheung", "" ], [ "Srinivasan", "Praveen", "" ], [ "Thrun", "Sebastian", "" ] ]
TITLE: Recovering Articulated Object Models from 3D Range Data ABSTRACT: We address the problem of unsupervised learning of complex articulated object models from 3D range data. We describe an algorithm whose input is a set of meshes corresponding to different configurations of an articulated object. The algorithm ...
1207.4132
Rodney Nielsen
Rodney Nielsen
MOB-ESP and other Improvements in Probability Estimation
Appears in Proceedings of the Twentieth Conference on Uncertainty in Artificial Intelligence (UAI2004)
null
null
UAI-P-2004-PG-418-425
cs.LG cs.AI stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A key prerequisite to optimal reasoning under uncertainty in intelligent systems is to start with good class probability estimates. This paper improves on the current best probability estimation trees (Bagged-PETs) and also presents a new ensemble-based algorithm (MOB-ESP). Comparisons are made using several benchmar...
[ { "version": "v1", "created": "Wed, 11 Jul 2012 14:51:03 GMT" } ]
2012-07-19T00:00:00
[ [ "Nielsen", "Rodney", "" ] ]
TITLE: MOB-ESP and other Improvements in Probability Estimation ABSTRACT: A key prerequisite to optimal reasoning under uncertainty in intelligent systems is to start with good class probability estimates. This paper improves on the current best probability estimation trees (Bagged-PETs) and also presents a new ens...
1207.4146
Rong Jin
Rong Jin, Luo Si
A Bayesian Approach toward Active Learning for Collaborative Filtering
Appears in Proceedings of the Twentieth Conference on Uncertainty in Artificial Intelligence (UAI2004)
null
null
UAI-P-2004-PG-278-285
cs.LG cs.IR stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Collaborative filtering is a useful technique for exploiting the preference patterns of a group of users to predict the utility of items for the active user. In general, the performance of collaborative filtering depends on the number of rated examples given by the active user. The more the number of rated examples g...
[ { "version": "v1", "created": "Wed, 11 Jul 2012 14:55:41 GMT" } ]
2012-07-19T00:00:00
[ [ "Jin", "Rong", "" ], [ "Si", "Luo", "" ] ]
TITLE: A Bayesian Approach toward Active Learning for Collaborative Filtering ABSTRACT: Collaborative filtering is a useful technique for exploiting the preference patterns of a group of users to predict the utility of items for the active user. In general, the performance of collaborative filtering depends on the ...
1207.4169
Michal Rosen-Zvi
Michal Rosen-Zvi, Thomas Griffiths, Mark Steyvers, Padhraic Smyth
The Author-Topic Model for Authors and Documents
Appears in Proceedings of the Twentieth Conference on Uncertainty in Artificial Intelligence (UAI2004)
null
null
UAI-P-2004-PG-487-494
cs.IR cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We introduce the author-topic model, a generative model for documents that extends Latent Dirichlet Allocation (LDA; Blei, Ng, & Jordan, 2003) to include authorship information. Each author is associated with a multinomial distribution over topics and each topic is associated with a multinomial distribution over word...
[ { "version": "v1", "created": "Wed, 11 Jul 2012 15:05:53 GMT" } ]
2012-07-19T00:00:00
[ [ "Rosen-Zvi", "Michal", "" ], [ "Griffiths", "Thomas", "" ], [ "Steyvers", "Mark", "" ], [ "Smyth", "Padhraic", "" ] ]
TITLE: The Author-Topic Model for Authors and Documents ABSTRACT: We introduce the author-topic model, a generative model for documents that extends Latent Dirichlet Allocation (LDA; Blei, Ng, & Jordan, 2003) to include authorship information. Each author is associated with a multinomial distribution over topics an...
1207.4293
Piotr Br\'odka
Piotr Br\'odka, Przemys{\l}aw Kazienko, Katarzyna Musia{\l}, Krzysztof Skibicki
Analysis of Neighbourhoods in Multi-layered Dynamic Social Networks
16 pages, International Journal of Computational Intelligence Systems
International Journal of Computational Intelligence Systems, Vol. 5, No. 3 (June, 2012), 582-596
10.1080/18756891.2012.696922
null
cs.SI physics.soc-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Social networks existing among employees, customers or users of various IT systems have become one of the research areas of growing importance. A social network consists of nodes - social entities and edges linking pairs of nodes. In regular, one-layered social networks, two nodes - i.e. people are connected with a s...
[ { "version": "v1", "created": "Wed, 18 Jul 2012 08:06:25 GMT" } ]
2012-07-19T00:00:00
[ [ "Bródka", "Piotr", "" ], [ "Kazienko", "Przemysław", "" ], [ "Musiał", "Katarzyna", "" ], [ "Skibicki", "Krzysztof", "" ] ]
TITLE: Analysis of Neighbourhoods in Multi-layered Dynamic Social Networks ABSTRACT: Social networks existing among employees, customers or users of various IT systems have become one of the research areas of growing importance. A social network consists of nodes - social entities and edges linking pairs of nodes. ...
1207.3790
Hocine Cherifi
Vincent Labatut (BIT Lab), Hocine Cherifi (Le2i)
Accuracy Measures for the Comparison of Classifiers
The 5th International Conference on Information Technology, amman : Jordanie (2011)
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The selection of the best classification algorithm for a given dataset is a very widespread problem. It is also a complex one, in the sense it requires to make several important methodological choices. Among them, in this work we focus on the measure used to assess the classification performance and rank the algorith...
[ { "version": "v1", "created": "Mon, 16 Jul 2012 08:49:34 GMT" } ]
2012-07-18T00:00:00
[ [ "Labatut", "Vincent", "", "BIT Lab" ], [ "Cherifi", "Hocine", "", "Le2i" ] ]
TITLE: Accuracy Measures for the Comparison of Classifiers ABSTRACT: The selection of the best classification algorithm for a given dataset is a very widespread problem. It is also a complex one, in the sense it requires to make several important methodological choices. Among them, in this work we focus on the meas...
1207.3809
Julian McAuley
Julian McAuley and Jure Leskovec
Image Labeling on a Network: Using Social-Network Metadata for Image Classification
ECCV 2012; 14 pages, 4 figures
null
null
null
cs.CV cs.SI physics.soc-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Large-scale image retrieval benchmarks invariably consist of images from the Web. Many of these benchmarks are derived from online photo sharing networks, like Flickr, which in addition to hosting images also provide a highly interactive social community. Such communities generate rich metadata that can naturally be ...
[ { "version": "v1", "created": "Mon, 16 Jul 2012 20:04:12 GMT" } ]
2012-07-18T00:00:00
[ [ "McAuley", "Julian", "" ], [ "Leskovec", "Jure", "" ] ]
TITLE: Image Labeling on a Network: Using Social-Network Metadata for Image Classification ABSTRACT: Large-scale image retrieval benchmarks invariably consist of images from the Web. Many of these benchmarks are derived from online photo sharing networks, like Flickr, which in addition to hosting images also prov...
1207.3520
Fabian Pedregosa
Fabian Pedregosa (INRIA Paris - Rocquencourt), Alexandre Gramfort (LNAO, INRIA Saclay - Ile de France), Ga\"el Varoquaux (LNAO, INRIA Saclay - Ile de France), Bertrand Thirion (INRIA Saclay - Ile de France), Christophe Pallier (NEUROSPIN), Elodie Cauvet (NEUROSPIN)
Improved brain pattern recovery through ranking approaches
null
Pattern Recognition in NeuroImaging (PRNI 2012) (2012)
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Inferring the functional specificity of brain regions from functional Magnetic Resonance Images (fMRI) data is a challenging statistical problem. While the General Linear Model (GLM) remains the standard approach for brain mapping, supervised learning techniques (a.k.a.} decoding) have proven to be useful to capture ...
[ { "version": "v1", "created": "Sun, 15 Jul 2012 15:06:35 GMT" } ]
2012-07-17T00:00:00
[ [ "Pedregosa", "Fabian", "", "INRIA Paris - Rocquencourt" ], [ "Gramfort", "Alexandre", "", "LNAO, INRIA Saclay - Ile de France" ], [ "Varoquaux", "Gaël", "", "LNAO, INRIA Saclay -\n Ile de France" ], [ "Thirion", "Bertrand", "", "INRIA Sa...
TITLE: Improved brain pattern recovery through ranking approaches ABSTRACT: Inferring the functional specificity of brain regions from functional Magnetic Resonance Images (fMRI) data is a challenging statistical problem. While the General Linear Model (GLM) remains the standard approach for brain mapping, supervis...
