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1306.4534
Antonio Lima
Antonio Lima, Manlio De Domenico, Veljko Pejovic, Mirco Musolesi
Exploiting Cellular Data for Disease Containment and Information Campaigns Strategies in Country-Wide Epidemics
9 pages, 9 figures. Appeared in Proceedings of NetMob 2013. Boston, MA, USA. May 2013
null
null
School of Computer Science University of Birmingham Technical Report CSR-13-01
cs.SI physics.soc-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Human mobility is one of the key factors at the basis of the spreading of diseases in a population. Containment strategies are usually devised on movement scenarios based on coarse-grained assumptions. Mobility phone data provide a unique opportunity for building models and defining strategies based on very precise i...
[ { "version": "v1", "created": "Wed, 19 Jun 2013 13:22:11 GMT" } ]
2013-06-20T00:00:00
[ [ "Lima", "Antonio", "" ], [ "De Domenico", "Manlio", "" ], [ "Pejovic", "Veljko", "" ], [ "Musolesi", "Mirco", "" ] ]
TITLE: Exploiting Cellular Data for Disease Containment and Information Campaigns Strategies in Country-Wide Epidemics ABSTRACT: Human mobility is one of the key factors at the basis of the spreading of diseases in a population. Containment strategies are usually devised on movement scenarios based on coarse-grai...
1305.3633
Mohammad Pourhomayoun
Mohammad Pourhomayoun, Peter Dugan, Marian Popescu, Denise Risch, Hal Lewis, Christopher Clark
Classification for Big Dataset of Bioacoustic Signals Based on Human Scoring System and Artificial Neural Network
To be Submitted to "ICML 2013 Workshop on Machine Learning for Bioacoustics", 6 pages, 4 figures
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we propose a method to improve sound classification performance by combining signal features, derived from the time-frequency spectrogram, with human perception. The method presented herein exploits an artificial neural network (ANN) and learns the signal features based on the human perception knowledg...
[ { "version": "v1", "created": "Wed, 15 May 2013 20:53:39 GMT" }, { "version": "v2", "created": "Mon, 17 Jun 2013 20:29:14 GMT" } ]
2013-06-19T00:00:00
[ [ "Pourhomayoun", "Mohammad", "" ], [ "Dugan", "Peter", "" ], [ "Popescu", "Marian", "" ], [ "Risch", "Denise", "" ], [ "Lewis", "Hal", "" ], [ "Clark", "Christopher", "" ] ]
TITLE: Classification for Big Dataset of Bioacoustic Signals Based on Human Scoring System and Artificial Neural Network ABSTRACT: In this paper, we propose a method to improve sound classification performance by combining signal features, derived from the time-frequency spectrogram, with human perception. The me...
1305.3635
Mohammad Pourhomayoun
Mohammad Pourhomayoun, Peter Dugan, Marian Popescu, Christopher Clark
Bioacoustic Signal Classification Based on Continuous Region Processing, Grid Masking and Artificial Neural Network
To be Submitted to "ICML 2013 Workshop on Machine Learning for Bioacoustics", 6 pages, 8 figures
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we develop a novel method based on machine-learning and image processing to identify North Atlantic right whale (NARW) up-calls in the presence of high levels of ambient and interfering noise. We apply a continuous region algorithm on the spectrogram to extract the regions of interest, and then use gri...
[ { "version": "v1", "created": "Wed, 15 May 2013 20:59:03 GMT" }, { "version": "v2", "created": "Mon, 17 Jun 2013 20:28:33 GMT" } ]
2013-06-19T00:00:00
[ [ "Pourhomayoun", "Mohammad", "" ], [ "Dugan", "Peter", "" ], [ "Popescu", "Marian", "" ], [ "Clark", "Christopher", "" ] ]
TITLE: Bioacoustic Signal Classification Based on Continuous Region Processing, Grid Masking and Artificial Neural Network ABSTRACT: In this paper, we develop a novel method based on machine-learning and image processing to identify North Atlantic right whale (NARW) up-calls in the presence of high levels of ambi...
1306.4207
Ragesh Jaiswal
Ragesh Jaiswal and Prachi Jain and Saumya Yadav
A bad 2-dimensional instance for k-means++
null
null
null
null
cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The k-means++ seeding algorithm is one of the most popular algorithms that is used for finding the initial $k$ centers when using the k-means heuristic. The algorithm is a simple sampling procedure and can be described as follows: {quote} Pick the first center randomly from among the given points. For $i > 1$, pick a...
[ { "version": "v1", "created": "Tue, 18 Jun 2013 14:22:12 GMT" } ]
2013-06-19T00:00:00
[ [ "Jaiswal", "Ragesh", "" ], [ "Jain", "Prachi", "" ], [ "Yadav", "Saumya", "" ] ]
TITLE: A bad 2-dimensional instance for k-means++ ABSTRACT: The k-means++ seeding algorithm is one of the most popular algorithms that is used for finding the initial $k$ centers when using the k-means heuristic. The algorithm is a simple sampling procedure and can be described as follows: {quote} Pick the first ce...
1211.6014
Vincent A Traag
Bal\'azs Cs. Cs\'aji, Arnaud Browet, V.A. Traag, Jean-Charles Delvenne, Etienne Huens, Paul Van Dooren, Zbigniew Smoreda and Vincent D. Blondel
Exploring the Mobility of Mobile Phone Users
16 pages, 12 figures
Physica A 392(6), pp. 1459-1473 (2013)
10.1016/j.physa.2012.11.040
null
physics.soc-ph cs.SI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Mobile phone datasets allow for the analysis of human behavior on an unprecedented scale. The social network, temporal dynamics and mobile behavior of mobile phone users have often been analyzed independently from each other using mobile phone datasets. In this article, we explore the connections between various feat...
[ { "version": "v1", "created": "Mon, 26 Nov 2012 16:30:59 GMT" } ]
2013-06-17T00:00:00
[ [ "Csáji", "Balázs Cs.", "" ], [ "Browet", "Arnaud", "" ], [ "Traag", "V. A.", "" ], [ "Delvenne", "Jean-Charles", "" ], [ "Huens", "Etienne", "" ], [ "Van Dooren", "Paul", "" ], [ "Smoreda", "Zbigniew", "" ...
TITLE: Exploring the Mobility of Mobile Phone Users ABSTRACT: Mobile phone datasets allow for the analysis of human behavior on an unprecedented scale. The social network, temporal dynamics and mobile behavior of mobile phone users have often been analyzed independently from each other using mobile phone datasets. ...
1306.3294
Quan Wang
Quan Wang, Kim L. Boyer
Feature Learning by Multidimensional Scaling and its Applications in Object Recognition
To appear in SIBGRAPI 2013
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present the MDS feature learning framework, in which multidimensional scaling (MDS) is applied on high-level pairwise image distances to learn fixed-length vector representations of images. The aspects of the images that are captured by the learned features, which we call MDS features, completely depend on what ki...
[ { "version": "v1", "created": "Fri, 14 Jun 2013 04:43:40 GMT" } ]
2013-06-17T00:00:00
[ [ "Wang", "Quan", "" ], [ "Boyer", "Kim L.", "" ] ]
TITLE: Feature Learning by Multidimensional Scaling and its Applications in Object Recognition ABSTRACT: We present the MDS feature learning framework, in which multidimensional scaling (MDS) is applied on high-level pairwise image distances to learn fixed-length vector representations of images. The aspects of t...
1306.3474
Yijun Wang
Yijun Wang
Classifying Single-Trial EEG during Motor Imagery with a Small Training Set
13 pages, 3 figures
null
null
null
cs.LG cs.HC stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Before the operation of a motor imagery based brain-computer interface (BCI) adopting machine learning techniques, a cumbersome training procedure is unavoidable. The development of a practical BCI posed the challenge of classifying single-trial EEG with a small training set. In this letter, we addressed this problem...
[ { "version": "v1", "created": "Fri, 14 Jun 2013 18:24:19 GMT" } ]
2013-06-17T00:00:00
[ [ "Wang", "Yijun", "" ] ]
TITLE: Classifying Single-Trial EEG during Motor Imagery with a Small Training Set ABSTRACT: Before the operation of a motor imagery based brain-computer interface (BCI) adopting machine learning techniques, a cumbersome training procedure is unavoidable. The development of a practical BCI posed the challenge of ...
1306.3003
Xuhui Fan
Xuhui Fan, Yiling Zeng, Longbing Cao
Non-parametric Power-law Data Clustering
null
null
null
null
cs.LG cs.CV stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
It has always been a great challenge for clustering algorithms to automatically determine the cluster numbers according to the distribution of datasets. Several approaches have been proposed to address this issue, including the recent promising work which incorporate Bayesian Nonparametrics into the $k$-means cluster...
[ { "version": "v1", "created": "Thu, 13 Jun 2013 01:20:50 GMT" } ]
2013-06-14T00:00:00
[ [ "Fan", "Xuhui", "" ], [ "Zeng", "Yiling", "" ], [ "Cao", "Longbing", "" ] ]
TITLE: Non-parametric Power-law Data Clustering ABSTRACT: It has always been a great challenge for clustering algorithms to automatically determine the cluster numbers according to the distribution of datasets. Several approaches have been proposed to address this issue, including the recent promising work which in...
1306.3058
Sebastien Paris
S\'ebastien Paris and Yann Doh and Herv\'e Glotin and Xanadu Halkias and Joseph Razik
Physeter catodon localization by sparse coding
6 pages, 6 figures, workshop ICML4B in ICML 2013 conference
null
null
null
cs.LG cs.CE stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper presents a spermwhale' localization architecture using jointly a bag-of-features (BoF) approach and machine learning framework. BoF methods are known, especially in computer vision, to produce from a collection of local features a global representation invariant to principal signal transformations. Our ide...
[ { "version": "v1", "created": "Thu, 13 Jun 2013 09:05:08 GMT" } ]
2013-06-14T00:00:00
[ [ "Paris", "Sébastien", "" ], [ "Doh", "Yann", "" ], [ "Glotin", "Hervé", "" ], [ "Halkias", "Xanadu", "" ], [ "Razik", "Joseph", "" ] ]
TITLE: Physeter catodon localization by sparse coding ABSTRACT: This paper presents a spermwhale' localization architecture using jointly a bag-of-features (BoF) approach and machine learning framework. BoF methods are known, especially in computer vision, to produce from a collection of local features a global rep...
1306.3084
Doriane Ibarra
Jorge Hernandez (CMM), Beatriz Marcotegui (CMM)
Segmentation et Interpr\'etation de Nuages de Points pour la Mod\'elisation d'Environnements Urbains
null
Revue fran\c{c}aise de photogrammetrie et de t\'el\'edection 191 (2008) 28-35
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Dans cet article, nous pr\'esentons une m\'ethode pour la d\'etection et la classification d'artefacts au niveau du sol, comme phase de filtrage pr\'ealable \`a la mod\'elisation d'environnements urbains. La m\'ethode de d\'etection est r\'ealis\'ee sur l'image profondeur, une projection de nuage de points sur un pla...
[ { "version": "v1", "created": "Thu, 13 Jun 2013 11:27:58 GMT" } ]
2013-06-14T00:00:00
[ [ "Hernandez", "Jorge", "", "CMM" ], [ "Marcotegui", "Beatriz", "", "CMM" ] ]
TITLE: Segmentation et Interpr\'etation de Nuages de Points pour la Mod\'elisation d'Environnements Urbains ABSTRACT: Dans cet article, nous pr\'esentons une m\'ethode pour la d\'etection et la classification d'artefacts au niveau du sol, comme phase de filtrage pr\'ealable \`a la mod\'elisation d'environnements ...
1306.2795
Ronan Collobert
Pedro H. O. Pinheiro, Ronan Collobert
Recurrent Convolutional Neural Networks for Scene Parsing
null
null
null
Idiap-RR-22-2013
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Scene parsing is a technique that consist on giving a label to all pixels in an image according to the class they belong to. To ensure a good visual coherence and a high class accuracy, it is essential for a scene parser to capture image long range dependencies. In a feed-forward architecture, this can be simply achi...
[ { "version": "v1", "created": "Wed, 12 Jun 2013 11:56:57 GMT" } ]
2013-06-13T00:00:00
[ [ "Pinheiro", "Pedro H. O.", "" ], [ "Collobert", "Ronan", "" ] ]
TITLE: Recurrent Convolutional Neural Networks for Scene Parsing ABSTRACT: Scene parsing is a technique that consist on giving a label to all pixels in an image according to the class they belong to. To ensure a good visual coherence and a high class accuracy, it is essential for a scene parser to capture image lon...
1306.2864
Catarina Moreira
Catarina Moreira and Andreas Wichert
Finding Academic Experts on a MultiSensor Approach using Shannon's Entropy
null
Journal of Expert Systems with Applications, 2013, volume 40, issue 14
10.1016/j.eswa.2013.04.001
null
cs.AI cs.IR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Expert finding is an information retrieval task concerned with the search for the most knowledgeable people, in some topic, with basis on documents describing peoples activities. The task involves taking a user query as input and returning a list of people sorted by their level of expertise regarding the user query. ...
[ { "version": "v1", "created": "Wed, 12 Jun 2013 15:35:57 GMT" } ]
2013-06-13T00:00:00
[ [ "Moreira", "Catarina", "" ], [ "Wichert", "Andreas", "" ] ]
TITLE: Finding Academic Experts on a MultiSensor Approach using Shannon's Entropy ABSTRACT: Expert finding is an information retrieval task concerned with the search for the most knowledgeable people, in some topic, with basis on documents describing peoples activities. The task involves taking a user query as in...
1306.2459
Sutanay Choudhury
Sutanay Choudhury, Lawrence Holder, George Chin, John Feo
Fast Search for Dynamic Multi-Relational Graphs
SIGMOD Workshop on Dynamic Networks Management and Mining (DyNetMM), 2013
null
null
null
cs.DB
http://creativecommons.org/licenses/publicdomain/
Acting on time-critical events by processing ever growing social media or news streams is a major technical challenge. Many of these data sources can be modeled as multi-relational graphs. Continuous queries or techniques to search for rare events that typically arise in monitoring applications have been studied exte...