1207.3532
Xifeng Yan Xifeng Yan
Yang Li, Pegah Kamousi, Fangqiu Han, Shengqi Yang, Xifeng Yan, Subhash Suri
Memory Efficient De Bruijn Graph Construction
13 pages, 19 figures, 1 table
null
null
null
cs.DS cs.DB
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Massively parallel DNA sequencing technologies are revolutionizing genomics research. Billions of short reads generated at low costs can be assembled for reconstructing the whole genomes. Unfortunately, the large memory footprint of the existing de novo assembly algorithms makes it challenging to get the assembly don...
[ { "version": "v1", "created": "Sun, 15 Jul 2012 19:45:19 GMT" } ]
2012-07-17T00:00:00
[ [ "Li", "Yang", "" ], [ "Kamousi", "Pegah", "" ], [ "Han", "Fangqiu", "" ], [ "Yang", "Shengqi", "" ], [ "Yan", "Xifeng", "" ], [ "Suri", "Subhash", "" ] ]
TITLE: Memory Efficient De Bruijn Graph Construction ABSTRACT: Massively parallel DNA sequencing technologies are revolutionizing genomics research. Billions of short reads generated at low costs can be assembled for reconstructing the whole genomes. Unfortunately, the large memory footprint of the existing de novo...
1207.2600
Sokyna Alqatawneh Dr
Sokyna Qatawneh, Afaf Alneaimi, Thamer Rawashdeh, Mmohammad Muhairat, Rami Qahwaji and Stan Ipson
Efficient Prediction of DNA-Binding Proteins Using Machine Learning
null
S. Qatawneh, A. Alneaimi, Th. Rawashdeh, M. Muhairat, R. Qahwaji and S. Ipson,"Efficient Prediction of DNA-Binding Proteins using Machine Learning", International Journal on Bioinformatics & Biosciences (IJBB) Vol.2, No.2, June 2012
null
null
cs.CV q-bio.QM
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
DNA-binding proteins are a class of proteins which have a specific or general affinity to DNA and include three important components: transcription factors; nucleases, and histones. DNA-binding proteins also perform important roles in many types of cellular activities. In this paper we describe machine learning syste...
[ { "version": "v1", "created": "Wed, 11 Jul 2012 11:28:57 GMT" } ]
2012-07-12T00:00:00
[ [ "Qatawneh", "Sokyna", "" ], [ "Alneaimi", "Afaf", "" ], [ "Rawashdeh", "Thamer", "" ], [ "Muhairat", "Mmohammad", "" ], [ "Qahwaji", "Rami", "" ], [ "Ipson", "Stan", "" ] ]
TITLE: Efficient Prediction of DNA-Binding Proteins Using Machine Learning ABSTRACT: DNA-binding proteins are a class of proteins which have a specific or general affinity to DNA and include three important components: transcription factors; nucleases, and histones. DNA-binding proteins also perform important roles...
1207.2424
Daniel Jones
Daniel C. Jones, Walter L. Ruzzo, Xinxia Peng, and Michael G. Katze
Compression of next-generation sequencing reads aided by highly efficient de novo assembly
null
null
null
null
q-bio.QM cs.DS q-bio.GN
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present Quip, a lossless compression algorithm for next-generation sequencing data in the FASTQ and SAM/BAM formats. In addition to implementing reference-based compression, we have developed, to our knowledge, the first assembly-based compressor, using a novel de novo assembly algorithm. A probabilistic data stru...
[ { "version": "v1", "created": "Tue, 10 Jul 2012 17:49:17 GMT" } ]
2012-07-11T00:00:00
[ [ "Jones", "Daniel C.", "" ], [ "Ruzzo", "Walter L.", "" ], [ "Peng", "Xinxia", "" ], [ "Katze", "Michael G.", "" ] ]
TITLE: Compression of next-generation sequencing reads aided by highly efficient de novo assembly ABSTRACT: We present Quip, a lossless compression algorithm for next-generation sequencing data in the FASTQ and SAM/BAM formats. In addition to implementing reference-based compression, we have developed, to our kno...
1205.6912
D\'avid W\'agner
D\'avid W\'agner, Emiliano Fable, Andreas Pitzschke, Olivier Sauter, Henri Weisen
Understanding the core density profile in TCV H-mode plasmas
23 pages, 12 figures
2012 Plasma Phys. Control. Fusion 54 085018
10.1088/0741-3335/54/8/085018
null
physics.plasm-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Results from a database analysis of H-mode electron density profiles on the Tokamak \`a Configuration Variable (TCV) in stationary conditions show that the logarithmic electron density gradient increases with collisionality. By contrast, usual observations of H-modes showed that the electron density profiles tend to ...
[ { "version": "v1", "created": "Thu, 31 May 2012 08:23:50 GMT" }, { "version": "v2", "created": "Mon, 9 Jul 2012 13:50:53 GMT" } ]
2012-07-10T00:00:00
[ [ "Wágner", "Dávid", "" ], [ "Fable", "Emiliano", "" ], [ "Pitzschke", "Andreas", "" ], [ "Sauter", "Olivier", "" ], [ "Weisen", "Henri", "" ] ]
TITLE: Understanding the core density profile in TCV H-mode plasmas ABSTRACT: Results from a database analysis of H-mode electron density profiles on the Tokamak \`a Configuration Variable (TCV) in stationary conditions show that the logarithmic electron density gradient increases with collisionality. By contrast, ...
1207.1765
Jonathan Masci
Jonathan Masci and Ueli Meier and Gabriel Fricout and J\"urgen Schmidhuber
Object Recognition with Multi-Scale Pyramidal Pooling Networks
null
null
null
null
cs.CV cs.NE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present a Multi-Scale Pyramidal Pooling Network, featuring a novel pyramidal pooling layer at multiple scales and a novel encoding layer. Thanks to the former the network does not require all images of a given classification task to be of equal size. The encoding layer improves generalisation performance in compar...
[ { "version": "v1", "created": "Sat, 7 Jul 2012 06:27:52 GMT" } ]
2012-07-10T00:00:00
[ [ "Masci", "Jonathan", "" ], [ "Meier", "Ueli", "" ], [ "Fricout", "Gabriel", "" ], [ "Schmidhuber", "Jürgen", "" ] ]
TITLE: Object Recognition with Multi-Scale Pyramidal Pooling Networks ABSTRACT: We present a Multi-Scale Pyramidal Pooling Network, featuring a novel pyramidal pooling layer at multiple scales and a novel encoding layer. Thanks to the former the network does not require all images of a given classification task to ...
1207.1916
Alejandro Frery
Eliana S. de Almeida, Antonio C. Medeiros and Alejandro C. Frery
How good are MatLab, Octave and Scilab for Computational Modelling?
Accepted for publication in the Computational and Applied Mathematics journal
null
null
null
cs.MS stat.CO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this article we test the accuracy of three platforms used in computational modelling: MatLab, Octave and Scilab, running on i386 architecture and three operating systems (Windows, Ubuntu and Mac OS). We submitted them to numerical tests using standard data sets and using the functions provided by each platform. A ...
[ { "version": "v1", "created": "Sun, 8 Jul 2012 21:52:03 GMT" } ]
2012-07-10T00:00:00
[ [ "de Almeida", "Eliana S.", "" ], [ "Medeiros", "Antonio C.", "" ], [ "Frery", "Alejandro C.", "" ] ]
TITLE: How good are MatLab, Octave and Scilab for Computational Modelling? ABSTRACT: In this article we test the accuracy of three platforms used in computational modelling: MatLab, Octave and Scilab, running on i386 architecture and three operating systems (Windows, Ubuntu and Mac OS). We submitted them to numeric...
1207.1394
Andreas Krause
Andreas Krause, Carlos E. Guestrin
Near-optimal Nonmyopic Value of Information in Graphical Models
Appears in Proceedings of the Twenty-First Conference on Uncertainty in Artificial Intelligence (UAI2005)
null
null
UAI-P-2005-PG-324-331
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A fundamental issue in real-world systems, such as sensor networks, is the selection of observations which most effectively reduce uncertainty. More specifically, we address the long standing problem of nonmyopically selecting the most informative subset of variables in a graphical model. We present the first efficie...
[ { "version": "v1", "created": "Wed, 4 Jul 2012 16:16:25 GMT" } ]
2012-07-09T00:00:00
[ [ "Krause", "Andreas", "" ], [ "Guestrin", "Carlos E.", "" ] ]
TITLE: Near-optimal Nonmyopic Value of Information in Graphical Models ABSTRACT: A fundamental issue in real-world systems, such as sensor networks, is the selection of observations which most effectively reduce uncertainty. More specifically, we address the long standing problem of nonmyopically selecting the most...
1207.0833
Fr\'ed\'eric Blanchard
Fr\'ed\'eric Blanchard and Michel Herbin
Relational Data Mining Through Extraction of Representative Exemplars
null
null
null
null
cs.AI cs.IR stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
With the growing interest on Network Analysis, Relational Data Mining is becoming an emphasized domain of Data Mining. This paper addresses the problem of extracting representative elements from a relational dataset. After defining the notion of degree of representativeness, computed using the Borda aggregation proce...
[ { "version": "v1", "created": "Tue, 3 Jul 2012 20:48:36 GMT" } ]
2012-07-05T00:00:00
[ [ "Blanchard", "Frédéric", "" ], [ "Herbin", "Michel", "" ] ]
TITLE: Relational Data Mining Through Extraction of Representative Exemplars ABSTRACT: With the growing interest on Network Analysis, Relational Data Mining is becoming an emphasized domain of Data Mining. This paper addresses the problem of extracting representative elements from a relational dataset. After defini...
1207.0913
Rong-Hua Li
Rong-Hua Li, Jeffrey Xu Yu, Zechao Shang
Estimating Node Influenceability in Social Networks
null
null
null
null
cs.SI cs.DB physics.soc-ph
http://creativecommons.org/licenses/by/3.0/
Influence analysis is a fundamental problem in social network analysis and mining. The important applications of the influence analysis in social network include influence maximization for viral marketing, finding the most influential nodes, online advertising, etc. For many of these applications, it is crucial to ev...
[ { "version": "v1", "created": "Wed, 4 Jul 2012 06:49:22 GMT" } ]
2012-07-05T00:00:00
[ [ "Li", "Rong-Hua", "" ], [ "Yu", "Jeffrey Xu", "" ], [ "Shang", "Zechao", "" ] ]
TITLE: Estimating Node Influenceability in Social Networks ABSTRACT: Influence analysis is a fundamental problem in social network analysis and mining. The important applications of the influence analysis in social network include influence maximization for viral marketing, finding the most influential nodes, onlin...
1207.0677
Romain Giot
Romain Giot (GREYC), Christophe Charrier (GREYC), Maxime Descoteaux (SCIL)
Local Water Diffusion Phenomenon Clustering From High Angular Resolution Diffusion Imaging (HARDI)
IAPR International Conference on Pattern Recognition (ICPR), Tsukuba, Japan : France (2012)
null
null
null
cs.LG cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The understanding of neurodegenerative diseases undoubtedly passes through the study of human brain white matter fiber tracts. To date, diffusion magnetic resonance imaging (dMRI) is the unique technique to obtain information about the neural architecture of the human brain, thus permitting the study of white matter ...
[ { "version": "v1", "created": "Tue, 3 Jul 2012 13:52:19 GMT" } ]
2012-07-04T00:00:00
[ [ "Giot", "Romain", "", "GREYC" ], [ "Charrier", "Christophe", "", "GREYC" ], [ "Descoteaux", "Maxime", "", "SCIL" ] ]
TITLE: Local Water Diffusion Phenomenon Clustering From High Angular Resolution Diffusion Imaging (HARDI) ABSTRACT: The understanding of neurodegenerative diseases undoubtedly passes through the study of human brain white matter fiber tracts. To date, diffusion magnetic resonance imaging (dMRI) is the unique tech...
1207.0783
Romain Giot
Romain Giot (GREYC), Christophe Rosenberger (GREYC), Bernadette Dorizzi (EPH, SAMOVAR)
Hybrid Template Update System for Unimodal Biometric Systems
IEEE International Conference on Biometrics: Theory, Applications and Systems (BTAS 2012), Washington, District of Columbia, USA : France (2012)
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Semi-supervised template update systems allow to automatically take into account the intra-class variability of the biometric data over time. Such systems can be inefficient by including too many impostor's samples or skipping too many genuine's samples. In the first case, the biometric reference drifts from the real...
[ { "version": "v1", "created": "Tue, 3 Jul 2012 19:12:13 GMT" } ]
2012-07-04T00:00:00
[ [ "Giot", "Romain", "", "GREYC" ], [ "Rosenberger", "Christophe", "", "GREYC" ], [ "Dorizzi", "Bernadette", "", "EPH, SAMOVAR" ] ]
TITLE: Hybrid Template Update System for Unimodal Biometric Systems ABSTRACT: Semi-supervised template update systems allow to automatically take into account the intra-class variability of the biometric data over time. Such systems can be inefficient by including too many impostor's samples or skipping too many ge...
1207.0784
Romain Giot
Romain Giot (GREYC), Mohamad El-Abed (GREYC), Christophe Rosenberger (GREYC)
Web-Based Benchmark for Keystroke Dynamics Biometric Systems: A Statistical Analysis
The Eighth International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIHMSP 2012), Piraeus : Greece (2012)
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Most keystroke dynamics studies have been evaluated using a specific kind of dataset in which users type an imposed login and password. Moreover, these studies are optimistics since most of them use different acquisition protocols, private datasets, controlled environment, etc. In order to enhance the accuracy of key...
[ { "version": "v1", "created": "Tue, 3 Jul 2012 19:12:56 GMT" } ]
2012-07-04T00:00:00
[ [ "Giot", "Romain", "", "GREYC" ], [ "El-Abed", "Mohamad", "", "GREYC" ], [ "Rosenberger", "Christophe", "", "GREYC" ] ]
TITLE: Web-Based Benchmark for Keystroke Dynamics Biometric Systems: A Statistical Analysis ABSTRACT: Most keystroke dynamics studies have been evaluated using a specific kind of dataset in which users type an imposed login and password. Moreover, these studies are optimistics since most of them use different acq...
1206.1728
Derek Greene
Derek Greene, Gavin Sheridan, Barry Smyth, P\'adraig Cunningham
Aggregating Content and Network Information to Curate Twitter User Lists
null
null
null
null
cs.SI cs.AI physics.soc-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Twitter introduced user lists in late 2009, allowing users to be grouped according to meaningful topics or themes. Lists have since been adopted by media outlets as a means of organising content around news stories. Thus the curation of these lists is important - they should contain the key information gatekeepers an...
[ { "version": "v1", "created": "Fri, 8 Jun 2012 11:12:53 GMT" }, { "version": "v2", "created": "Mon, 2 Jul 2012 12:20:38 GMT" } ]
2012-07-03T00:00:00
[ [ "Greene", "Derek", "" ], [ "Sheridan", "Gavin", "" ], [ "Smyth", "Barry", "" ], [ "Cunningham", "Pádraig", "" ] ]
TITLE: Aggregating Content and Network Information to Curate Twitter User Lists ABSTRACT: Twitter introduced user lists in late 2009, allowing users to be grouped according to meaningful topics or themes. Lists have since been adopted by media outlets as a means of organising content around news stories. Thus the c...
1206.6392
Nicolas Boulanger-Lewandowski
Nicolas Boulanger-Lewandowski (Universite de Montreal), Yoshua Bengio (Universite de Montreal), Pascal Vincent (Universite de Montreal)
Modeling Temporal Dependencies in High-Dimensional Sequences: Application to Polyphonic Music Generation and Transcription
Appears in Proceedings of the 29th International Conference on Machine Learning (ICML 2012)
null
null
null
cs.LG cs.SD stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We investigate the problem of modeling symbolic sequences of polyphonic music in a completely general piano-roll representation. We introduce a probabilistic model based on distribution estimators conditioned on a recurrent neural network that is able to discover temporal dependencies in high-dimensional sequences. O...
[ { "version": "v1", "created": "Wed, 27 Jun 2012 19:59:59 GMT" } ]
2012-07-03T00:00:00
[ [ "Boulanger-Lewandowski", "Nicolas", "", "Universite de Montreal" ], [ "Bengio", "Yoshua", "", "Universite de Montreal" ], [ "Vincent", "Pascal", "", "Universite de Montreal" ] ]
TITLE: Modeling Temporal Dependencies in High-Dimensional Sequences: Application to Polyphonic Music Generation and Transcription ABSTRACT: We investigate the problem of modeling symbolic sequences of polyphonic music in a completely general piano-roll representation. We introduce a probabilistic model based on d...