[ { "version": "v1", "created": "Tue, 11 Jun 2013 09:21:42 GMT" } ]
2013-06-12T00:00:00
[ [ "Choudhury", "Sutanay", "" ], [ "Holder", "Lawrence", "" ], [ "Chin", "George", "" ], [ "Feo", "John", "" ] ]
TITLE: Fast Search for Dynamic Multi-Relational Graphs ABSTRACT: Acting on time-critical events by processing ever growing social media or news streams is a major technical challenge. Many of these data sources can be modeled as multi-relational graphs. Continuous queries or techniques to search for rare events tha...
1306.2539
Albane Saintenoy
Albane Saintenoy (IDES), J.-M. Friedt (UMR 6174), Adam D. Booth, F. Tolle (Th\'eMA), E. Bernard (Th\'eMA), Dominique Laffly (GEODE), C. Marlin (IDES), M. Griselin (Th\'eMA)
Deriving ice thickness, glacier volume and bedrock morphology of the Austre Lov\'enbreen (Svalbard) using Ground-penetrating Radar
null
Near Surface Geophysics 11 (2013) 253-261
null
null
physics.geo-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The Austre Lov\'enbreen is a 4.6 km2 glacier on the Archipelago of Svalbard (79 degrees N) that has been surveyed over the last 47 years in order of monitoring in particular the glacier evolution and associated hydrological phenomena in the context of nowadays global warming. A three-week field survey over April 2010...
[ { "version": "v1", "created": "Tue, 11 Jun 2013 14:45:13 GMT" } ]
2013-06-12T00:00:00
[ [ "Saintenoy", "Albane", "", "IDES" ], [ "Friedt", "J. -M.", "", "UMR 6174" ], [ "Booth", "Adam D.", "", "ThéMA" ], [ "Tolle", "F.", "", "ThéMA" ], [ "Bernard", "E.", "", "ThéMA" ], [ "Laffly", "Dominique", ...
TITLE: Deriving ice thickness, glacier volume and bedrock morphology of the Austre Lov\'enbreen (Svalbard) using Ground-penetrating Radar ABSTRACT: The Austre Lov\'enbreen is a 4.6 km2 glacier on the Archipelago of Svalbard (79 degrees N) that has been surveyed over the last 47 years in order of monitoring in par...
1306.2597
Tao Qin Dr.
Tao Qin and Tie-Yan Liu
Introducing LETOR 4.0 Datasets
null
null
null
null
cs.IR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
LETOR is a package of benchmark data sets for research on LEarning TO Rank, which contains standard features, relevance judgments, data partitioning, evaluation tools, and several baselines. Version 1.0 was released in April 2007. Version 2.0 was released in Dec. 2007. Version 3.0 was released in Dec. 2008. This vers...
[ { "version": "v1", "created": "Sun, 9 Jun 2013 09:58:00 GMT" } ]
2013-06-12T00:00:00
[ [ "Qin", "Tao", "" ], [ "Liu", "Tie-Yan", "" ] ]
TITLE: Introducing LETOR 4.0 Datasets ABSTRACT: LETOR is a package of benchmark data sets for research on LEarning TO Rank, which contains standard features, relevance judgments, data partitioning, evaluation tools, and several baselines. Version 1.0 was released in April 2007. Version 2.0 was released in Dec. 2007...
1306.1850
Ayad Ghany Ismaeel
Ayad Ghany Ismaeel, Anar Auda Ablahad
Enhancement of a Novel Method for Mutational Disease Prediction using Bioinformatics Techniques and Backpropagation Algorithm
5 pages, 8 figures, 1 Table, conference or other essential info
International Journal of Scientific & Engineering Research, Volume 4, Issue 6, June 2013 pages 1169-1173
null
null
cs.CE q-bio.QM
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The noval method for mutational disease prediction using bioinformatics tools and datasets for diagnosis the malignant mutations with powerful Artificial Neural Network (Backpropagation Network) for classifying these malignant mutations are related to gene(s) (like BRCA1 and BRCA2) cause a disease (breast cancer). Th...
[ { "version": "v1", "created": "Fri, 7 Jun 2013 21:53:25 GMT" } ]
2013-06-11T00:00:00
[ [ "Ismaeel", "Ayad Ghany", "" ], [ "Ablahad", "Anar Auda", "" ] ]
TITLE: Enhancement of a Novel Method for Mutational Disease Prediction using Bioinformatics Techniques and Backpropagation Algorithm ABSTRACT: The noval method for mutational disease prediction using bioinformatics tools and datasets for diagnosis the malignant mutations with powerful Artificial Neural Network (B...
1306.2084
Maximilian Nickel
Maximilian Nickel, Volker Tresp
Logistic Tensor Factorization for Multi-Relational Data
Accepted at ICML 2013 Workshop "Structured Learning: Inferring Graphs from Structured and Unstructured Inputs" (SLG 2013)
null
null
null
stat.ML cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Tensor factorizations have become increasingly popular approaches for various learning tasks on structured data. In this work, we extend the RESCAL tensor factorization, which has shown state-of-the-art results for multi-relational learning, to account for the binary nature of adjacency tensors. We study the improvem...
[ { "version": "v1", "created": "Mon, 10 Jun 2013 01:45:49 GMT" } ]
2013-06-11T00:00:00
[ [ "Nickel", "Maximilian", "" ], [ "Tresp", "Volker", "" ] ]
TITLE: Logistic Tensor Factorization for Multi-Relational Data ABSTRACT: Tensor factorizations have become increasingly popular approaches for various learning tasks on structured data. In this work, we extend the RESCAL tensor factorization, which has shown state-of-the-art results for multi-relational learning, t...
1306.2118
E.N.Sathishkumar
E.N.Sathishkumar, K.Thangavel, T.Chandrasekhar
A Novel Approach for Single Gene Selection Using Clustering and Dimensionality Reduction
6 pages, 4 figures. arXiv admin note: text overlap with arXiv:1306.1323
International Journal of Scientific & Engineering Research, Volume 4, Issue 5, May-2013, page no 1540-1545
null
null
cs.CE cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We extend the standard rough set-based approach to deal with huge amounts of numeric attributes versus small amount of available objects. Here, a novel approach of clustering along with dimensionality reduction; Hybrid Fuzzy C Means-Quick Reduct (FCMQR) algorithm is proposed for single gene selection. Gene selection ...
[ { "version": "v1", "created": "Mon, 10 Jun 2013 07:28:51 GMT" } ]
2013-06-11T00:00:00
[ [ "Sathishkumar", "E. N.", "" ], [ "Thangavel", "K.", "" ], [ "Chandrasekhar", "T.", "" ] ]
TITLE: A Novel Approach for Single Gene Selection Using Clustering and Dimensionality Reduction ABSTRACT: We extend the standard rough set-based approach to deal with huge amounts of numeric attributes versus small amount of available objects. Here, a novel approach of clustering along with dimensionality reducti...
1305.0445
Yoshua Bengio
Yoshua Bengio
Deep Learning of Representations: Looking Forward
null
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Deep learning research aims at discovering learning algorithms that discover multiple levels of distributed representations, with higher levels representing more abstract concepts. Although the study of deep learning has already led to impressive theoretical results, learning algorithms and breakthrough experiments, ...
[ { "version": "v1", "created": "Thu, 2 May 2013 14:33:28 GMT" }, { "version": "v2", "created": "Fri, 7 Jun 2013 02:35:21 GMT" } ]
2013-06-10T00:00:00
[ [ "Bengio", "Yoshua", "" ] ]
TITLE: Deep Learning of Representations: Looking Forward ABSTRACT: Deep learning research aims at discovering learning algorithms that discover multiple levels of distributed representations, with higher levels representing more abstract concepts. Although the study of deep learning has already led to impressive th...
1306.1716
Alexander Petukhov
Alexander Petukhov and Inna Kozlov
Fast greedy algorithm for subspace clustering from corrupted and incomplete data
arXiv admin note: substantial text overlap with arXiv:1304.4282
null
null
null
cs.LG cs.DS math.NA stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We describe the Fast Greedy Sparse Subspace Clustering (FGSSC) algorithm providing an efficient method for clustering data belonging to a few low-dimensional linear or affine subspaces. The main difference of our algorithm from predecessors is its ability to work with noisy data having a high rate of erasures (missed...
[ { "version": "v1", "created": "Fri, 7 Jun 2013 13:14:50 GMT" } ]
2013-06-10T00:00:00
[ [ "Petukhov", "Alexander", "" ], [ "Kozlov", "Inna", "" ] ]
TITLE: Fast greedy algorithm for subspace clustering from corrupted and incomplete data ABSTRACT: We describe the Fast Greedy Sparse Subspace Clustering (FGSSC) algorithm providing an efficient method for clustering data belonging to a few low-dimensional linear or affine subspaces. The main difference of our alg...
1104.2930
Donghui Yan
Donghui Yan, Aiyou Chen, Michael I. Jordan
Cluster Forests
23 pages, 6 figures
Computational Statistics and Data Analysis 2013, Vol. 66, 178-192
10.1016/j.csda.2013.04.010
COMSTA5571
stat.ME cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
With inspiration from Random Forests (RF) in the context of classification, a new clustering ensemble method---Cluster Forests (CF) is proposed. Geometrically, CF randomly probes a high-dimensional data cloud to obtain "good local clusterings" and then aggregates via spectral clustering to obtain cluster assignments ...
[ { "version": "v1", "created": "Thu, 14 Apr 2011 21:29:10 GMT" }, { "version": "v2", "created": "Mon, 18 Apr 2011 05:06:04 GMT" }, { "version": "v3", "created": "Thu, 23 May 2013 21:17:26 GMT" } ]
2013-06-07T00:00:00
[ [ "Yan", "Donghui", "" ], [ "Chen", "Aiyou", "" ], [ "Jordan", "Michael I.", "" ] ]
TITLE: Cluster Forests ABSTRACT: With inspiration from Random Forests (RF) in the context of classification, a new clustering ensemble method---Cluster Forests (CF) is proposed. Geometrically, CF randomly probes a high-dimensional data cloud to obtain "good local clusterings" and then aggregates via spectral cluste...
1306.1298
Allon G. Percus
Cristina Garcia-Cardona, Arjuna Flenner, Allon G. Percus
Multiclass Semi-Supervised Learning on Graphs using Ginzburg-Landau Functional Minimization
16 pages, to appear in Springer's Lecture Notes in Computer Science volume "Pattern Recognition Applications and Methods 2013", part of series on Advances in Intelligent and Soft Computing
null
null
null
stat.ML cs.LG math.ST physics.data-an stat.TH
http://creativecommons.org/licenses/publicdomain/
We present a graph-based variational algorithm for classification of high-dimensional data, generalizing the binary diffuse interface model to the case of multiple classes. Motivated by total variation techniques, the method involves minimizing an energy functional made up of three terms. The first two terms promote ...
[ { "version": "v1", "created": "Thu, 6 Jun 2013 05:32:00 GMT" } ]
2013-06-07T00:00:00
[ [ "Garcia-Cardona", "Cristina", "" ], [ "Flenner", "Arjuna", "" ], [ "Percus", "Allon G.", "" ] ]
TITLE: Multiclass Semi-Supervised Learning on Graphs using Ginzburg-Landau Functional Minimization ABSTRACT: We present a graph-based variational algorithm for classification of high-dimensional data, generalizing the binary diffuse interface model to the case of multiple classes. Motivated by total variation tec...
1209.1797
Eitan Menahem
Eitan Menahem, Alon Schclar, Lior Rokach, Yuval Elovici
Securing Your Transactions: Detecting Anomalous Patterns In XML Documents
Journal version (14 pages)
null
null
null
cs.CR cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
XML transactions are used in many information systems to store data and interact with other systems. Abnormal transactions, the result of either an on-going cyber attack or the actions of a benign user, can potentially harm the interacting systems and therefore they are regarded as a threat. In this paper we address ...
[ { "version": "v1", "created": "Sun, 9 Sep 2012 13:02:49 GMT" }, { "version": "v2", "created": "Tue, 11 Sep 2012 05:48:34 GMT" }, { "version": "v3", "created": "Wed, 5 Jun 2013 13:19:42 GMT" } ]
2013-06-06T00:00:00
[ [ "Menahem", "Eitan", "" ], [ "Schclar", "Alon", "" ], [ "Rokach", "Lior", "" ], [ "Elovici", "Yuval", "" ] ]
TITLE: Securing Your Transactions: Detecting Anomalous Patterns In XML Documents ABSTRACT: XML transactions are used in many information systems to store data and interact with other systems. Abnormal transactions, the result of either an on-going cyber attack or the actions of a benign user, can potentially harm...
1306.0974
Jiuqing Wan
Jiuqing Wan, Li Liu
Distributed Bayesian inference for consistent labeling of tracked objects in non-overlapping camera networks
19 pages, 8 figures
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
One of the fundamental requirements for visual surveillance using non-overlapping camera networks is the correct labeling of tracked objects on each camera in a consistent way,in the sense that the captured tracklets, or observations in this paper, of the same object at different cameras should be assigned with the s...
[ { "version": "v1", "created": "Wed, 5 Jun 2013 03:50:58 GMT" } ]
2013-06-06T00:00:00
[ [ "Wan", "Jiuqing", "" ], [ "Liu", "Li", "" ] ]
TITLE: Distributed Bayesian inference for consistent labeling of tracked objects in non-overlapping camera networks ABSTRACT: One of the fundamental requirements for visual surveillance using non-overlapping camera networks is the correct labeling of tracked objects on each camera in a consistent way,in the sense...
1306.1083
Puneet Kumar
Pierre-Yves Baudin (INRIA Saclay - Ile de France), Danny Goodman, Puneet Kumar (INRIA Saclay - Ile de France, CVN), Noura Azzabou (MIRCEN, UPMC), Pierre G. Carlier (UPMC), Nikos Paragios (INRIA Saclay - Ile de France, LIGM, ENPC, MAS), M. Pawan Kumar (INRIA Saclay - Ile de France, CVN)
Discriminative Parameter Estimation for Random Walks Segmentation: Technical Report
null
null
null
null
cs.CV cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The Random Walks (RW) algorithm is one of the most e - cient and easy-to-use probabilistic segmentation methods. By combining contrast terms with prior terms, it provides accurate segmentations of medical images in a fully automated manner. However, one of the main drawbacks of using the RW algorithm is that its para...
[ { "version": "v1", "created": "Wed, 5 Jun 2013 12:48:02 GMT" } ]
2013-06-06T00:00:00
[ [ "Baudin", "Pierre-Yves", "", "INRIA Saclay - Ile de France" ], [ "Goodman", "Danny", "", "INRIA Saclay - Ile de France, CVN" ], [ "Kumar", "Puneet", "", "INRIA Saclay - Ile de France, CVN" ], [ "Azzabou", "Noura", "", "MIRCEN,\n UPMC" ...
TITLE: Discriminative Parameter Estimation for Random Walks Segmentation: Technical Report ABSTRACT: The Random Walks (RW) algorithm is one of the most e - cient and easy-to-use probabilistic segmentation methods. By combining contrast terms with prior terms, it provides accurate segmentations of medical images i...
1306.0886
Felix X. Yu
Felix X. Yu, Dong Liu, Sanjiv Kumar, Tony Jebara, Shih-Fu Chang
$\propto$SVM for learning with label proportions
Appears in Proceedings of the 30th International Conference on Machine Learning (ICML 2013)
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We study the problem of learning with label proportions in which the training data is provided in groups and only the proportion of each class in each group is known. We propose a new method called proportion-SVM, or $\propto$SVM, which explicitly models the latent unknown instance labels together with the known grou...
[ { "version": "v1", "created": "Tue, 4 Jun 2013 19:35:31 GMT" } ]
2013-06-05T00:00:00
[ [ "Yu", "Felix X.", "" ], [ "Liu", "Dong", "" ], [ "Kumar", "Sanjiv", "" ], [ "Jebara", "Tony", "" ], [ "Chang", "Shih-Fu", "" ] ]
TITLE: $\propto$SVM for learning with label proportions ABSTRACT: We study the problem of learning with label proportions in which the training data is provided in groups and only the proportion of each class in each group is known. We propose a new method called proportion-SVM, or $\propto$SVM, which explicitly mo...
1210.0091
Hong Zhao
Hong Zhao, Fan Min, William Zhu
Test-cost-sensitive attribute reduction of data with normal distribution measurement errors
This paper has been withdrawn by the author due to the error of the title
null
null
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The measurement error with normal distribution is universal in applications. Generally, smaller measurement error requires better instrument and higher test cost. In decision making based on attribute values of objects, we shall select an attribute subset with appropriate measurement error to minimize the total test ...
[ { "version": "v1", "created": "Sat, 29 Sep 2012 10:22:55 GMT" }, { "version": "v2", "created": "Mon, 3 Jun 2013 03:15:51 GMT" } ]
2013-06-04T00:00:00
[ [ "Zhao", "Hong", "" ], [ "Min", "Fan", "" ], [ "Zhu", "William", "" ] ]
TITLE: Test-cost-sensitive attribute reduction of data with normal distribution measurement errors ABSTRACT: The measurement error with normal distribution is universal in applications. Generally, smaller measurement error requires better instrument and higher test cost. In decision making based on attribute valu...
1303.0309
Krikamol Muandet
Krikamol Muandet and Bernhard Sch\"olkopf
One-Class Support Measure Machines for Group Anomaly Detection
Conference on Uncertainty in Artificial Intelligence (UAI2013)
null
null
null
stat.ML cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We propose one-class support measure machines (OCSMMs) for group anomaly detection which aims at recognizing anomalous aggregate behaviors of data points. The OCSMMs generalize well-known one-class support vector machines (OCSVMs) to a space of probability measures. By formulating the problem as quantile estimation o...
[ { "version": "v1", "created": "Fri, 1 Mar 2013 21:50:09 GMT" }, { "version": "v2", "created": "Sat, 1 Jun 2013 13:42:46 GMT" } ]
2013-06-04T00:00:00
[ [ "Muandet", "Krikamol", "" ], [ "Schölkopf", "Bernhard", "" ] ]
TITLE: One-Class Support Measure Machines for Group Anomaly Detection ABSTRACT: We propose one-class support measure machines (OCSMMs) for group anomaly detection which aims at recognizing anomalous aggregate behaviors of data points. The OCSMMs generalize well-known one-class support vector machines (OCSVMs) to a ...
1306.0152
Eugenio Culurciello Eugenio Culurciello
Eugenio Culurciello, Jonghoon Jin, Aysegul Dundar, Jordan Bates
An Analysis of the Connections Between Layers of Deep Neural Networks
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present an analysis of different techniques for selecting the connection be- tween layers of deep neural networks. Traditional deep neural networks use ran- dom connection tables between layers to keep the number of connections small and tune to different image features. This kind of connection performs adequately...
[ { "version": "v1", "created": "Sat, 1 Jun 2013 21:37:25 GMT" } ]
2013-06-04T00:00:00
[ [ "Culurciello", "Eugenio", "" ], [ "Jin", "Jonghoon", "" ], [ "Dundar", "Aysegul", "" ], [ "Bates", "Jordan", "" ] ]
TITLE: An Analysis of the Connections Between Layers of Deep Neural Networks ABSTRACT: We present an analysis of different techniques for selecting the connection be- tween layers of deep neural networks. Traditional deep neural networks use ran- dom connection tables between layers to keep the number of connection...
1306.0326
Tomasz Kajdanowicz
Tomasz Kajdanowicz, Przemyslaw Kazienko, Wojciech Indyk
Parallel Processing of Large Graphs
Preprint submitted to Future Generation Computer Systems
null
null
null
cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
More and more large data collections are gathered worldwide in various IT systems. Many of them possess the networked nature and need to be processed and analysed as graph structures. Due to their size they require very often usage of parallel paradigm for efficient computation. Three parallel techniques have been co...
[ { "version": "v1", "created": "Mon, 3 Jun 2013 08:44:32 GMT" } ]
2013-06-04T00:00:00
[ [ "Kajdanowicz", "Tomasz", "" ], [ "Kazienko", "Przemyslaw", "" ], [ "Indyk", "Wojciech", "" ] ]
TITLE: Parallel Processing of Large Graphs ABSTRACT: More and more large data collections are gathered worldwide in various IT systems. Many of them possess the networked nature and need to be processed and analysed as graph structures. Due to their size they require very often usage of parallel paradigm for effici...
1306.0424
Lionel Tabourier
Abdelhamid Salah Brahim, Lionel Tabourier, B\'en\'edicte Le Grand
A data-driven analysis to question epidemic models for citation cascades on the blogosphere
18 pages, 9 figures, to be published in ICWSM-13 proceedings
null
null
null
cs.SI physics.soc-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Citation cascades in blog networks are often considered as traces of information spreading on this social medium. In this work, we question this point of view using both a structural and semantic analysis of five months activity of the most representative blogs of the french-speaking community.Statistical measures re...
[ { "version": "v1", "created": "Mon, 3 Jun 2013 14:17:54 GMT" } ]
2013-06-04T00:00:00
[ [ "Brahim", "Abdelhamid Salah", "" ], [ "Tabourier", "Lionel", "" ], [ "Grand", "Bénédicte Le", "" ] ]
TITLE: A data-driven analysis to question epidemic models for citation cascades on the blogosphere ABSTRACT: Citation cascades in blog networks are often considered as traces of information spreading on this social medium. In this work, we question this point of view using both a structural and semantic analysis ...
1306.0505
Juan Guan
Kejia Chen, Bo Wang, Juan Guan, and Steve Granick
Diagnosing Heterogeneous Dynamics in Single Molecule/Particle Trajectories with Multiscale Wavelets
null
null
null
null
physics.data-an physics.bio-ph q-bio.QM
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We describe a simple automated method to extract and quantify transient heterogeneous dynamical changes from large datasets generated in single molecule/particle tracking experiments. Based on wavelet transform, the method transforms raw data to locally match dynamics of interest. This is accomplished using statistic...
[ { "version": "v1", "created": "Mon, 3 Jun 2013 17:12:20 GMT" } ]
2013-06-04T00:00:00
[ [ "Chen", "Kejia", "" ], [ "Wang", "Bo", "" ], [ "Guan", "Juan", "" ], [ "Granick", "Steve", "" ] ]
TITLE: Diagnosing Heterogeneous Dynamics in Single Molecule/Particle Trajectories with Multiscale Wavelets ABSTRACT: We describe a simple automated method to extract and quantify transient heterogeneous dynamical changes from large datasets generated in single molecule/particle tracking experiments. Based on wave...
1305.7438
Tian Qiu
Tian Qiu, Tian-Tian Wang, Zi-Ke Zhang, Li-Xin Zhong, Guang Chen
Heterogeneity Involved Network-based Algorithm Leads to Accurate and Personalized Recommendations
null
null
null
null
physics.soc-ph cs.IR cs.SI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Heterogeneity of both the source and target objects is taken into account in a network-based algorithm for the directional resource transformation between objects. Based on a biased heat conduction recommendation method (BHC) which considers the heterogeneity of the target object, we propose a heterogeneous heat cond...
[ { "version": "v1", "created": "Fri, 31 May 2013 15:01:25 GMT" } ]
2013-06-03T00:00:00
[ [ "Qiu", "Tian", "" ], [ "Wang", "Tian-Tian", "" ], [ "Zhang", "Zi-Ke", "" ], [ "Zhong", "Li-Xin", "" ], [ "Chen", "Guang", "" ] ]
TITLE: Heterogeneity Involved Network-based Algorithm Leads to Accurate and Personalized Recommendations ABSTRACT: Heterogeneity of both the source and target objects is taken into account in a network-based algorithm for the directional resource transformation between objects. Based on a biased heat conduction r...
1305.7454
Uwe Aickelin
Jan Feyereisl, Uwe Aickelin
Privileged Information for Data Clustering
Information Sciences 194, 4-23, 2012
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Many machine learning algorithms assume that all input samples are independently and identically distributed from some common distribution on either the input space X, in the case of unsupervised learning, or the input and output space X x Y in the case of supervised and semi-supervised learning. In the last number o...
[ { "version": "v1", "created": "Fri, 31 May 2013 15:28:44 GMT" } ]
2013-06-03T00:00:00
[ [ "Feyereisl", "Jan", "" ], [ "Aickelin", "Uwe", "" ] ]
TITLE: Privileged Information for Data Clustering ABSTRACT: Many machine learning algorithms assume that all input samples are independently and identically distributed from some common distribution on either the input space X, in the case of unsupervised learning, or the input and output space X x Y in the case of...
1305.7465
Uwe Aickelin
Yihui Liu, Uwe Aickelin, Jan Feyereisl, Lindy G. Durrant
Wavelet feature extraction and genetic algorithm for biomarker detection in colorectal cancer data
null
Knowledge-Based Systems 37, 502-514, 2013
null
null
cs.NE cs.CE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Biomarkers which predict patient's survival can play an important role in medical diagnosis and treatment. How to select the significant biomarkers from hundreds of protein markers is a key step in survival analysis. In this paper a novel method is proposed to detect the prognostic biomarkers of survival in colorecta...
[ { "version": "v1", "created": "Fri, 31 May 2013 15:53:08 GMT" } ]
2013-06-03T00:00:00
[ [ "Liu", "Yihui", "" ], [ "Aickelin", "Uwe", "" ], [ "Feyereisl", "Jan", "" ], [ "Durrant", "Lindy G.", "" ] ]
TITLE: Wavelet feature extraction and genetic algorithm for biomarker detection in colorectal cancer data ABSTRACT: Biomarkers which predict patient's survival can play an important role in medical diagnosis and treatment. How to select the significant biomarkers from hundreds of protein markers is a key step in ...
1210.6844
Qing-Bin Lu
Qing-Bin Lu
Cosmic-Ray-Driven Reaction and Greenhouse Effect of Halogenated Molecules: Culprits for Atmospheric Ozone Depletion and Global Climate Change
24 pages, 12 figures; an updated version
Int. J. Mod. Phys. B Vol. 27 (2013) 1350073 (38 pages)
10.1142/S0217979213500732
null
physics.ao-ph physics.atm-clus physics.chem-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This study is focused on the effects of cosmic rays (solar activity) and halogenated molecules (mainly chlorofluorocarbons-CFCs) on atmospheric O3 depletion and global climate change. Brief reviews are first given on the cosmic-ray-driven electron-induced-reaction (CRE) theory for O3 depletion and the warming theory ...
[ { "version": "v1", "created": "Tue, 16 Oct 2012 16:32:15 GMT" }, { "version": "v2", "created": "Mon, 13 May 2013 04:54:36 GMT" } ]
2013-05-31T00:00:00
[ [ "Lu", "Qing-Bin", "" ] ]
TITLE: Cosmic-Ray-Driven Reaction and Greenhouse Effect of Halogenated Molecules: Culprits for Atmospheric Ozone Depletion and Global Climate Change ABSTRACT: This study is focused on the effects of cosmic rays (solar activity) and halogenated molecules (mainly chlorofluorocarbons-CFCs) on atmospheric O3 depletio...
1206.4229
Torsten Ensslin
Torsten A. En{\ss}lin
Information field dynamics for simulation scheme construction
19 pages, 3 color figures, accepted by Phys. Rev. E
null
10.1103/PhysRevE.87.013308
null
physics.comp-ph astro-ph.IM cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Information field dynamics (IFD) is introduced here as a framework to derive numerical schemes for the simulation of physical and other fields without assuming a particular sub-grid structure as many schemes do. IFD constructs an ensemble of non-parametric sub-grid field configurations from the combination of the dat...