1206.6397
Minhua Chen
Minhua Chen (Duke University), William Carson (PA Consulting Group, Cambridge Technology Centre), Miguel Rodrigues (University College London), Robert Calderbank (Duke University), Lawrence Carin (Duke University)
Communications Inspired Linear Discriminant Analysis
Appears in Proceedings of the 29th International Conference on Machine Learning (ICML 2012)
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We study the problem of supervised linear dimensionality reduction, taking an information-theoretic viewpoint. The linear projection matrix is designed by maximizing the mutual information between the projected signal and the class label (based on a Shannon entropy measure). By harnessing a recent theoretical result ...
[ { "version": "v1", "created": "Wed, 27 Jun 2012 19:59:59 GMT" } ]
2012-07-03T00:00:00
[ [ "Chen", "Minhua", "", "Duke University" ], [ "Carson", "William", "", "PA Consulting Group,\n Cambridge Technology Centre" ], [ "Rodrigues", "Miguel", "", "University College London" ], [ "Calderbank", "Robert", "", "Duke University" ]...
TITLE: Communications Inspired Linear Discriminant Analysis ABSTRACT: We study the problem of supervised linear dimensionality reduction, taking an information-theoretic viewpoint. The linear projection matrix is designed by maximizing the mutual information between the projected signal and the class label (based o...
1206.6407
Ian Goodfellow
Ian Goodfellow (Universite de Montreal), Aaron Courville (Universite de Montreal), Yoshua Bengio (Universite de Montreal)
Large-Scale Feature Learning With Spike-and-Slab Sparse Coding
Appears in Proceedings of the 29th International Conference on Machine Learning (ICML 2012). arXiv admin note: substantial text overlap with arXiv:1201.3382
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We consider the problem of object recognition with a large number of classes. In order to overcome the low amount of labeled examples available in this setting, we introduce a new feature learning and extraction procedure based on a factor model we call spike-and-slab sparse coding (S3C). Prior work on S3C has not pr...
[ { "version": "v1", "created": "Wed, 27 Jun 2012 19:59:59 GMT" } ]
2012-07-03T00:00:00
[ [ "Goodfellow", "Ian", "", "Universite de Montreal" ], [ "Courville", "Aaron", "", "Universite\n de Montreal" ], [ "Bengio", "Yoshua", "", "Universite de Montreal" ] ]
TITLE: Large-Scale Feature Learning With Spike-and-Slab Sparse Coding ABSTRACT: We consider the problem of object recognition with a large number of classes. In order to overcome the low amount of labeled examples available in this setting, we introduce a new feature learning and extraction procedure based on a fac...
1206.6413
Armand Joulin
Armand Joulin (INRIA - Ecole Normale Superieure), Francis Bach (INRIA - Ecole Normale Superieure)
A Convex Relaxation for Weakly Supervised Classifiers
Appears in Proceedings of the 29th International Conference on Machine Learning (ICML 2012)
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper introduces a general multi-class approach to weakly supervised classification. Inferring the labels and learning the parameters of the model is usually done jointly through a block-coordinate descent algorithm such as expectation-maximization (EM), which may lead to local minima. To avoid this problem, we ...
[ { "version": "v1", "created": "Wed, 27 Jun 2012 19:59:59 GMT" } ]
2012-07-03T00:00:00
[ [ "Joulin", "Armand", "", "INRIA - Ecole Normale Superieure" ], [ "Bach", "Francis", "", "INRIA\n - Ecole Normale Superieure" ] ]
TITLE: A Convex Relaxation for Weakly Supervised Classifiers ABSTRACT: This paper introduces a general multi-class approach to weakly supervised classification. Inferring the labels and learning the parameters of the model is usually done jointly through a block-coordinate descent algorithm such as expectation-maxi...
1206.6415
Ariel Kleiner
Ariel Kleiner (UC Berkeley), Ameet Talwalkar (UC Berkeley), Purnamrita Sarkar (UC Berkeley), Michael Jordan (UC Berkeley)
The Big Data Bootstrap
Appears in Proceedings of the 29th International Conference on Machine Learning (ICML 2012). arXiv admin note: text overlap with arXiv:1112.5016
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The bootstrap provides a simple and powerful means of assessing the quality of estimators. However, in settings involving large datasets, the computation of bootstrap-based quantities can be prohibitively demanding. As an alternative, we present the Bag of Little Bootstraps (BLB), a new procedure which incorporates f...
[ { "version": "v1", "created": "Wed, 27 Jun 2012 19:59:59 GMT" } ]
2012-07-03T00:00:00
[ [ "Kleiner", "Ariel", "", "UC Berkeley" ], [ "Talwalkar", "Ameet", "", "UC Berkeley" ], [ "Sarkar", "Purnamrita", "", "UC Berkeley" ], [ "Jordan", "Michael", "", "UC Berkeley" ] ]
TITLE: The Big Data Bootstrap ABSTRACT: The bootstrap provides a simple and powerful means of assessing the quality of estimators. However, in settings involving large datasets, the computation of bootstrap-based quantities can be prohibitively demanding. As an alternative, we present the Bag of Little Bootstraps (...
1206.6417
Abhishek Kumar
Abhishek Kumar (University of Maryland), Hal Daume III (University of Maryland)
Learning Task Grouping and Overlap in Multi-task Learning
Appears in Proceedings of the 29th International Conference on Machine Learning (ICML 2012)
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In the paradigm of multi-task learning, mul- tiple related prediction tasks are learned jointly, sharing information across the tasks. We propose a framework for multi-task learn- ing that enables one to selectively share the information across the tasks. We assume that each task parameter vector is a linear combi- n...
[ { "version": "v1", "created": "Wed, 27 Jun 2012 19:59:59 GMT" } ]
2012-07-03T00:00:00
[ [ "Kumar", "Abhishek", "", "University of Maryland" ], [ "Daume", "Hal", "III", "University of\n Maryland" ] ]
TITLE: Learning Task Grouping and Overlap in Multi-task Learning ABSTRACT: In the paradigm of multi-task learning, mul- tiple related prediction tasks are learned jointly, sharing information across the tasks. We propose a framework for multi-task learn- ing that enables one to selectively share the information acr...
1206.6418
Honglak Lee
Kihyuk Sohn (University of Michigan), Honglak Lee (University of Michigan)
Learning Invariant Representations with Local Transformations
Appears in Proceedings of the 29th International Conference on Machine Learning (ICML 2012)
null
null
null
cs.LG cs.CV stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Learning invariant representations is an important problem in machine learning and pattern recognition. In this paper, we present a novel framework of transformation-invariant feature learning by incorporating linear transformations into the feature learning algorithms. For example, we present the transformation-inva...
[ { "version": "v1", "created": "Wed, 27 Jun 2012 19:59:59 GMT" } ]
2012-07-03T00:00:00
[ [ "Sohn", "Kihyuk", "", "University of Michigan" ], [ "Lee", "Honglak", "", "University of\n Michigan" ] ]
TITLE: Learning Invariant Representations with Local Transformations ABSTRACT: Learning invariant representations is an important problem in machine learning and pattern recognition. In this paper, we present a novel framework of transformation-invariant feature learning by incorporating linear transformations into...
1206.6419
Xuejun Liao
Shaobo Han (Duke University), Xuejun Liao (Duke University), Lawrence Carin (Duke University)
Cross-Domain Multitask Learning with Latent Probit Models
Appears in Proceedings of the 29th International Conference on Machine Learning (ICML 2012)
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Learning multiple tasks across heterogeneous domains is a challenging problem since the feature space may not be the same for different tasks. We assume the data in multiple tasks are generated from a latent common domain via sparse domain transforms and propose a latent probit model (LPM) to jointly learn the domain...
[ { "version": "v1", "created": "Wed, 27 Jun 2012 19:59:59 GMT" } ]
2012-07-03T00:00:00
[ [ "Han", "Shaobo", "", "Duke University" ], [ "Liao", "Xuejun", "", "Duke University" ], [ "Carin", "Lawrence", "", "Duke University" ] ]
TITLE: Cross-Domain Multitask Learning with Latent Probit Models ABSTRACT: Learning multiple tasks across heterogeneous domains is a challenging problem since the feature space may not be the same for different tasks. We assume the data in multiple tasks are generated from a latent common domain via sparse domain t...
1206.6447
Gael Varoquaux
Gael Varoquaux (INRIA), Alexandre Gramfort (INRIA), Bertrand Thirion (INRIA)
Small-sample Brain Mapping: Sparse Recovery on Spatially Correlated Designs with Randomization and Clustering
Appears in Proceedings of the 29th International Conference on Machine Learning (ICML 2012)
null
null
null
cs.LG cs.CV stat.AP stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Functional neuroimaging can measure the brain?s response to an external stimulus. It is used to perform brain mapping: identifying from these observations the brain regions involved. This problem can be cast into a linear supervised learning task where the neuroimaging data are used as predictors for the stimulus. Br...
[ { "version": "v1", "created": "Wed, 27 Jun 2012 19:59:59 GMT" } ]
2012-07-03T00:00:00
[ [ "Varoquaux", "Gael", "", "INRIA" ], [ "Gramfort", "Alexandre", "", "INRIA" ], [ "Thirion", "Bertrand", "", "INRIA" ] ]
TITLE: Small-sample Brain Mapping: Sparse Recovery on Spatially Correlated Designs with Randomization and Clustering ABSTRACT: Functional neuroimaging can measure the brain?s response to an external stimulus. It is used to perform brain mapping: identifying from these observations the brain regions involved. This...
1206.6458
Javad Azimi
Javad Azimi (Oregon State University), Alan Fern (Oregon State University), Xiaoli Zhang-Fern (Oregon State University), Glencora Borradaile (Oregon State University), Brent Heeringa (Williams College)
Batch Active Learning via Coordinated Matching
Appears in Proceedings of the 29th International Conference on Machine Learning (ICML 2012)
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Most prior work on active learning of classifiers has focused on sequentially selecting one unlabeled example at a time to be labeled in order to reduce the overall labeling effort. In many scenarios, however, it is desirable to label an entire batch of examples at once, for example, when labels can be acquired in pa...
[ { "version": "v1", "created": "Wed, 27 Jun 2012 19:59:59 GMT" } ]
2012-07-03T00:00:00
[ [ "Azimi", "Javad", "", "Oregon State University" ], [ "Fern", "Alan", "", "Oregon State\n University" ], [ "Zhang-Fern", "Xiaoli", "", "Oregon State University" ], [ "Borradaile", "Glencora", "", "Oregon State University" ], [ "He...
TITLE: Batch Active Learning via Coordinated Matching ABSTRACT: Most prior work on active learning of classifiers has focused on sequentially selecting one unlabeled example at a time to be labeled in order to reduce the overall labeling effort. In many scenarios, however, it is desirable to label an entire batch o...
1206.6466
Lawrence McAfee
Lawrence McAfee (Stanford University), Kunle Olukotun (Stanford University)
Utilizing Static Analysis and Code Generation to Accelerate Neural Networks
Appears in Proceedings of the 29th International Conference on Machine Learning (ICML 2012)
null
null
null
cs.NE cs.MS cs.PL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
As datasets continue to grow, neural network (NN) applications are becoming increasingly limited by both the amount of available computational power and the ease of developing high-performance applications. Researchers often must have expert systems knowledge to make their algorithms run efficiently. Although availab...
[ { "version": "v1", "created": "Wed, 27 Jun 2012 19:59:59 GMT" } ]
2012-07-03T00:00:00
[ [ "McAfee", "Lawrence", "", "Stanford University" ], [ "Olukotun", "Kunle", "", "Stanford\n University" ] ]
TITLE: Utilizing Static Analysis and Code Generation to Accelerate Neural Networks ABSTRACT: As datasets continue to grow, neural network (NN) applications are becoming increasingly limited by both the amount of available computational power and the ease of developing high-performance applications. Researchers of...
1206.6467
Luke McDowell
Luke McDowell (U.S. Naval Academy), David Aha (U.S. Naval Research Laboratory)
Semi-Supervised Collective Classification via Hybrid Label Regularization
Appears in Proceedings of the 29th International Conference on Machine Learning (ICML 2012)
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Many classification problems involve data instances that are interlinked with each other, such as webpages connected by hyperlinks. Techniques for "collective classification" (CC) often increase accuracy for such data graphs, but usually require a fully-labeled training graph. In contrast, we examine how to improve t...
[ { "version": "v1", "created": "Wed, 27 Jun 2012 19:59:59 GMT" } ]
2012-07-03T00:00:00
[ [ "McDowell", "Luke", "", "U.S. Naval Academy" ], [ "Aha", "David", "", "U.S. Naval Research\n Laboratory" ] ]
TITLE: Semi-Supervised Collective Classification via Hybrid Label Regularization ABSTRACT: Many classification problems involve data instances that are interlinked with each other, such as webpages connected by hyperlinks. Techniques for "collective classification" (CC) often increase accuracy for such data graph...
1206.6477
Yiteng Zhai
Yiteng Zhai (Nanyang Technological University), Mingkui Tan (Nanyang Technological University), Ivor Tsang (Nanyang Technological University), Yew Soon Ong (Nanyang Technological University)
Discovering Support and Affiliated Features from Very High Dimensions
Appears in Proceedings of the 29th International Conference on Machine Learning (ICML 2012)
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, a novel learning paradigm is presented to automatically identify groups of informative and correlated features from very high dimensions. Specifically, we explicitly incorporate correlation measures as constraints and then propose an efficient embedded feature selection method using recently developed ...
[ { "version": "v1", "created": "Wed, 27 Jun 2012 19:59:59 GMT" } ]
2012-07-03T00:00:00
[ [ "Zhai", "Yiteng", "", "Nanyang Technological University" ], [ "Tan", "Mingkui", "", "Nanyang\n Technological University" ], [ "Tsang", "Ivor", "", "Nanyang Technological University" ], [ "Ong", "Yew Soon", "", "Nanyang Technological Univ...
TITLE: Discovering Support and Affiliated Features from Very High Dimensions ABSTRACT: In this paper, a novel learning paradigm is presented to automatically identify groups of informative and correlated features from very high dimensions. Specifically, we explicitly incorporate correlation measures as constraints ...
1206.6479
Krishnakumar Balasubramanian
Krishnakumar Balasubramanian (Georgia Institute of Technology), Guy Lebanon (Georgia Institute of Technology)
The Landmark Selection Method for Multiple Output Prediction
Appears in Proceedings of the 29th International Conference on Machine Learning (ICML 2012)
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Conditional modeling x \to y is a central problem in machine learning. A substantial research effort is devoted to such modeling when x is high dimensional. We consider, instead, the case of a high dimensional y, where x is either low dimensional or high dimensional. Our approach is based on selecting a small subset ...
[ { "version": "v1", "created": "Wed, 27 Jun 2012 19:59:59 GMT" } ]
2012-07-03T00:00:00
[ [ "Balasubramanian", "Krishnakumar", "", "Georgia Institute of Technology" ], [ "Lebanon", "Guy", "", "Georgia Institute of Technology" ] ]
TITLE: The Landmark Selection Method for Multiple Output Prediction ABSTRACT: Conditional modeling x \to y is a central problem in machine learning. A substantial research effort is devoted to such modeling when x is high dimensional. We consider, instead, the case of a high dimensional y, where x is either low dim...
1206.6486
Piyush Rai
Alexandre Passos (UMass Amherst), Piyush Rai (University of Utah), Jacques Wainer (University of Campinas), Hal Daume III (University of Maryland)
Flexible Modeling of Latent Task Structures in Multitask Learning
Appears in Proceedings of the 29th International Conference on Machine Learning (ICML 2012)
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Multitask learning algorithms are typically designed assuming some fixed, a priori known latent structure shared by all the tasks. However, it is usually unclear what type of latent task structure is the most appropriate for a given multitask learning problem. Ideally, the "right" latent task structure should be lear...
[ { "version": "v1", "created": "Wed, 27 Jun 2012 19:59:59 GMT" } ]
2012-07-03T00:00:00
[ [ "Passos", "Alexandre", "", "UMass Amherst" ], [ "Rai", "Piyush", "", "University of Utah" ], [ "Wainer", "Jacques", "", "University of Campinas" ], [ "Daume", "Hal", "III", "University of\n Maryland" ] ]
TITLE: Flexible Modeling of Latent Task Structures in Multitask Learning ABSTRACT: Multitask learning algorithms are typically designed assuming some fixed, a priori known latent structure shared by all the tasks. However, it is usually unclear what type of latent task structure is the most appropriate for a given ...
1207.0078
Hugo Hernandez-Salda\~na
H. Hern\'andez-Salda\~na
Three predictions on July 2012 Federal Elections in Mexico based on past regularities
6 pages, one table
null
null
null
physics.soc-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Electoral systems are subject of study for physicist and mathematicians in last years given place to a new area: sociophysics. Based on previous works of the author on the Mexican electoral processes in the new millennium, he found three characteristics appearing along the 2000 and 2006 preliminary dataset offered by...