[ { "version": "v1", "created": "Tue, 19 Jun 2012 15:01:52 GMT" }, { "version": "v2", "created": "Fri, 5 Oct 2012 10:21:19 GMT" }, { "version": "v3", "created": "Sun, 16 Dec 2012 13:24:30 GMT" }, { "version": "v4", "created": "Fri, 28 Dec 2012 12:29:19 GMT" } ]
2013-05-30T00:00:00
[ [ "Enßlin", "Torsten A.", "" ] ]
TITLE: Information field dynamics for simulation scheme construction ABSTRACT: Information field dynamics (IFD) is introduced here as a framework to derive numerical schemes for the simulation of physical and other fields without assuming a particular sub-grid structure as many schemes do. IFD constructs an ensembl...
1304.5862
Forrest Briggs
Forrest Briggs, Xiaoli Z. Fern, Jed Irvine
Multi-Label Classifier Chains for Bird Sound
6 pages, 1 figure, submission to ICML 2013 workshop on bioacoustics. Note: this is a minor revision- the blind submission format has been replaced with one that shows author names, and a few corrections have been made
null
null
null
cs.LG cs.SD stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Bird sound data collected with unattended microphones for automatic surveys, or mobile devices for citizen science, typically contain multiple simultaneously vocalizing birds of different species. However, few works have considered the multi-label structure in birdsong. We propose to use an ensemble of classifier cha...
[ { "version": "v1", "created": "Mon, 22 Apr 2013 07:44:05 GMT" }, { "version": "v2", "created": "Wed, 29 May 2013 17:36:07 GMT" } ]
2013-05-30T00:00:00
[ [ "Briggs", "Forrest", "" ], [ "Fern", "Xiaoli Z.", "" ], [ "Irvine", "Jed", "" ] ]
TITLE: Multi-Label Classifier Chains for Bird Sound ABSTRACT: Bird sound data collected with unattended microphones for automatic surveys, or mobile devices for citizen science, typically contain multiple simultaneously vocalizing birds of different species. However, few works have considered the multi-label struct...
0910.1800
Cyril Furtlehner
Cyril Furtlehner, Michele Sebag and Xiangliang Zhang
Scaling Analysis of Affinity Propagation
28 pages, 14 figures, Inria research report
Phys. Rev. E 81,066102 (2010)
10.1103/PhysRevE.81.066102
7046
cs.AI cond-mat.stat-mech
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We analyze and exploit some scaling properties of the Affinity Propagation (AP) clustering algorithm proposed by Frey and Dueck (2007). First we observe that a divide and conquer strategy, used on a large data set hierarchically reduces the complexity ${\cal O}(N^2)$ to ${\cal O}(N^{(h+2)/(h+1)})$, for a data-set of ...
[ { "version": "v1", "created": "Fri, 9 Oct 2009 17:43:35 GMT" } ]
2013-05-29T00:00:00
[ [ "Furtlehner", "Cyril", "" ], [ "Sebag", "Michele", "" ], [ "Zhang", "Xiangliang", "" ] ]
TITLE: Scaling Analysis of Affinity Propagation ABSTRACT: We analyze and exploit some scaling properties of the Affinity Propagation (AP) clustering algorithm proposed by Frey and Dueck (2007). First we observe that a divide and conquer strategy, used on a large data set hierarchically reduces the complexity ${\cal...
1305.6046
Sidahmed Mokeddem
Sidahmed Mokeddem, Baghdad Atmani and Mostefa Mokaddem
Supervised Feature Selection for Diagnosis of Coronary Artery Disease Based on Genetic Algorithm
First International Conference on Computational Science and Engineering (CSE-2013), May 18 ~ 19, 2013, Dubai, UAE. Volume Editors: Sundarapandian Vaidyanathan, Dhinaharan Nagamalai
null
10.5121/csit.2013.3305
null
cs.LG cs.CE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Feature Selection (FS) has become the focus of much research on decision support systems areas for which data sets with tremendous number of variables are analyzed. In this paper we present a new method for the diagnosis of Coronary Artery Diseases (CAD) founded on Genetic Algorithm (GA) wrapped Bayes Naive (BN) base...
[ { "version": "v1", "created": "Sun, 26 May 2013 18:16:52 GMT" } ]
2013-05-28T00:00:00
[ [ "Mokeddem", "Sidahmed", "" ], [ "Atmani", "Baghdad", "" ], [ "Mokaddem", "Mostefa", "" ] ]
TITLE: Supervised Feature Selection for Diagnosis of Coronary Artery Disease Based on Genetic Algorithm ABSTRACT: Feature Selection (FS) has become the focus of much research on decision support systems areas for which data sets with tremendous number of variables are analyzed. In this paper we present a new meth...
1305.5824
Slim Bouker
Slim Bouker, Rabie Saidi, Sadok Ben Yahia, Engelbert Mephu Nguifo
Towards a semantic and statistical selection of association rules
null
null
null
null
cs.DB
http://creativecommons.org/licenses/by/3.0/
The increasing growth of databases raises an urgent need for more accurate methods to better understand the stored data. In this scope, association rules were extensively used for the analysis and the comprehension of huge amounts of data. However, the number of generated rules is too large to be efficiently analyzed...
[ { "version": "v1", "created": "Fri, 24 May 2013 18:46:34 GMT" } ]
2013-05-27T00:00:00
[ [ "Bouker", "Slim", "" ], [ "Saidi", "Rabie", "" ], [ "Yahia", "Sadok Ben", "" ], [ "Nguifo", "Engelbert Mephu", "" ] ]
TITLE: Towards a semantic and statistical selection of association rules ABSTRACT: The increasing growth of databases raises an urgent need for more accurate methods to better understand the stored data. In this scope, association rules were extensively used for the analysis and the comprehension of huge amounts of...
1305.5826
Kian Hsiang Low
Jie Chen, Nannan Cao, Kian Hsiang Low, Ruofei Ouyang, Colin Keng-Yan Tan, Patrick Jaillet
Parallel Gaussian Process Regression with Low-Rank Covariance Matrix Approximations
29th Conference on Uncertainty in Artificial Intelligence (UAI 2013), Extended version with proofs, 13 pages
null
null
null
stat.ML cs.DC cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Gaussian processes (GP) are Bayesian non-parametric models that are widely used for probabilistic regression. Unfortunately, it cannot scale well with large data nor perform real-time predictions due to its cubic time cost in the data size. This paper presents two parallel GP regression methods that exploit low-rank ...
[ { "version": "v1", "created": "Fri, 24 May 2013 19:00:28 GMT" } ]
2013-05-27T00:00:00
[ [ "Chen", "Jie", "" ], [ "Cao", "Nannan", "" ], [ "Low", "Kian Hsiang", "" ], [ "Ouyang", "Ruofei", "" ], [ "Tan", "Colin Keng-Yan", "" ], [ "Jaillet", "Patrick", "" ] ]
TITLE: Parallel Gaussian Process Regression with Low-Rank Covariance Matrix Approximations ABSTRACT: Gaussian processes (GP) are Bayesian non-parametric models that are widely used for probabilistic regression. Unfortunately, it cannot scale well with large data nor perform real-time predictions due to its cubic ...
1305.5267
Bluma Gelley
Bluma S. Gelley
Investigating Deletion in Wikipedia
null
null
null
null
cs.CY cs.DL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Several hundred Wikipedia articles are deleted every day because they lack sufficient significance to be included in the encyclopedia. We collect a dataset of deleted articles and analyze them to determine whether or not the deletions were justified. We find evidence to support the hypothesis that many deletions are ...
[ { "version": "v1", "created": "Wed, 22 May 2013 20:54:18 GMT" } ]
2013-05-24T00:00:00
[ [ "Gelley", "Bluma S.", "" ] ]
TITLE: Investigating Deletion in Wikipedia ABSTRACT: Several hundred Wikipedia articles are deleted every day because they lack sufficient significance to be included in the encyclopedia. We collect a dataset of deleted articles and analyze them to determine whether or not the deletions were justified. We find evid...
1305.5306
Yin Zheng
Yin Zheng, Yu-Jin Zhang, Hugo Larochelle
A Supervised Neural Autoregressive Topic Model for Simultaneous Image Classification and Annotation
13 pages, 5 figures
null
null
null
cs.CV cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Topic modeling based on latent Dirichlet allocation (LDA) has been a framework of choice to perform scene recognition and annotation. Recently, a new type of topic model called the Document Neural Autoregressive Distribution Estimator (DocNADE) was proposed and demonstrated state-of-the-art performance for document m...
[ { "version": "v1", "created": "Thu, 23 May 2013 03:35:31 GMT" } ]
2013-05-24T00:00:00
[ [ "Zheng", "Yin", "" ], [ "Zhang", "Yu-Jin", "" ], [ "Larochelle", "Hugo", "" ] ]
TITLE: A Supervised Neural Autoregressive Topic Model for Simultaneous Image Classification and Annotation ABSTRACT: Topic modeling based on latent Dirichlet allocation (LDA) has been a framework of choice to perform scene recognition and annotation. Recently, a new type of topic model called the Document Neural ...
1304.1209
Ben Fulcher
Ben D. Fulcher, Max A. Little, Nick S. Jones
Highly comparative time-series analysis: The empirical structure of time series and their methods
null
J. R. Soc. Interface vol. 10 no. 83 20130048 (2013)
10.1098/rsif.2013.0048
null
physics.data-an cs.CV physics.bio-ph q-bio.QM stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The process of collecting and organizing sets of observations represents a common theme throughout the history of science. However, despite the ubiquity of scientists measuring, recording, and analyzing the dynamics of different processes, an extensive organization of scientific time-series data and analysis methods ...
[ { "version": "v1", "created": "Wed, 3 Apr 2013 23:24:02 GMT" } ]
2013-05-23T00:00:00
[ [ "Fulcher", "Ben D.", "" ], [ "Little", "Max A.", "" ], [ "Jones", "Nick S.", "" ] ]
TITLE: Highly comparative time-series analysis: The empirical structure of time series and their methods ABSTRACT: The process of collecting and organizing sets of observations represents a common theme throughout the history of science. However, despite the ubiquity of scientists measuring, recording, and analyz...
1305.5189
Neven Caplar
Neven Caplar, Mirko Suznjevic and Maja Matijasevic
Analysis of player's in-game performance vs rating: Case study of Heroes of Newerth
8 pages, 14 figures, to appear in proceedings of "Foundation of Digital Games 2013" conference (14-17 May 2013)
null
null
null
physics.soc-ph cs.SI physics.data-an physics.pop-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We evaluate the rating system of "Heroes of Newerth" (HoN), a multiplayer online action role-playing game, by using statistical analysis and comparison of a player's in-game performance metrics and the player rating assigned by the rating system. The datasets for the analysis have been extracted from the web sites th...
[ { "version": "v1", "created": "Wed, 22 May 2013 16:45:47 GMT" } ]
2013-05-23T00:00:00
[ [ "Caplar", "Neven", "" ], [ "Suznjevic", "Mirko", "" ], [ "Matijasevic", "Maja", "" ] ]
TITLE: Analysis of player's in-game performance vs rating: Case study of Heroes of Newerth ABSTRACT: We evaluate the rating system of "Heroes of Newerth" (HoN), a multiplayer online action role-playing game, by using statistical analysis and comparison of a player's in-game performance metrics and the player rati...
1209.5601
Fan Min
Fan Min, Qinghua Hu, William Zhu
Feature selection with test cost constraint
23 pages
null
10.1016/j.ijar.2013.04.003
null
cs.AI cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Feature selection is an important preprocessing step in machine learning and data mining. In real-world applications, costs, including money, time and other resources, are required to acquire the features. In some cases, there is a test cost constraint due to limited resources. We shall deliberately select an informa...
[ { "version": "v1", "created": "Tue, 25 Sep 2012 13:21:40 GMT" } ]
2013-05-22T00:00:00
[ [ "Min", "Fan", "" ], [ "Hu", "Qinghua", "" ], [ "Zhu", "William", "" ] ]
TITLE: Feature selection with test cost constraint ABSTRACT: Feature selection is an important preprocessing step in machine learning and data mining. In real-world applications, costs, including money, time and other resources, are required to acquire the features. In some cases, there is a test cost constraint du...
1302.7278
Gregory Kucherov
Kamil Salikhov, Gustavo Sacomoto, and Gregory Kucherov
Using cascading Bloom filters to improve the memory usage for de Brujin graphs
12 pages, submitted
null
null
null
cs.DS
http://creativecommons.org/licenses/by/3.0/
De Brujin graphs are widely used in bioinformatics for processing next-generation sequencing data. Due to a very large size of NGS datasets, it is essential to represent de Bruijn graphs compactly, and several approaches to this problem have been proposed recently. In this work, we show how to reduce the memory requi...
[ { "version": "v1", "created": "Thu, 28 Feb 2013 18:35:21 GMT" }, { "version": "v2", "created": "Tue, 21 May 2013 15:25:19 GMT" } ]
2013-05-22T00:00:00
[ [ "Salikhov", "Kamil", "" ], [ "Sacomoto", "Gustavo", "" ], [ "Kucherov", "Gregory", "" ] ]
TITLE: Using cascading Bloom filters to improve the memory usage for de Brujin graphs ABSTRACT: De Brujin graphs are widely used in bioinformatics for processing next-generation sequencing data. Due to a very large size of NGS datasets, it is essential to represent de Bruijn graphs compactly, and several approach...
1305.4820
Nader Jelassi
Mohamed Nader Jelassi and Sadok Ben Yahia and Engelbert Mephu Nguifo
Nouvelle approche de recommandation personnalisee dans les folksonomies basee sur le profil des utilisateurs
7 pages
null
null
null
cs.IR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In folksonomies, users use to share objects (movies, books, bookmarks, etc.) by annotating them with a set of tags of their own choice. With the rise of the Web 2.0 age, users become the core of the system since they are both the contributors and the creators of the information. Yet, each user has its own profile and...