[ { "version": "v1", "created": "Sat, 30 Jun 2012 11:07:38 GMT" } ]
2012-07-03T00:00:00
[ [ "Hernández-Saldaña", "H.", "" ] ]
TITLE: Three predictions on July 2012 Federal Elections in Mexico based on past regularities ABSTRACT: Electoral systems are subject of study for physicist and mathematicians in last years given place to a new area: sociophysics. Based on previous works of the author on the Mexican electoral processes in the new ...
1207.0135
Manolis Terrovitis
Manolis Terrovitis, John Liagouris, Nikos Mamoulis, Spiros Skiadopoulos
Privacy Preservation by Disassociation
VLDB2012
Proceedings of the VLDB Endowment (PVLDB), Vol. 5, No. 10, pp. 944-955 (2012)
null
null
cs.DB
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this work, we focus on protection against identity disclosure in the publication of sparse multidimensional data. Existing multidimensional anonymization techniquesa) protect the privacy of users either by altering the set of quasi-identifiers of the original data (e.g., by generalization or suppression) or by add...
[ { "version": "v1", "created": "Sat, 30 Jun 2012 20:16:16 GMT" } ]
2012-07-03T00:00:00
[ [ "Terrovitis", "Manolis", "" ], [ "Liagouris", "John", "" ], [ "Mamoulis", "Nikos", "" ], [ "Skiadopoulos", "Spiros", "" ] ]
TITLE: Privacy Preservation by Disassociation ABSTRACT: In this work, we focus on protection against identity disclosure in the publication of sparse multidimensional data. Existing multidimensional anonymization techniquesa) protect the privacy of users either by altering the set of quasi-identifiers of the origin...
1207.0136
Bhargav Kanagal
Bhargav Kanagal, Amr Ahmed, Sandeep Pandey, Vanja Josifovski, Jeff Yuan, Lluis Garcia-Pueyo
Supercharging Recommender Systems using Taxonomies for Learning User Purchase Behavior
VLDB2012
Proceedings of the VLDB Endowment (PVLDB), Vol. 5, No. 10, pp. 956-967 (2012)
null
null
cs.DB
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recommender systems based on latent factor models have been effectively used for understanding user interests and predicting future actions. Such models work by projecting the users and items into a smaller dimensional space, thereby clustering similar users and items together and subsequently compute similarity betw...
[ { "version": "v1", "created": "Sat, 30 Jun 2012 20:17:05 GMT" } ]
2012-07-03T00:00:00
[ [ "Kanagal", "Bhargav", "" ], [ "Ahmed", "Amr", "" ], [ "Pandey", "Sandeep", "" ], [ "Josifovski", "Vanja", "" ], [ "Yuan", "Jeff", "" ], [ "Garcia-Pueyo", "Lluis", "" ] ]
TITLE: Supercharging Recommender Systems using Taxonomies for Learning User Purchase Behavior ABSTRACT: Recommender systems based on latent factor models have been effectively used for understanding user interests and predicting future actions. Such models work by projecting the users and items into a smaller dim...
1206.6815
Koby Crammer
Koby Crammer, Amir Globerson
Discriminative Learning via Semidefinite Probabilistic Models
Appears in Proceedings of the Twenty-Second Conference on Uncertainty in Artificial Intelligence (UAI2006)
null
null
UAI-P-2006-PG-98-105
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Discriminative linear models are a popular tool in machine learning. These can be generally divided into two types: The first is linear classifiers, such as support vector machines, which are well studied and provide state-of-the-art results. One shortcoming of these models is that their output (known as the 'margin'...
[ { "version": "v1", "created": "Wed, 27 Jun 2012 15:38:14 GMT" } ]
2012-07-02T00:00:00
[ [ "Crammer", "Koby", "" ], [ "Globerson", "Amir", "" ] ]
TITLE: Discriminative Learning via Semidefinite Probabilistic Models ABSTRACT: Discriminative linear models are a popular tool in machine learning. These can be generally divided into two types: The first is linear classifiers, such as support vector machines, which are well studied and provide state-of-the-art res...
1206.6850
Guobiao Mei
Guobiao Mei, Christian R. Shelton
Visualization of Collaborative Data
Appears in Proceedings of the Twenty-Second Conference on Uncertainty in Artificial Intelligence (UAI2006)
null
null
UAI-P-2006-PG-341-348
cs.GR cs.AI cs.HC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Collaborative data consist of ratings relating two distinct sets of objects: users and items. Much of the work with such data focuses on filtering: predicting unknown ratings for pairs of users and items. In this paper we focus on the problem of visualizing the information. Given all of the ratings, our task is to em...
[ { "version": "v1", "created": "Wed, 27 Jun 2012 16:24:29 GMT" } ]
2012-07-02T00:00:00
[ [ "Mei", "Guobiao", "" ], [ "Shelton", "Christian R.", "" ] ]
TITLE: Visualization of Collaborative Data ABSTRACT: Collaborative data consist of ratings relating two distinct sets of objects: users and items. Much of the work with such data focuses on filtering: predicting unknown ratings for pairs of users and items. In this paper we focus on the problem of visualizing the i...
1206.6852
Vikash Mansinghka
Vikash Mansinghka, Charles Kemp, Thomas Griffiths, Joshua Tenenbaum
Structured Priors for Structure Learning
Appears in Proceedings of the Twenty-Second Conference on Uncertainty in Artificial Intelligence (UAI2006)
null
null
UAI-P-2006-PG-324-331
cs.LG cs.AI stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Traditional approaches to Bayes net structure learning typically assume little regularity in graph structure other than sparseness. However, in many cases, we expect more systematicity: variables in real-world systems often group into classes that predict the kinds of probabilistic dependencies they participate in. H...
[ { "version": "v1", "created": "Wed, 27 Jun 2012 16:24:57 GMT" } ]
2012-07-02T00:00:00
[ [ "Mansinghka", "Vikash", "" ], [ "Kemp", "Charles", "" ], [ "Griffiths", "Thomas", "" ], [ "Tenenbaum", "Joshua", "" ] ]
TITLE: Structured Priors for Structure Learning ABSTRACT: Traditional approaches to Bayes net structure learning typically assume little regularity in graph structure other than sparseness. However, in many cases, we expect more systematicity: variables in real-world systems often group into classes that predict th...
1206.6860
John Langford
John Langford, Roberto Oliveira, Bianca Zadrozny
Predicting Conditional Quantiles via Reduction to Classification
Appears in Proceedings of the Twenty-Second Conference on Uncertainty in Artificial Intelligence (UAI2006)
null
null
UAI-P-2006-PG-257-264
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We show how to reduce the process of predicting general order statistics (and the median in particular) to solving classification. The accompanying theoretical statement shows that the regret of the classifier bounds the regret of the quantile regression under a quantile loss. We also test this reduction empirically ...
[ { "version": "v1", "created": "Wed, 27 Jun 2012 16:27:25 GMT" } ]
2012-07-02T00:00:00
[ [ "Langford", "John", "" ], [ "Oliveira", "Roberto", "" ], [ "Zadrozny", "Bianca", "" ] ]
TITLE: Predicting Conditional Quantiles via Reduction to Classification ABSTRACT: We show how to reduce the process of predicting general order statistics (and the median in particular) to solving classification. The accompanying theoretical statement shows that the regret of the classifier bounds the regret of the...
1206.6865
Frank Wood
Frank Wood, Thomas Griffiths, Zoubin Ghahramani
A Non-Parametric Bayesian Method for Inferring Hidden Causes
Appears in Proceedings of the Twenty-Second Conference on Uncertainty in Artificial Intelligence (UAI2006)
null
null
UAI-P-2006-PG-536-543
cs.LG cs.AI stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present a non-parametric Bayesian approach to structure learning with hidden causes. Previous Bayesian treatments of this problem define a prior over the number of hidden causes and use algorithms such as reversible jump Markov chain Monte Carlo to move between solutions. In contrast, we assume that the number of ...
[ { "version": "v1", "created": "Wed, 27 Jun 2012 16:28:41 GMT" } ]
2012-07-02T00:00:00
[ [ "Wood", "Frank", "" ], [ "Griffiths", "Thomas", "" ], [ "Ghahramani", "Zoubin", "" ] ]
TITLE: A Non-Parametric Bayesian Method for Inferring Hidden Causes ABSTRACT: We present a non-parametric Bayesian approach to structure learning with hidden causes. Previous Bayesian treatments of this problem define a prior over the number of hidden causes and use algorithms such as reversible jump Markov chain M...
1206.6883
Jun Wang
Jun Wang, Adam Woznica, Alexandros Kalousis
Learning Neighborhoods for Metric Learning
null
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Metric learning methods have been shown to perform well on different learning tasks. Many of them rely on target neighborhood relationships that are computed in the original feature space and remain fixed throughout learning. As a result, the learned metric reflects the original neighborhood relations. We propose a n...
[ { "version": "v1", "created": "Thu, 28 Jun 2012 18:57:01 GMT" } ]
2012-07-02T00:00:00
[ [ "Wang", "Jun", "" ], [ "Woznica", "Adam", "" ], [ "Kalousis", "Alexandros", "" ] ]
TITLE: Learning Neighborhoods for Metric Learning ABSTRACT: Metric learning methods have been shown to perform well on different learning tasks. Many of them rely on target neighborhood relationships that are computed in the original feature space and remain fixed throughout learning. As a result, the learned metri...
1204.3251
Vladimir Vovk
Valentina Fedorova, Alex Gammerman, Ilia Nouretdinov, and Vladimir Vovk
Plug-in martingales for testing exchangeability on-line
8 pages, 7 figures; ICML 2012 Conference Proceedings
null
null
On-line Compression Modelling Project (New Series), Working Paper 04
cs.LG stat.ME
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A standard assumption in machine learning is the exchangeability of data, which is equivalent to assuming that the examples are generated from the same probability distribution independently. This paper is devoted to testing the assumption of exchangeability on-line: the examples arrive one by one, and after receivin...
[ { "version": "v1", "created": "Sun, 15 Apr 2012 10:21:57 GMT" }, { "version": "v2", "created": "Thu, 28 Jun 2012 09:36:27 GMT" } ]
2012-06-29T00:00:00
[ [ "Fedorova", "Valentina", "" ], [ "Gammerman", "Alex", "" ], [ "Nouretdinov", "Ilia", "" ], [ "Vovk", "Vladimir", "" ] ]
TITLE: Plug-in martingales for testing exchangeability on-line ABSTRACT: A standard assumption in machine learning is the exchangeability of data, which is equivalent to assuming that the examples are generated from the same probability distribution independently. This paper is devoted to testing the assumption of ...
1205.6359
Akshay Deepak
Akshay Deepak, David Fern\'andez-Baca, and Michelle M. McMahon
Extracting Conflict-free Information from Multi-labeled Trees
Submitted in Workshop on Algorithms in Bioinformatics 2012 (http://algo12.fri.uni-lj.si/?file=wabi)
null
null
null
cs.DS q-bio.PE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A multi-labeled tree, or MUL-tree, is a phylogenetic tree where two or more leaves share a label, e.g., a species name. A MUL-tree can imply multiple conflicting phylogenetic relationships for the same set of taxa, but can also contain conflict-free information that is of interest and yet is not obvious. We define th...
[ { "version": "v1", "created": "Tue, 29 May 2012 13:35:56 GMT" }, { "version": "v2", "created": "Thu, 28 Jun 2012 14:50:07 GMT" } ]
2012-06-29T00:00:00
[ [ "Deepak", "Akshay", "" ], [ "Fernández-Baca", "David", "" ], [ "McMahon", "Michelle M.", "" ] ]
TITLE: Extracting Conflict-free Information from Multi-labeled Trees ABSTRACT: A multi-labeled tree, or MUL-tree, is a phylogenetic tree where two or more leaves share a label, e.g., a species name. A MUL-tree can imply multiple conflicting phylogenetic relationships for the same set of taxa, but can also contain c...
1206.6588
Bosiljka Tadic
Milovan Suvakov, Marija Mitrovic, Vladimir Gligorijevic, Bosiljka Tadic
How the online social networks are used: Dialogs-based structure of MySpace
18 pages, 12 figures (resized to 50KB)
null
null
null
physics.soc-ph cs.SI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Quantitative study of collective dynamics in online social networks is a new challenge based on the abundance of empirical data. Conclusions, however, may depend on factors as user's psychology profiles and their reasons to use the online contacts. In this paper we have compiled and analyzed two datasets from \texttt...
[ { "version": "v1", "created": "Thu, 28 Jun 2012 08:20:03 GMT" } ]
2012-06-29T00:00:00
[ [ "Suvakov", "Milovan", "" ], [ "Mitrovic", "Marija", "" ], [ "Gligorijevic", "Vladimir", "" ], [ "Tadic", "Bosiljka", "" ] ]
TITLE: How the online social networks are used: Dialogs-based structure of MySpace ABSTRACT: Quantitative study of collective dynamics in online social networks is a new challenge based on the abundance of empirical data. Conclusions, however, may depend on factors as user's psychology profiles and their reasons ...
1206.6646
Arnab Bhattacharya
Arnab Bhattacharya and B. Palvali Teja
Aggregate Skyline Join Queries: Skylines with Aggregate Operations over Multiple Relations
Best student paper award; COMAD 2010 (International Conference on Management of Data)
null
null
null
cs.DB
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The multi-criteria decision making, which is possible with the advent of skyline queries, has been applied in many areas. Though most of the existing research is concerned with only a single relation, several real world applications require finding the skyline set of records over multiple relations. Consequently, the...
[ { "version": "v1", "created": "Thu, 28 Jun 2012 12:06:51 GMT" } ]
2012-06-29T00:00:00
[ [ "Bhattacharya", "Arnab", "" ], [ "Teja", "B. Palvali", "" ] ]
TITLE: Aggregate Skyline Join Queries: Skylines with Aggregate Operations over Multiple Relations ABSTRACT: The multi-criteria decision making, which is possible with the advent of skyline queries, has been applied in many areas. Though most of the existing research is concerned with only a single relation, sever...
1206.6196
Pierre-Francois Marteau
Pierre-Fran\c{c}ois Marteau (IRISA), Nicolas Bonnel (IRISA), Gilbas M\'enier (IRISA)
Discrete Elastic Inner Vector Spaces with Application in Time Series and Sequence Mining
arXiv admin note: substantial text overlap with arXiv:1101.4318
IEEE Transactions on Knowledge and Data Engineering (2012) pp 1-14
10.1109/TKDE.2012.131
null
cs.LG cs.DB
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper proposes a framework dedicated to the construction of what we call discrete elastic inner product allowing one to embed sets of non-uniformly sampled multivariate time series or sequences of varying lengths into inner product space structures. This framework is based on a recursive definition that covers t...
[ { "version": "v1", "created": "Wed, 27 Jun 2012 07:44:15 GMT" } ]
2012-06-28T00:00:00
[ [ "Marteau", "Pierre-François", "", "IRISA" ], [ "Bonnel", "Nicolas", "", "IRISA" ], [ "Ménier", "Gilbas", "", "IRISA" ] ]
TITLE: Discrete Elastic Inner Vector Spaces with Application in Time Series and Sequence Mining ABSTRACT: This paper proposes a framework dedicated to the construction of what we call discrete elastic inner product allowing one to embed sets of non-uniformly sampled multivariate time series or sequences of varyin...
1206.6293
Alexander Sch\"atzle
Martin Przyjaciel-Zablocki, Alexander Sch\"atzle, Thomas Hornung, Christopher Dorner, Georg Lausen
Cascading map-side joins over HBase for scalable join processing
null
null
null
null
cs.DB cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
One of the major challenges in large-scale data processing with MapReduce is the smart computation of joins. Since Semantic Web datasets published in RDF have increased rapidly over the last few years, scalable join techniques become an important issue for SPARQL query processing as well. In this paper, we introduce ...
[ { "version": "v1", "created": "Wed, 27 Jun 2012 15:05:05 GMT" } ]
2012-06-28T00:00:00
[ [ "Przyjaciel-Zablocki", "Martin", "" ], [ "Schätzle", "Alexander", "" ], [ "Hornung", "Thomas", "" ], [ "Dorner", "Christopher", "" ], [ "Lausen", "Georg", "" ] ]
TITLE: Cascading map-side joins over HBase for scalable join processing ABSTRACT: One of the major challenges in large-scale data processing with MapReduce is the smart computation of joins. Since Semantic Web datasets published in RDF have increased rapidly over the last few years, scalable join techniques become ...
1206.5915
Sundararajan Sellamanickam
Sundararajan Sellamanickam, Sathiya Keerthi Selvaraj
Graph Based Classification Methods Using Inaccurate External Classifier Information
12 pages
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper we consider the problem of collectively classifying entities where relational information is available across the entities. In practice inaccurate class distribution for each entity is often available from another (external) classifier. For example this distribution could come from a classifier built us...