[ { "version": "v1", "created": "Tue, 21 May 2013 13:59:51 GMT" } ]
2013-05-22T00:00:00
[ [ "Jelassi", "Mohamed Nader", "" ], [ "Yahia", "Sadok Ben", "" ], [ "Nguifo", "Engelbert Mephu", "" ] ]
TITLE: Nouvelle approche de recommandation personnalisee dans les folksonomies basee sur le profil des utilisateurs ABSTRACT: In folksonomies, users use to share objects (movies, books, bookmarks, etc.) by annotating them with a set of tags of their own choice. With the rise of the Web 2.0 age, users become the c...
1208.0787
Shang Shang
Shang Shang, Sanjeev R. Kulkarni, Paul W. Cuff and Pan Hui
A Random Walk Based Model Incorporating Social Information for Recommendations
2012 IEEE Machine Learning for Signal Processing Workshop (MLSP), 6 pages
null
null
null
cs.IR cs.LG
http://creativecommons.org/licenses/by-nc-sa/3.0/
Collaborative filtering (CF) is one of the most popular approaches to build a recommendation system. In this paper, we propose a hybrid collaborative filtering model based on a Makovian random walk to address the data sparsity and cold start problems in recommendation systems. More precisely, we construct a directed ...
[ { "version": "v1", "created": "Fri, 3 Aug 2012 16:15:10 GMT" }, { "version": "v2", "created": "Fri, 17 May 2013 21:57:26 GMT" } ]
2013-05-21T00:00:00
[ [ "Shang", "Shang", "" ], [ "Kulkarni", "Sanjeev R.", "" ], [ "Cuff", "Paul W.", "" ], [ "Hui", "Pan", "" ] ]
TITLE: A Random Walk Based Model Incorporating Social Information for Recommendations ABSTRACT: Collaborative filtering (CF) is one of the most popular approaches to build a recommendation system. In this paper, we propose a hybrid collaborative filtering model based on a Makovian random walk to address the data ...
1211.7312
Francis Casson
F. J. Casson, R. M. McDermott, C. Angioni, Y. Camenen, R. Dux, E. Fable, R. Fischer, B. Geiger, P. Manas, L. Menchero, G. Tardini, and ASDEX Upgrade team
Validation of gyrokinetic modelling of light impurity transport including rotation in ASDEX Upgrade
19 pages, 11 figures, accepted in Nuclear Fusion
Nucl. Fusion 53 063026 (2013)
10.1088/0029-5515/53/6/063026
null
physics.plasm-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Upgraded spectroscopic hardware and an improved impurity concentration calculation allow accurate determination of boron density in the ASDEX Upgrade tokamak. A database of boron measurements is compared to quasilinear and nonlinear gyrokinetic simulations including Coriolis and centrifugal rotational effects over a ...
[ { "version": "v1", "created": "Fri, 30 Nov 2012 17:01:21 GMT" }, { "version": "v2", "created": "Fri, 19 Apr 2013 12:53:48 GMT" } ]
2013-05-21T00:00:00
[ [ "Casson", "F. J.", "" ], [ "McDermott", "R. M.", "" ], [ "Angioni", "C.", "" ], [ "Camenen", "Y.", "" ], [ "Dux", "R.", "" ], [ "Fable", "E.", "" ], [ "Fischer", "R.", "" ], [ "Geiger", "B.", ...
TITLE: Validation of gyrokinetic modelling of light impurity transport including rotation in ASDEX Upgrade ABSTRACT: Upgraded spectroscopic hardware and an improved impurity concentration calculation allow accurate determination of boron density in the ASDEX Upgrade tokamak. A database of boron measurements is co...
1305.4345
Alon Schclar
Alon Schclar and Lior Rokach and Amir Amit
Ensembles of Classifiers based on Dimensionality Reduction
31 pages, 4 figures, 4 tables, Submitted to Pattern Analysis and Applications
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present a novel approach for the construction of ensemble classifiers based on dimensionality reduction. Dimensionality reduction methods represent datasets using a small number of attributes while preserving the information conveyed by the original dataset. The ensemble members are trained based on dimension-redu...
[ { "version": "v1", "created": "Sun, 19 May 2013 10:24:06 GMT" } ]
2013-05-21T00:00:00
[ [ "Schclar", "Alon", "" ], [ "Rokach", "Lior", "" ], [ "Amit", "Amir", "" ] ]
TITLE: Ensembles of Classifiers based on Dimensionality Reduction ABSTRACT: We present a novel approach for the construction of ensemble classifiers based on dimensionality reduction. Dimensionality reduction methods represent datasets using a small number of attributes while preserving the information conveyed by ...
1305.4429
Youfang Lin
Youfang Lin, Xuguang Jia, Mingjie Lin, Steve Gregory, Huaiyu Wan, Zhihao Wu
Inferring High Quality Co-Travel Networks
20 pages, 23 figures
null
null
null
cs.SI physics.soc-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Social networks provide a new perspective for enterprises to better understand their customers and have attracted substantial attention in industry. However, inferring high quality customer social networks is a great challenge while there are no explicit customer relations in many traditional OLTP environments. In th...
[ { "version": "v1", "created": "Mon, 20 May 2013 03:04:23 GMT" } ]
2013-05-21T00:00:00
[ [ "Lin", "Youfang", "" ], [ "Jia", "Xuguang", "" ], [ "Lin", "Mingjie", "" ], [ "Gregory", "Steve", "" ], [ "Wan", "Huaiyu", "" ], [ "Wu", "Zhihao", "" ] ]
TITLE: Inferring High Quality Co-Travel Networks ABSTRACT: Social networks provide a new perspective for enterprises to better understand their customers and have attracted substantial attention in industry. However, inferring high quality customer social networks is a great challenge while there are no explicit cu...
1305.4455
Mark Wilkinson
Ben P Vandervalk, E Luke McCarthy, Mark D Wilkinson
SHARE: A Web Service Based Framework for Distributed Querying and Reasoning on the Semantic Web
Third Asian Semantic Web Conference, ASWC2008 Bangkok, Thailand December 2008, Workshops Proceedings (NEFORS2008), pp69-78
null
null
null
cs.DL cs.AI cs.SE
http://creativecommons.org/licenses/by/3.0/
Here we describe the SHARE system, a web service based framework for distributed querying and reasoning on the semantic web. The main innovations of SHARE are: (1) the extension of a SPARQL query engine to perform on-demand data retrieval from web services, and (2) the extension of an OWL reasoner to test property re...
[ { "version": "v1", "created": "Mon, 20 May 2013 07:54:09 GMT" } ]
2013-05-21T00:00:00
[ [ "Vandervalk", "Ben P", "" ], [ "McCarthy", "E Luke", "" ], [ "Wilkinson", "Mark D", "" ] ]
TITLE: SHARE: A Web Service Based Framework for Distributed Querying and Reasoning on the Semantic Web ABSTRACT: Here we describe the SHARE system, a web service based framework for distributed querying and reasoning on the semantic web. The main innovations of SHARE are: (1) the extension of a SPARQL query engin...
1305.3616
Manuel Gomez Rodriguez
Manuel Gomez Rodriguez, Jure Leskovec, Bernhard Schoelkopf
Modeling Information Propagation with Survival Theory
To appear at ICML '13
null
null
null
cs.SI cs.DS physics.soc-ph stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Networks provide a skeleton for the spread of contagions, like, information, ideas, behaviors and diseases. Many times networks over which contagions diffuse are unobserved and need to be inferred. Here we apply survival theory to develop general additive and multiplicative risk models under which the network inferen...
[ { "version": "v1", "created": "Wed, 15 May 2013 20:01:06 GMT" } ]
2013-05-17T00:00:00
[ [ "Rodriguez", "Manuel Gomez", "" ], [ "Leskovec", "Jure", "" ], [ "Schoelkopf", "Bernhard", "" ] ]
TITLE: Modeling Information Propagation with Survival Theory ABSTRACT: Networks provide a skeleton for the spread of contagions, like, information, ideas, behaviors and diseases. Many times networks over which contagions diffuse are unobserved and need to be inferred. Here we apply survival theory to develop genera...
1305.3384
Lior Rokach
Naseem Biadsy, Lior Rokach, Armin Shmilovici
Transfer Learning for Content-Based Recommender Systems using Tree Matching
null
null
null
null
cs.LG cs.IR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper we present a new approach to content-based transfer learning for solving the data sparsity problem in cases when the users' preferences in the target domain are either scarce or unavailable, but the necessary information on the preferences exists in another domain. We show that training a system to use ...
[ { "version": "v1", "created": "Wed, 15 May 2013 08:00:54 GMT" } ]
2013-05-16T00:00:00
[ [ "Biadsy", "Naseem", "" ], [ "Rokach", "Lior", "" ], [ "Shmilovici", "Armin", "" ] ]
TITLE: Transfer Learning for Content-Based Recommender Systems using Tree Matching ABSTRACT: In this paper we present a new approach to content-based transfer learning for solving the data sparsity problem in cases when the users' preferences in the target domain are either scarce or unavailable, but the necessar...
1302.4922
David Duvenaud
David Duvenaud, James Robert Lloyd, Roger Grosse, Joshua B. Tenenbaum, Zoubin Ghahramani
Structure Discovery in Nonparametric Regression through Compositional Kernel Search
9 pages, 7 figures, To appear in proceedings of the 2013 International Conference on Machine Learning
null
null
null
stat.ML cs.LG stat.ME
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Despite its importance, choosing the structural form of the kernel in nonparametric regression remains a black art. We define a space of kernel structures which are built compositionally by adding and multiplying a small number of base kernels. We present a method for searching over this space of structures which mir...
[ { "version": "v1", "created": "Wed, 20 Feb 2013 14:53:13 GMT" }, { "version": "v2", "created": "Tue, 5 Mar 2013 11:48:12 GMT" }, { "version": "v3", "created": "Fri, 5 Apr 2013 16:53:30 GMT" }, { "version": "v4", "created": "Mon, 13 May 2013 13:10:31 GMT" } ]
2013-05-15T00:00:00
[ [ "Duvenaud", "David", "" ], [ "Lloyd", "James Robert", "" ], [ "Grosse", "Roger", "" ], [ "Tenenbaum", "Joshua B.", "" ], [ "Ghahramani", "Zoubin", "" ] ]
TITLE: Structure Discovery in Nonparametric Regression through Compositional Kernel Search ABSTRACT: Despite its importance, choosing the structural form of the kernel in nonparametric regression remains a black art. We define a space of kernel structures which are built compositionally by adding and multiplying ...
1305.0540
Shang Shang
Shang Shang and Yuk Hui and Pan Hui and Paul Cuff and Sanjeev Kulkarni
Privacy Preserving Recommendation System Based on Groups
null
null
null
null
cs.IR
http://creativecommons.org/licenses/by/3.0/
Recommendation systems have received considerable attention in the recent decades. Yet with the development of information technology and social media, the risk in revealing private data to service providers has been a growing concern to more and more users. Trade-offs between quality and privacy in recommendation sy...
[ { "version": "v1", "created": "Thu, 2 May 2013 19:17:08 GMT" }, { "version": "v2", "created": "Mon, 13 May 2013 19:50:41 GMT" } ]
2013-05-14T00:00:00
[ [ "Shang", "Shang", "" ], [ "Hui", "Yuk", "" ], [ "Hui", "Pan", "" ], [ "Cuff", "Paul", "" ], [ "Kulkarni", "Sanjeev", "" ] ]
TITLE: Privacy Preserving Recommendation System Based on Groups ABSTRACT: Recommendation systems have received considerable attention in the recent decades. Yet with the development of information technology and social media, the risk in revealing private data to service providers has been a growing concern to more...
1305.2788
Fabian Pedregosa
Fabian Pedregosa (INRIA Paris - Rocquencourt, INRIA Saclay - Ile de France), Michael Eickenberg (INRIA Saclay - Ile de France, LNAO), Bertrand Thirion (INRIA Saclay - Ile de France, LNAO), Alexandre Gramfort (LTCI)
HRF estimation improves sensitivity of fMRI encoding and decoding models
3nd International Workshop on Pattern Recognition in NeuroImaging (2013)
null
null
null
cs.LG stat.AP
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Extracting activation patterns from functional Magnetic Resonance Images (fMRI) datasets remains challenging in rapid-event designs due to the inherent delay of blood oxygen level-dependent (BOLD) signal. The general linear model (GLM) allows to estimate the activation from a design matrix and a fixed hemodynamic res...
[ { "version": "v1", "created": "Mon, 13 May 2013 14:19:24 GMT" } ]
2013-05-14T00:00:00
[ [ "Pedregosa", "Fabian", "", "INRIA Paris - Rocquencourt, INRIA Saclay - Ile de\n France" ], [ "Eickenberg", "Michael", "", "INRIA Saclay - Ile de France, LNAO" ], [ "Thirion", "Bertrand", "", "INRIA Saclay - Ile de France, LNAO" ], [ "Gramfort", ...
TITLE: HRF estimation improves sensitivity of fMRI encoding and decoding models ABSTRACT: Extracting activation patterns from functional Magnetic Resonance Images (fMRI) datasets remains challenging in rapid-event designs due to the inherent delay of blood oxygen level-dependent (BOLD) signal. The general linear mo...
1305.2835
Kostas Tsichlas
Andreas Kosmatopoulos and Kostas Tsichlas
Dynamic Top-$k$ Dominating Queries
null
null
null
null
cs.CG cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Let $\mathcal{S}$ be a dataset of $n$ 2-dimensional points. The top-$k$ dominating query aims to report the $k$ points that dominate the most points in $\mathcal{S}$. A point $p$ dominates a point $q$ iff all coordinates of $p$ are smaller than or equal to those of $q$ and at least one of them is strictly smaller. Th...
[ { "version": "v1", "created": "Mon, 13 May 2013 16:30:11 GMT" } ]
2013-05-14T00:00:00
[ [ "Kosmatopoulos", "Andreas", "" ], [ "Tsichlas", "Kostas", "" ] ]
TITLE: Dynamic Top-$k$ Dominating Queries ABSTRACT: Let $\mathcal{S}$ be a dataset of $n$ 2-dimensional points. The top-$k$ dominating query aims to report the $k$ points that dominate the most points in $\mathcal{S}$. A point $p$ dominates a point $q$ iff all coordinates of $p$ are smaller than or equal to those o...