[ { "version": "v1", "created": "Tue, 26 Jun 2012 08:29:43 GMT" } ]
2012-06-27T00:00:00
[ [ "Sellamanickam", "Sundararajan", "" ], [ "Selvaraj", "Sathiya Keerthi", "" ] ]
TITLE: Graph Based Classification Methods Using Inaccurate External Classifier Information ABSTRACT: In this paper we consider the problem of collectively classifying entities where relational information is available across the entities. In practice inaccurate class distribution for each entity is often availabl...
1206.6015
Sundararajan Sellamanickam
Sundararajan Sellamanickam, Sathiya Keerthi Selvaraj
Transductive Classification Methods for Mixed Graphs
8 Pages, 2 Tables, 2 Figures, KDD Workshop - MLG'11 San Diego, CA, USA
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper we provide a principled approach to solve a transductive classification problem involving a similar graph (edges tend to connect nodes with same labels) and a dissimilar graph (edges tend to connect nodes with opposing labels). Most of the existing methods, e.g., Information Regularization (IR), Weighte...
[ { "version": "v1", "created": "Tue, 26 Jun 2012 14:56:33 GMT" } ]
2012-06-27T00:00:00
[ [ "Sellamanickam", "Sundararajan", "" ], [ "Selvaraj", "Sathiya Keerthi", "" ] ]
TITLE: Transductive Classification Methods for Mixed Graphs ABSTRACT: In this paper we provide a principled approach to solve a transductive classification problem involving a similar graph (edges tend to connect nodes with same labels) and a dissimilar graph (edges tend to connect nodes with opposing labels). Most...
1206.6030
Sundararajan Sellamanickam
Sundararajan Sellamanickam, Shirish Shevade
An Additive Model View to Sparse Gaussian Process Classifier Design
14 pages, 3 figures
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We consider the problem of designing a sparse Gaussian process classifier (SGPC) that generalizes well. Viewing SGPC design as constructing an additive model like in boosting, we present an efficient and effective SGPC design method to perform a stage-wise optimization of a predictive loss function. We introduce new ...
[ { "version": "v1", "created": "Tue, 26 Jun 2012 15:58:21 GMT" } ]
2012-06-27T00:00:00
[ [ "Sellamanickam", "Sundararajan", "" ], [ "Shevade", "Shirish", "" ] ]
TITLE: An Additive Model View to Sparse Gaussian Process Classifier Design ABSTRACT: We consider the problem of designing a sparse Gaussian process classifier (SGPC) that generalizes well. Viewing SGPC design as constructing an additive model like in boosting, we present an efficient and effective SGPC design metho...
1206.6038
Sundararajan Sellamanickam
Sundararajan Sellamanickam, Sathiya Keerthi Selvaraj
Predictive Approaches For Gaussian Process Classifier Model Selection
21 pages
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper we consider the problem of Gaussian process classifier (GPC) model selection with different Leave-One-Out (LOO) Cross Validation (CV) based optimization criteria and provide a practical algorithm using LOO predictive distributions with such criteria to select hyperparameters. Apart from the standard ave...
[ { "version": "v1", "created": "Tue, 26 Jun 2012 16:19:51 GMT" } ]
2012-06-27T00:00:00
[ [ "Sellamanickam", "Sundararajan", "" ], [ "Selvaraj", "Sathiya Keerthi", "" ] ]
TITLE: Predictive Approaches For Gaussian Process Classifier Model Selection ABSTRACT: In this paper we consider the problem of Gaussian process classifier (GPC) model selection with different Leave-One-Out (LOO) Cross Validation (CV) based optimization criteria and provide a practical algorithm using LOO predictiv...
1206.5270
Wei Li
Wei Li, David Blei, Andrew McCallum
Nonparametric Bayes Pachinko Allocation
Appears in Proceedings of the Twenty-Third Conference on Uncertainty in Artificial Intelligence (UAI2007)
null
null
UAI-P-2007-PG-243-250
cs.IR cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recent advances in topic models have explored complicated structured distributions to represent topic correlation. For example, the pachinko allocation model (PAM) captures arbitrary, nested, and possibly sparse correlations between topics using a directed acyclic graph (DAG). While PAM provides more flexibility and ...
[ { "version": "v1", "created": "Wed, 20 Jun 2012 15:04:47 GMT" } ]
2012-06-26T00:00:00
[ [ "Li", "Wei", "" ], [ "Blei", "David", "" ], [ "McCallum", "Andrew", "" ] ]
TITLE: Nonparametric Bayes Pachinko Allocation ABSTRACT: Recent advances in topic models have explored complicated structured distributions to represent topic correlation. For example, the pachinko allocation model (PAM) captures arbitrary, nested, and possibly sparse correlations between topics using a directed ac...
1206.5278
Michael P. Holmes
Michael P. Holmes, Alexander G. Gray, Charles Lee Isbell
Fast Nonparametric Conditional Density Estimation
Appears in Proceedings of the Twenty-Third Conference on Uncertainty in Artificial Intelligence (UAI2007)
null
null
UAI-P-2007-PG-175-182
stat.ME cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Conditional density estimation generalizes regression by modeling a full density f(yjx) rather than only the expected value E(yjx). This is important for many tasks, including handling multi-modality and generating prediction intervals. Though fundamental and widely applicable, nonparametric conditional density estim...
[ { "version": "v1", "created": "Wed, 20 Jun 2012 15:08:36 GMT" } ]
2012-06-26T00:00:00
[ [ "Holmes", "Michael P.", "" ], [ "Gray", "Alexander G.", "" ], [ "Isbell", "Charles Lee", "" ] ]
TITLE: Fast Nonparametric Conditional Density Estimation ABSTRACT: Conditional density estimation generalizes regression by modeling a full density f(yjx) rather than only the expected value E(yjx). This is important for many tasks, including handling multi-modality and generating prediction intervals. Though funda...
1112.3265
Neil Zhenqiang Gong
Neil Zhenqiang Gong, Ameet Talwalkar, Lester Mackey, Ling Huang, Eui Chul Richard Shin, Emil Stefanov, Elaine (Runting) Shi and Dawn Song
Jointly Predicting Links and Inferring Attributes using a Social-Attribute Network (SAN)
9 pages, 4 figures and 4 tables
null
null
null
cs.SI physics.soc-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The effects of social influence and homophily suggest that both network structure and node attribute information should inform the tasks of link prediction and node attribute inference. Recently, Yin et al. proposed Social-Attribute Network (SAN), an attribute-augmented social network, to integrate network structure ...
[ { "version": "v1", "created": "Wed, 14 Dec 2011 16:13:02 GMT" }, { "version": "v2", "created": "Fri, 16 Dec 2011 04:22:15 GMT" }, { "version": "v3", "created": "Mon, 19 Dec 2011 14:01:37 GMT" }, { "version": "v4", "created": "Mon, 13 Feb 2012 23:44:46 GMT" }, { "v...
2012-06-25T00:00:00
[ [ "Gong", "Neil Zhenqiang", "", "Runting" ], [ "Talwalkar", "Ameet", "", "Runting" ], [ "Mackey", "Lester", "", "Runting" ], [ "Huang", "Ling", "", "Runting" ], [ "Shin", "Eui Chul Richard", "", "Runting" ], [ "S...
TITLE: Jointly Predicting Links and Inferring Attributes using a Social-Attribute Network (SAN) ABSTRACT: The effects of social influence and homophily suggest that both network structure and node attribute information should inform the tasks of link prediction and node attribute inference. Recently, Yin et al. p...
1206.5102
Stevenn Volant
Stevenn Volant, Caroline B\'erard, Marie-Laure Martin-Magniette and St\'ephane Robin
Hidden Markov Models with mixtures as emission distributions
null
null
null
null
stat.ML cs.LG stat.CO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In unsupervised classification, Hidden Markov Models (HMM) are used to account for a neighborhood structure between observations. The emission distributions are often supposed to belong to some parametric family. In this paper, a semiparametric modeling where the emission distributions are a mixture of parametric dis...
[ { "version": "v1", "created": "Fri, 22 Jun 2012 10:24:55 GMT" } ]
2012-06-25T00:00:00
[ [ "Volant", "Stevenn", "" ], [ "Bérard", "Caroline", "" ], [ "Martin-Magniette", "Marie-Laure", "" ], [ "Robin", "Stéphane", "" ] ]
TITLE: Hidden Markov Models with mixtures as emission distributions ABSTRACT: In unsupervised classification, Hidden Markov Models (HMM) are used to account for a neighborhood structure between observations. The emission distributions are often supposed to belong to some parametric family. In this paper, a semipara...