1304.4682
Yuan Li
Yuan Li, Haoyu Gao, Mingmin Yang, Wanqiu Guan, Haixin Ma, Weining Qian, Zhigang Cao, Xiaoguang Yang
What are Chinese Talking about in Hot Weibos?
null
null
null
null
cs.SI cs.CY physics.soc-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
SinaWeibo is a Twitter-like social network service emerging in China in recent years. People can post weibos (microblogs) and communicate with others on it. Based on a dataset of 650 million weibos from August 2009 to January 2012 crawled from APIs of SinaWeibo, we study the hot ones that have been reposted for at le...
[ { "version": "v1", "created": "Wed, 17 Apr 2013 04:25:33 GMT" }, { "version": "v2", "created": "Fri, 10 May 2013 09:52:35 GMT" } ]
2013-05-13T00:00:00
[ [ "Li", "Yuan", "" ], [ "Gao", "Haoyu", "" ], [ "Yang", "Mingmin", "" ], [ "Guan", "Wanqiu", "" ], [ "Ma", "Haixin", "" ], [ "Qian", "Weining", "" ], [ "Cao", "Zhigang", "" ], [ "Yang", "Xiaoguang...
TITLE: What are Chinese Talking about in Hot Weibos? ABSTRACT: SinaWeibo is a Twitter-like social network service emerging in China in recent years. People can post weibos (microblogs) and communicate with others on it. Based on a dataset of 650 million weibos from August 2009 to January 2012 crawled from APIs of S...
1305.1956
Andrew Lan
Andrew S. Lan, Christoph Studer, Andrew E. Waters and Richard G. Baraniuk
Joint Topic Modeling and Factor Analysis of Textual Information and Graded Response Data
null
null
null
null
stat.ML cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Modern machine learning methods are critical to the development of large-scale personalized learning systems that cater directly to the needs of individual learners. The recently developed SPARse Factor Analysis (SPARFA) framework provides a new statistical model and algorithms for machine learning-based learning ana...
[ { "version": "v1", "created": "Wed, 8 May 2013 20:44:55 GMT" }, { "version": "v2", "created": "Fri, 10 May 2013 01:05:09 GMT" } ]
2013-05-13T00:00:00
[ [ "Lan", "Andrew S.", "" ], [ "Studer", "Christoph", "" ], [ "Waters", "Andrew E.", "" ], [ "Baraniuk", "Richard G.", "" ] ]
TITLE: Joint Topic Modeling and Factor Analysis of Textual Information and Graded Response Data ABSTRACT: Modern machine learning methods are critical to the development of large-scale personalized learning systems that cater directly to the needs of individual learners. The recently developed SPARse Factor Analy...
1305.2269
Fang Wang
Fang Wang and Yi Li
Beyond Physical Connections: Tree Models in Human Pose Estimation
CVPR 2013
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Simple tree models for articulated objects prevails in the last decade. However, it is also believed that these simple tree models are not capable of capturing large variations in many scenarios, such as human pose estimation. This paper attempts to address three questions: 1) are simple tree models sufficient? more ...
[ { "version": "v1", "created": "Fri, 10 May 2013 07:09:14 GMT" } ]
2013-05-13T00:00:00
[ [ "Wang", "Fang", "" ], [ "Li", "Yi", "" ] ]
TITLE: Beyond Physical Connections: Tree Models in Human Pose Estimation ABSTRACT: Simple tree models for articulated objects prevails in the last decade. However, it is also believed that these simple tree models are not capable of capturing large variations in many scenarios, such as human pose estimation. This p...
1305.2388
Ehsan Saboori Mr.
Shafigh Parsazad, Ehsan Saboori, Amin Allahyar
Fast Feature Reduction in intrusion detection datasets
null
Parsazad, Shafigh; Saboori, Ehsan; Allahyar, Amin; , "Fast Feature Reduction in intrusion detection datasets," MIPRO, 2012 Proceedings of the 35th International Convention , vol., no., pp.1023-1029, 21-25 May 2012
null
null
cs.CR cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In the most intrusion detection systems (IDS), a system tries to learn characteristics of different type of attacks by analyzing packets that sent or received in network. These packets have a lot of features. But not all of them is required to be analyzed to detect that specific type of attack. Detection speed and co...
[ { "version": "v1", "created": "Mon, 1 Apr 2013 05:27:47 GMT" } ]
2013-05-13T00:00:00
[ [ "Parsazad", "Shafigh", "" ], [ "Saboori", "Ehsan", "" ], [ "Allahyar", "Amin", "" ] ]
TITLE: Fast Feature Reduction in intrusion detection datasets ABSTRACT: In the most intrusion detection systems (IDS), a system tries to learn characteristics of different type of attacks by analyzing packets that sent or received in network. These packets have a lot of features. But not all of them is required to ...
1305.1946
Luca Mazzola
Elena Camossi, Paola Villa, Luca Mazzola
Semantic-based Anomalous Pattern Discovery in Moving Object Trajectories
null
null
null
null
cs.AI cs.IR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this work, we investigate a novel semantic approach for pattern discovery in trajectories that, relying on ontologies, enhances object movement information with event semantics. The approach can be applied to the detection of movement patterns and behaviors whenever the semantics of events occurring along the traj...
[ { "version": "v1", "created": "Wed, 8 May 2013 20:14:03 GMT" } ]
2013-05-10T00:00:00
[ [ "Camossi", "Elena", "" ], [ "Villa", "Paola", "" ], [ "Mazzola", "Luca", "" ] ]
TITLE: Semantic-based Anomalous Pattern Discovery in Moving Object Trajectories ABSTRACT: In this work, we investigate a novel semantic approach for pattern discovery in trajectories that, relying on ontologies, enhances object movement information with event semantics. The approach can be applied to the detection ...
1305.1657
Emanuele Goldoni
Alberto Savioli, Emanuele Goldoni, Pietro Savazzi, Paolo Gamba
Low Complexity Indoor Localization in Wireless Sensor Networks by UWB and Inertial Data Fusion
null
null
null
null
cs.NI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Precise indoor localization of moving targets is a challenging activity which cannot be easily accomplished without combining different sources of information. In this sense, the combination of different data sources with an appropriate filter might improve both positioning and tracking performance. This work propose...
[ { "version": "v1", "created": "Tue, 7 May 2013 21:43:07 GMT" } ]
2013-05-09T00:00:00
[ [ "Savioli", "Alberto", "" ], [ "Goldoni", "Emanuele", "" ], [ "Savazzi", "Pietro", "" ], [ "Gamba", "Paolo", "" ] ]
TITLE: Low Complexity Indoor Localization in Wireless Sensor Networks by UWB and Inertial Data Fusion ABSTRACT: Precise indoor localization of moving targets is a challenging activity which cannot be easily accomplished without combining different sources of information. In this sense, the combination of differen...
1305.1372
Fan Min
Fan Min and William Zhu
Cold-start recommendation through granular association rules
Submitted to Joint Rough Sets 2013
null
null
null
cs.IR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recommender systems are popular in e-commerce as they suggest items of interest to users. Researchers have addressed the cold-start problem where either the user or the item is new. However, the situation with both new user and new item has seldom been considered. In this paper, we propose a cold-start recommendation...
[ { "version": "v1", "created": "Tue, 7 May 2013 01:08:27 GMT" } ]
2013-05-08T00:00:00
[ [ "Min", "Fan", "" ], [ "Zhu", "William", "" ] ]
TITLE: Cold-start recommendation through granular association rules ABSTRACT: Recommender systems are popular in e-commerce as they suggest items of interest to users. Researchers have addressed the cold-start problem where either the user or the item is new. However, the situation with both new user and new item h...
1210.1207
Hema Swetha Koppula
Hema Swetha Koppula, Rudhir Gupta, Ashutosh Saxena
Learning Human Activities and Object Affordances from RGB-D Videos
arXiv admin note: substantial text overlap with arXiv:1208.0967
null
null
null
cs.RO cs.AI cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Understanding human activities and object affordances are two very important skills, especially for personal robots which operate in human environments. In this work, we consider the problem of extracting a descriptive labeling of the sequence of sub-activities being performed by a human, and more importantly, of the...
[ { "version": "v1", "created": "Thu, 4 Oct 2012 04:53:42 GMT" }, { "version": "v2", "created": "Mon, 6 May 2013 01:13:39 GMT" } ]
2013-05-07T00:00:00
[ [ "Koppula", "Hema Swetha", "" ], [ "Gupta", "Rudhir", "" ], [ "Saxena", "Ashutosh", "" ] ]
TITLE: Learning Human Activities and Object Affordances from RGB-D Videos ABSTRACT: Understanding human activities and object affordances are two very important skills, especially for personal robots which operate in human environments. In this work, we consider the problem of extracting a descriptive labeling of t...
1212.2278
Carl Vondrick
Carl Vondrick and Aditya Khosla and Tomasz Malisiewicz and Antonio Torralba
Inverting and Visualizing Features for Object Detection
This paper is a preprint of our conference paper. We have made it available early in the hopes that others find it useful
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We introduce algorithms to visualize feature spaces used by object detectors. The tools in this paper allow a human to put on `HOG goggles' and perceive the visual world as a HOG based object detector sees it. We found that these visualizations allow us to analyze object detection systems in new ways and gain new ins...
[ { "version": "v1", "created": "Tue, 11 Dec 2012 01:59:51 GMT" }, { "version": "v2", "created": "Sun, 5 May 2013 18:17:44 GMT" } ]
2013-05-07T00:00:00
[ [ "Vondrick", "Carl", "" ], [ "Khosla", "Aditya", "" ], [ "Malisiewicz", "Tomasz", "" ], [ "Torralba", "Antonio", "" ] ]
TITLE: Inverting and Visualizing Features for Object Detection ABSTRACT: We introduce algorithms to visualize feature spaces used by object detectors. The tools in this paper allow a human to put on `HOG goggles' and perceive the visual world as a HOG based object detector sees it. We found that these visualization...
1305.1002
Ji Won Yoon
Ji Won Yoon and Nial Friel
Efficient Estimation of the number of neighbours in Probabilistic K Nearest Neighbour Classification
null
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Probabilistic k-nearest neighbour (PKNN) classification has been introduced to improve the performance of original k-nearest neighbour (KNN) classification algorithm by explicitly modelling uncertainty in the classification of each feature vector. However, an issue common to both KNN and PKNN is to select the optimal...
[ { "version": "v1", "created": "Sun, 5 May 2013 09:44:08 GMT" } ]
2013-05-07T00:00:00
[ [ "Yoon", "Ji Won", "" ], [ "Friel", "Nial", "" ] ]
TITLE: Efficient Estimation of the number of neighbours in Probabilistic K Nearest Neighbour Classification ABSTRACT: Probabilistic k-nearest neighbour (PKNN) classification has been introduced to improve the performance of original k-nearest neighbour (KNN) classification algorithm by explicitly modelling uncert...
1305.1040
Ting-Li Chen
Ting-Li Chen
On the Convergence and Consistency of the Blurring Mean-Shift Process
arXiv admin note: text overlap with arXiv:1201.1979
null
null
null
stat.ML cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The mean-shift algorithm is a popular algorithm in computer vision and image processing. It can also be cast as a minimum gamma-divergence estimation. In this paper we focus on the "blurring" mean shift algorithm, which is one version of the mean-shift process that successively blurs the dataset. The analysis of the ...
[ { "version": "v1", "created": "Sun, 5 May 2013 18:51:24 GMT" } ]
2013-05-07T00:00:00
[ [ "Chen", "Ting-Li", "" ] ]
TITLE: On the Convergence and Consistency of the Blurring Mean-Shift Process ABSTRACT: The mean-shift algorithm is a popular algorithm in computer vision and image processing. It can also be cast as a minimum gamma-divergence estimation. In this paper we focus on the "blurring" mean shift algorithm, which is one ve...
1210.0748
Yongming Luo
Yongming Luo, George H. L. Fletcher, Jan Hidders, Yuqing Wu and Paul De Bra
External memory bisimulation reduction of big graphs
17 pages
null
null
null
cs.DB cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we present, to our knowledge, the first known I/O efficient solutions for computing the k-bisimulation partition of a massive directed graph, and performing maintenance of such a partition upon updates to the underlying graph. Ubiquitous in the theory and application of graph data, bisimulation is a ro...
[ { "version": "v1", "created": "Tue, 2 Oct 2012 12:30:15 GMT" }, { "version": "v2", "created": "Mon, 5 Nov 2012 09:26:03 GMT" }, { "version": "v3", "created": "Thu, 2 May 2013 08:23:28 GMT" } ]
2013-05-03T00:00:00
[ [ "Luo", "Yongming", "" ], [ "Fletcher", "George H. L.", "" ], [ "Hidders", "Jan", "" ], [ "Wu", "Yuqing", "" ], [ "De Bra", "Paul", "" ] ]
TITLE: External memory bisimulation reduction of big graphs ABSTRACT: In this paper, we present, to our knowledge, the first known I/O efficient solutions for computing the k-bisimulation partition of a massive directed graph, and performing maintenance of such a partition upon updates to the underlying graph. Ubiq...
1305.0423
Somayeh Danafar
Somayeh Danafar, Paola M.V. Rancoita, Tobias Glasmachers, Kevin Whittingstall, Juergen Schmidhuber
Testing Hypotheses by Regularized Maximum Mean Discrepancy
null
null
null
null
cs.LG cs.AI stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Do two data samples come from different distributions? Recent studies of this fundamental problem focused on embedding probability distributions into sufficiently rich characteristic Reproducing Kernel Hilbert Spaces (RKHSs), to compare distributions by the distance between their embeddings. We show that Regularized ...
[ { "version": "v1", "created": "Thu, 2 May 2013 13:03:53 GMT" } ]
2013-05-03T00:00:00
[ [ "Danafar", "Somayeh", "" ], [ "Rancoita", "Paola M. V.", "" ], [ "Glasmachers", "Tobias", "" ], [ "Whittingstall", "Kevin", "" ], [ "Schmidhuber", "Juergen", "" ] ]
TITLE: Testing Hypotheses by Regularized Maximum Mean Discrepancy ABSTRACT: Do two data samples come from different distributions? Recent studies of this fundamental problem focused on embedding probability distributions into sufficiently rich characteristic Reproducing Kernel Hilbert Spaces (RKHSs), to compare dis...
1301.3641
Ryan Kiros
Ryan Kiros
Training Neural Networks with Stochastic Hessian-Free Optimization
11 pages, ICLR 2013
null
null
null
cs.LG cs.NE stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Hessian-free (HF) optimization has been successfully used for training deep autoencoders and recurrent networks. HF uses the conjugate gradient algorithm to construct update directions through curvature-vector products that can be computed on the same order of time as gradients. In this paper we exploit this property...
[ { "version": "v1", "created": "Wed, 16 Jan 2013 10:10:23 GMT" }, { "version": "v2", "created": "Mon, 18 Mar 2013 05:51:37 GMT" }, { "version": "v3", "created": "Wed, 1 May 2013 06:57:50 GMT" } ]
2013-05-02T00:00:00
[ [ "Kiros", "Ryan", "" ] ]
TITLE: Training Neural Networks with Stochastic Hessian-Free Optimization ABSTRACT: Hessian-free (HF) optimization has been successfully used for training deep autoencoders and recurrent networks. HF uses the conjugate gradient algorithm to construct update directions through curvature-vector products that can be c...
1304.2272
Elmar Peise
Elmar Peise (1), Diego Fabregat (1), Yurii Aulchenko (2), Paolo Bientinesi (1) ((1) AICES, RWTH Aachen, (2) Institute of Cytology and Genetics, Novosibirsk)
Algorithms for Large-scale Whole Genome Association Analysis
null
null
null
AICES-2013/04-2
cs.CE cs.MS q-bio.GN
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In order to associate complex traits with genetic polymorphisms, genome-wide association studies process huge datasets involving tens of thousands of individuals genotyped for millions of polymorphisms. When handling these datasets, which exceed the main memory of contemporary computers, one faces two distinct challe...
[ { "version": "v1", "created": "Mon, 8 Apr 2013 17:13:39 GMT" } ]
2013-05-02T00:00:00
[ [ "Peise", "Elmar", "" ], [ "Fabregat", "Diego", "" ], [ "Aulchenko", "Yurii", "" ], [ "Bientinesi", "Paolo", "" ] ]
TITLE: Algorithms for Large-scale Whole Genome Association Analysis ABSTRACT: In order to associate complex traits with genetic polymorphisms, genome-wide association studies process huge datasets involving tens of thousands of individuals genotyped for millions of polymorphisms. When handling these datasets, which...
1305.0015
Balaji Lakshminarayanan
Balaji Lakshminarayanan and Yee Whye Teh
Inferring ground truth from multi-annotator ordinal data: a probabilistic approach
null
null
null
null
stat.ML cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A popular approach for large scale data annotation tasks is crowdsourcing, wherein each data point is labeled by multiple noisy annotators. We consider the problem of inferring ground truth from noisy ordinal labels obtained from multiple annotators of varying and unknown expertise levels. Annotation models for ordin...
[ { "version": "v1", "created": "Tue, 30 Apr 2013 20:12:01 GMT" } ]
2013-05-02T00:00:00
[ [ "Lakshminarayanan", "Balaji", "" ], [ "Teh", "Yee Whye", "" ] ]
TITLE: Inferring ground truth from multi-annotator ordinal data: a probabilistic approach ABSTRACT: A popular approach for large scale data annotation tasks is crowdsourcing, wherein each data point is labeled by multiple noisy annotators. We consider the problem of inferring ground truth from noisy ordinal label...
1305.0103
Marthinus Christoffel du Plessis Marthinus Christoffel du Plessi
Marthinus Christoffel du Plessis and Masashi Sugiyama
Clustering Unclustered Data: Unsupervised Binary Labeling of Two Datasets Having Different Class Balances
null
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We consider the unsupervised learning problem of assigning labels to unlabeled data. A naive approach is to use clustering methods, but this works well only when data is properly clustered and each cluster corresponds to an underlying class. In this paper, we first show that this unsupervised labeling problem in bala...
[ { "version": "v1", "created": "Wed, 1 May 2013 06:32:12 GMT" } ]
2013-05-02T00:00:00
[ [ "Plessis", "Marthinus Christoffel du", "" ], [ "Sugiyama", "Masashi", "" ] ]
TITLE: Clustering Unclustered Data: Unsupervised Binary Labeling of Two Datasets Having Different Class Balances ABSTRACT: We consider the unsupervised learning problem of assigning labels to unlabeled data. A naive approach is to use clustering methods, but this works well only when data is properly clustered an...
1305.0159
Anthony J Cox
Lilian Janin and Giovanna Rosone and Anthony J. Cox
Adaptive reference-free compression of sequence quality scores
Accepted paper for HiTSeq 2013, to appear in Bioinformatics. Bioinformatics should be considered the original place of publication of this work, please cite accordingly
null
null
null
q-bio.GN cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Motivation: Rapid technological progress in DNA sequencing has stimulated interest in compressing the vast datasets that are now routinely produced. Relatively little attention has been paid to compressing the quality scores that are assigned to each sequence, even though these scores may be harder to compress than...
[ { "version": "v1", "created": "Wed, 1 May 2013 12:51:10 GMT" } ]
2013-05-02T00:00:00
[ [ "Janin", "Lilian", "" ], [ "Rosone", "Giovanna", "" ], [ "Cox", "Anthony J.", "" ] ]
TITLE: Adaptive reference-free compression of sequence quality scores ABSTRACT: Motivation: Rapid technological progress in DNA sequencing has stimulated interest in compressing the vast datasets that are now routinely produced. Relatively little attention has been paid to compressing the quality scores that are ...
1305.0160
Anthony J Cox
Markus J. Bauer and Anthony J. Cox and Giovanna Rosone and Marinella Sciortino
Lightweight LCP Construction for Next-Generation Sequencing Datasets
Springer LNCS (Lecture Notes in Computer Science) should be considered as the original place of publication, please cite accordingly. The final version of this manuscript is available at http://link.springer.com/chapter/10.1007/978-3-642-33122-0_26
Lecture Notes in Computer Science Volume 7534, 2012, pp 326-337
10.1007/978-3-642-33122-0_26
null
cs.DS q-bio.GN
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The advent of "next-generation" DNA sequencing (NGS) technologies has meant that collections of hundreds of millions of DNA sequences are now commonplace in bioinformatics. Knowing the longest common prefix array (LCP) of such a collection would facilitate the rapid computation of maximal exact matches, shortest uniq...
[ { "version": "v1", "created": "Wed, 1 May 2013 12:51:45 GMT" } ]
2013-05-02T00:00:00
[ [ "Bauer", "Markus J.", "" ], [ "Cox", "Anthony J.", "" ], [ "Rosone", "Giovanna", "" ], [ "Sciortino", "Marinella", "" ] ]
TITLE: Lightweight LCP Construction for Next-Generation Sequencing Datasets ABSTRACT: The advent of "next-generation" DNA sequencing (NGS) technologies has meant that collections of hundreds of millions of DNA sequences are now commonplace in bioinformatics. Knowing the longest common prefix array (LCP) of such a c...
1211.2863
Alon Schclar
Alon Schclar
Multi-Sensor Fusion via Reduction of Dimensionality
PhD Thesis, Tel Aviv Univ, 2008
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Large high-dimensional datasets are becoming more and more popular in an increasing number of research areas. Processing the high dimensional data incurs a high computational cost and is inherently inefficient since many of the values that describe a data object are redundant due to noise and inner correlations. Cons...
[ { "version": "v1", "created": "Tue, 13 Nov 2012 01:05:42 GMT" } ]
2013-05-01T00:00:00
[ [ "Schclar", "Alon", "" ] ]
TITLE: Multi-Sensor Fusion via Reduction of Dimensionality ABSTRACT: Large high-dimensional datasets are becoming more and more popular in an increasing number of research areas. Processing the high dimensional data incurs a high computational cost and is inherently inefficient since many of the values that describ...
0905.4614
Alexander Artikis
A. Artikis, M. Sergot and G. Paliouras
A Logic Programming Approach to Activity Recognition
The original publication is available in the Proceedings of the 2nd ACM international workshop on Events in multimedia, 2010
null
null
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We have been developing a system for recognising human activity given a symbolic representation of video content. The input of our system is a set of time-stamped short-term activities detected on video frames. The output of our system is a set of recognised long-term activities, which are pre-defined temporal combin...
[ { "version": "v1", "created": "Thu, 28 May 2009 11:44:04 GMT" }, { "version": "v2", "created": "Mon, 29 Apr 2013 17:06:25 GMT" } ]
2013-04-30T00:00:00
[ [ "Artikis", "A.", "" ], [ "Sergot", "M.", "" ], [ "Paliouras", "G.", "" ] ]
TITLE: A Logic Programming Approach to Activity Recognition ABSTRACT: We have been developing a system for recognising human activity given a symbolic representation of video content. The input of our system is a set of time-stamped short-term activities detected on video frames. The output of our system is a set o...
1304.7632
Rastislav \v{S}r\'amek
Barbara Geissmann and Rastislav \v{S}r\'amek
Counting small cuts in a graph
null
null
null
null
cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We study the minimum cut problem in the presence of uncertainty and show how to apply a novel robust optimization approach, which aims to exploit the similarity in subsequent graph measurements or similar graph instances, without posing any assumptions on the way they have been obtained. With experiments we show that...
[ { "version": "v1", "created": "Mon, 29 Apr 2013 12:08:32 GMT" } ]
2013-04-30T00:00:00
[ [ "Geissmann", "Barbara", "" ], [ "Šrámek", "Rastislav", "" ] ]
TITLE: Counting small cuts in a graph ABSTRACT: We study the minimum cut problem in the presence of uncertainty and show how to apply a novel robust optimization approach, which aims to exploit the similarity in subsequent graph measurements or similar graph instances, without posing any assumptions on the way they...
1304.6933
Manuel Keglevic
Manuel Keglevic and Robert Sablatnig
Digit Recognition in Handwritten Weather Records
Part of the OAGM/AAPR 2013 proceedings (arXiv:1304.1876), 8 pages
null
null
OAGM-AAPR/2013/07
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper addresses the automatic recognition of handwritten temperature values in weather records. The localization of table cells is based on line detection using projection profiles. Further, a stroke-preserving line removal method which is based on gradient images is proposed. The presented digit recognition uti...
[ { "version": "v1", "created": "Thu, 25 Apr 2013 15:14:42 GMT" }, { "version": "v2", "created": "Fri, 26 Apr 2013 08:35:18 GMT" } ]
2013-04-29T00:00:00
[ [ "Keglevic", "Manuel", "" ], [ "Sablatnig", "Robert", "" ] ]
TITLE: Digit Recognition in Handwritten Weather Records ABSTRACT: This paper addresses the automatic recognition of handwritten temperature values in weather records. The localization of table cells is based on line detection using projection profiles. Further, a stroke-preserving line removal method which is based...
1304.7140
Michael Helmberger Michael Helmberger
M. Helmberger, M. Urschler, M. Pienn, Z.Balint, A. Olschewski and H. Bischof
Pulmonary Vascular Tree Segmentation from Contrast-Enhanced CT Images
Part of the OAGM/AAPR 2013 proceedings (1304.1876)
null
null
OAGM-AAPR/2013/09
cs.CV physics.med-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present a pulmonary vessel segmentation algorithm, which is fast, fully automatic and robust. It uses a coarse segmentation of the airway tree and a left and right lung labeled volume to restrict a vessel enhancement filter, based on an offset medialness function, to the lungs. We show the application of our algor...
[ { "version": "v1", "created": "Fri, 26 Apr 2013 12:30:36 GMT" } ]
2013-04-29T00:00:00
[ [ "Helmberger", "M.", "" ], [ "Urschler", "M.", "" ], [ "Pienn", "M.", "" ], [ "Balint", "Z.", "" ], [ "Olschewski", "A.", "" ], [ "Bischof", "H.", "" ] ]
TITLE: Pulmonary Vascular Tree Segmentation from Contrast-Enhanced CT Images ABSTRACT: We present a pulmonary vessel segmentation algorithm, which is fast, fully automatic and robust. It uses a coarse segmentation of the airway tree and a left and right lung labeled volume to restrict a vessel enhancement filter, b...
1304.7236
Alessandro Perina
Alessandro Perina, Nebojsa Jojic
In the sight of my wearable camera: Classifying my visual experience
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We introduce and we analyze a new dataset which resembles the input to biological vision systems much more than most previously published ones. Our analysis leaded to several important conclusions. First, it is possible to disambiguate over dozens of visual scenes (locations) encountered over the course of several we...
[ { "version": "v1", "created": "Fri, 26 Apr 2013 17:28:13 GMT" } ]
2013-04-29T00:00:00
[ [ "Perina", "Alessandro", "" ], [ "Jojic", "Nebojsa", "" ] ]
TITLE: In the sight of my wearable camera: Classifying my visual experience ABSTRACT: We introduce and we analyze a new dataset which resembles the input to biological vision systems much more than most previously published ones. Our analysis leaded to several important conclusions. First, it is possible to disambi...
1304.6480
Liwei Wang
Yining Wang, Liwei Wang, Yuanzhi Li, Di He, Tie-Yan Liu, Wei Chen
A Theoretical Analysis of NDCG Type Ranking Measures
COLT 2013
null
null
null
cs.LG cs.IR stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A central problem in ranking is to design a ranking measure for evaluation of ranking functions. In this paper we study, from a theoretical perspective, the widely used Normalized Discounted Cumulative Gain (NDCG)-type ranking measures. Although there are extensive empirical studies of NDCG, little is known about its...
[ { "version": "v1", "created": "Wed, 24 Apr 2013 04:08:23 GMT" } ]
2013-04-25T00:00:00
[ [ "Wang", "Yining", "" ], [ "Wang", "Liwei", "" ], [ "Li", "Yuanzhi", "" ], [ "He", "Di", "" ], [ "Liu", "Tie-Yan", "" ], [ "Chen", "Wei", "" ] ]
TITLE: A Theoretical Analysis of NDCG Type Ranking Measures ABSTRACT: A central problem in ranking is to design a ranking measure for evaluation of ranking functions. In this paper we study, from a theoretical perspective, the widely used Normalized Discounted Cumulative Gain (NDCG)-type ranking measures. Although ...
1304.5894
Bruno Cornelis
Bruno Cornelis, Yun Yang, Joshua T. Vogelstein, Ann Dooms, Ingrid Daubechies, David Dunson
Bayesian crack detection in ultra high resolution multimodal images of paintings
8 pages, double column
null
null
null
cs.CV cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The preservation of our cultural heritage is of paramount importance. Thanks to recent developments in digital acquisition techniques, powerful image analysis algorithms are developed which can be useful non-invasive tools to assist in the restoration and preservation of art. In this paper we propose a semi-supervise...
[ { "version": "v1", "created": "Mon, 22 Apr 2013 09:46:47 GMT" }, { "version": "v2", "created": "Tue, 23 Apr 2013 09:00:01 GMT" } ]
2013-04-24T00:00:00
[ [ "Cornelis", "Bruno", "" ], [ "Yang", "Yun", "" ], [ "Vogelstein", "Joshua T.", "" ], [ "Dooms", "Ann", "" ], [ "Daubechies", "Ingrid", "" ], [ "Dunson", "David", "" ] ]
TITLE: Bayesian crack detection in ultra high resolution multimodal images of paintings ABSTRACT: The preservation of our cultural heritage is of paramount importance. Thanks to recent developments in digital acquisition techniques, powerful image analysis algorithms are developed which can be useful non-invasive...
1304.6291
Fang Wang
Fang Wang and Yi Li
Learning Visual Symbols for Parsing Human Poses in Images
IJCAI 2013
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Parsing human poses in images is fundamental in extracting critical visual information for artificial intelligent agents. Our goal is to learn self-contained body part representations from images, which we call visual symbols, and their symbol-wise geometric contexts in this parsing process. Each symbol is individual...
[ { "version": "v1", "created": "Tue, 23 Apr 2013 14:07:19 GMT" } ]
2013-04-24T00:00:00
[ [ "Wang", "Fang", "" ], [ "Li", "Yi", "" ] ]
TITLE: Learning Visual Symbols for Parsing Human Poses in Images ABSTRACT: Parsing human poses in images is fundamental in extracting critical visual information for artificial intelligent agents. Our goal is to learn self-contained body part representations from images, which we call visual symbols, and their symb...
1212.5238
Andrea Baronchelli
Delia Mocanu, Andrea Baronchelli, Bruno Gon\c{c}alves, Nicola Perra, Alessandro Vespignani
The Twitter of Babel: Mapping World Languages through Microblogging Platforms
null
PLoS One 8, E61981 (2013)
10.1371/journal.pone.0061981
null
physics.soc-ph cs.CL cs.SI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Large scale analysis and statistics of socio-technical systems that just a few short years ago would have required the use of consistent economic and human resources can nowadays be conveniently performed by mining the enormous amount of digital data produced by human activities. Although a characterization of severa...
[ { "version": "v1", "created": "Thu, 20 Dec 2012 20:43:12 GMT" } ]
2013-04-23T00:00:00
[ [ "Mocanu", "Delia", "" ], [ "Baronchelli", "Andrea", "" ], [ "Gonçalves", "Bruno", "" ], [ "Perra", "Nicola", "" ], [ "Vespignani", "Alessandro", "" ] ]
TITLE: The Twitter of Babel: Mapping World Languages through Microblogging Platforms ABSTRACT: Large scale analysis and statistics of socio-technical systems that just a few short years ago would have required the use of consistent economic and human resources can nowadays be conveniently performed by mining the ...
1301.5177
Andrea Scharnhorst
Linda Reijnhoudt, Rodrigo Costas, Ed Noyons, Katy Boerner, Andrea Scharnhorst
"Seed+Expand": A validated methodology for creating high quality publication oeuvres of individual researchers
Paper accepted for the ISSI 2013, small changes in the text due to referee comments, one figure added (Fig 3)
null
null
null
cs.DL cs.IR
http://creativecommons.org/licenses/by/3.0/
The study of science at the individual micro-level frequently requires the disambiguation of author names. The creation of author's publication oeuvres involves matching the list of unique author names to names used in publication databases. Despite recent progress in the development of unique author identifiers, e.g...
[ { "version": "v1", "created": "Tue, 22 Jan 2013 13:16:15 GMT" }, { "version": "v2", "created": "Mon, 22 Apr 2013 11:01:55 GMT" } ]
2013-04-23T00:00:00
[ [ "Reijnhoudt", "Linda", "" ], [ "Costas", "Rodrigo", "" ], [ "Noyons", "Ed", "" ], [ "Boerner", "Katy", "" ], [ "Scharnhorst", "Andrea", "" ] ]
TITLE: "Seed+Expand": A validated methodology for creating high quality publication oeuvres of individual researchers ABSTRACT: The study of science at the individual micro-level frequently requires the disambiguation of author names. The creation of author's publication oeuvres involves matching the list of uniq...
1304.5755
Puneet Kishor
Puneet Kishor, Oshani Seneviratne, and Noah Giansiracusa
Policy Aware Geospatial Data
5 pages. Accepted for ACMGIS 2009, but withdrawn because ACM would not include this paper unless I presented in person (prior commitments prevented me from travel even though I had registered)
null
null
null
cs.OH
http://creativecommons.org/licenses/publicdomain/
Digital Rights Management (DRM) prevents end-users from using content in a manner inconsistent with its creator's wishes. The license describing these use-conditions typically accompanies the content as its metadata. A resulting problem is that the license and the content can get separated and lose track of each othe...
[ { "version": "v1", "created": "Sun, 21 Apr 2013 15:50:46 GMT" } ]
2013-04-23T00:00:00
[ [ "Kishor", "Puneet", "" ], [ "Seneviratne", "Oshani", "" ], [ "Giansiracusa", "Noah", "" ] ]
TITLE: Policy Aware Geospatial Data ABSTRACT: Digital Rights Management (DRM) prevents end-users from using content in a manner inconsistent with its creator's wishes. The license describing these use-conditions typically accompanies the content as its metadata. A resulting problem is that the license and the conte...
1304.4371
Joel Lang
Joel Lang and James Henderson
Efficient Computation of Mean Truncated Hitting Times on Very Large Graphs
null
null
null
null
cs.DS cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Previous work has shown the effectiveness of random walk hitting times as a measure of dissimilarity in a variety of graph-based learning problems such as collaborative filtering, query suggestion or finding paraphrases. However, application of hitting times has been limited to small datasets because of computational...
[ { "version": "v1", "created": "Tue, 16 Apr 2013 09:11:16 GMT" } ]
2013-04-17T00:00:00
[ [ "Lang", "Joel", "" ], [ "Henderson", "James", "" ] ]
TITLE: Efficient Computation of Mean Truncated Hitting Times on Very Large Graphs ABSTRACT: Previous work has shown the effectiveness of random walk hitting times as a measure of dissimilarity in a variety of graph-based learning problems such as collaborative filtering, query suggestion or finding paraphrases. H...
1304.3745
Khadoudja Ghanem
Khadoudja Ghanem
Towards more accurate clustering method by using dynamic time warping
12 pages, 1 figure, 2 tables, journal. arXiv admin note: text overlap with arXiv:1206.3509 by other authors
International Journal of Data Mining & Knowledge Management Process (IJDKP) Vol.3, No.2, March 2013
10.5121/ijdkp.2013.3207
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
An intrinsic problem of classifiers based on machine learning (ML) methods is that their learning time grows as the size and complexity of the training dataset increases. For this reason, it is important to have efficient computational methods and algorithms that can be applied on large datasets, such that it is stil...
[ { "version": "v1", "created": "Fri, 12 Apr 2013 22:23:53 GMT" } ]
2013-04-16T00:00:00
[ [ "Ghanem", "Khadoudja", "" ] ]
TITLE: Towards more accurate clustering method by using dynamic time warping ABSTRACT: An intrinsic problem of classifiers based on machine learning (ML) methods is that their learning time grows as the size and complexity of the training dataset increases. For this reason, it is important to have efficient computa...
1304.3816
Justin Thaler
Amit Chakrabarti and Graham Cormode and Navin Goyal and Justin Thaler
Annotations for Sparse Data Streams
29 pages, 5 tables
null
null
null
cs.CC cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Motivated by cloud computing, a number of recent works have studied annotated data streams and variants thereof. In this setting, a computationally weak verifier (cloud user), lacking the resources to store and manipulate his massive input locally, accesses a powerful but untrusted prover (cloud service). The verifie...
[ { "version": "v1", "created": "Sat, 13 Apr 2013 15:17:28 GMT" } ]
2013-04-16T00:00:00
[ [ "Chakrabarti", "Amit", "" ], [ "Cormode", "Graham", "" ], [ "Goyal", "Navin", "" ], [ "Thaler", "Justin", "" ] ]
TITLE: Annotations for Sparse Data Streams ABSTRACT: Motivated by cloud computing, a number of recent works have studied annotated data streams and variants thereof. In this setting, a computationally weak verifier (cloud user), lacking the resources to store and manipulate his massive input locally, accesses a pow...
1304.4041
Humayun Irshad
H. Irshad, A. Gouaillard, L. Roux, D. Racoceanu
Multispectral Spatial Characterization: Application to Mitosis Detection in Breast Cancer Histopathology
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Accurate detection of mitosis plays a critical role in breast cancer histopathology. Manual detection and counting of mitosis is tedious and subject to considerable inter- and intra-reader variations. Multispectral imaging is a recent medical imaging technology, proven successful in increasing the segmentation accura...
[ { "version": "v1", "created": "Mon, 15 Apr 2013 10:11:34 GMT" } ]
2013-04-16T00:00:00
[ [ "Irshad", "H.", "" ], [ "Gouaillard", "A.", "" ], [ "Roux", "L.", "" ], [ "Racoceanu", "D.", "" ] ]
TITLE: Multispectral Spatial Characterization: Application to Mitosis Detection in Breast Cancer Histopathology ABSTRACT: Accurate detection of mitosis plays a critical role in breast cancer histopathology. Manual detection and counting of mitosis is tedious and subject to considerable inter- and intra-reader var...
1304.3192
Yulan Guo
Yulan Guo, Ferdous Sohel, Mohammed Bennamoun, Min Lu, Jianwei Wan
Rotational Projection Statistics for 3D Local Surface Description and Object Recognition
The final publication is available at link.springer.com International Journal of Computer Vision 2013
null
10.1007/s11263-013-0627-y
null
cs.CV
http://creativecommons.org/licenses/by/3.0/
Recognizing 3D objects in the presence of noise, varying mesh resolution, occlusion and clutter is a very challenging task. This paper presents a novel method named Rotational Projection Statistics (RoPS). It has three major modules: Local Reference Frame (LRF) definition, RoPS feature description and 3D object recog...
[ { "version": "v1", "created": "Thu, 11 Apr 2013 04:26:52 GMT" } ]
2013-04-12T00:00:00
[ [ "Guo", "Yulan", "" ], [ "Sohel", "Ferdous", "" ], [ "Bennamoun", "Mohammed", "" ], [ "Lu", "Min", "" ], [ "Wan", "Jianwei", "" ] ]
TITLE: Rotational Projection Statistics for 3D Local Surface Description and Object Recognition ABSTRACT: Recognizing 3D objects in the presence of noise, varying mesh resolution, occlusion and clutter is a very challenging task. This paper presents a novel method named Rotational Projection Statistics (RoPS). It...
1304.3345
Marzieh Parandehgheibi
Marzieh Parandehgheibi
Probabilistic Classification using Fuzzy Support Vector Machines
6 pages, Proceedings of the 6th INFORMS Workshop on Data Mining and Health Informatics (DM-HI 2011)
null
null
null
cs.LG math.ST stat.TH
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In medical applications such as recognizing the type of a tumor as Malignant or Benign, a wrong diagnosis can be devastating. Methods like Fuzzy Support Vector Machines (FSVM) try to reduce the effect of misplaced training points by assigning a lower weight to the outliers. However, there are still uncertain points w...
[ { "version": "v1", "created": "Thu, 11 Apr 2013 15:44:18 GMT" } ]
2013-04-12T00:00:00
[ [ "Parandehgheibi", "Marzieh", "" ] ]
TITLE: Probabilistic Classification using Fuzzy Support Vector Machines ABSTRACT: In medical applications such as recognizing the type of a tumor as Malignant or Benign, a wrong diagnosis can be devastating. Methods like Fuzzy Support Vector Machines (FSVM) try to reduce the effect of misplaced training points by a...
1304.3406
Seyed Hamed Alemohammad
Seyed Hamed Alemohammad, Dara Entekhabi
Merging Satellite Measurements of Rainfall Using Multi-scale Imagery Technique
6 pages, 10 Figures, WCRP Open Science Conference, 2011
null
null
null
cs.CV cs.IR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Several passive microwave satellites orbit the Earth and measure rainfall. These measurements have the advantage of almost full global coverage when compared to surface rain gauges. However, these satellites have low temporal revisit and missing data over some regions. Image fusion is a useful technique to fill in th...
[ { "version": "v1", "created": "Thu, 11 Apr 2013 19:31:57 GMT" } ]
2013-04-12T00:00:00
[ [ "Alemohammad", "Seyed Hamed", "" ], [ "Entekhabi", "Dara", "" ] ]
TITLE: Merging Satellite Measurements of Rainfall Using Multi-scale Imagery Technique ABSTRACT: Several passive microwave satellites orbit the Earth and measure rainfall. These measurements have the advantage of almost full global coverage when compared to surface rain gauges. However, these satellites have low t...
1302.6569
Nicola Perra
Qian Zhang, Nicola Perra, Bruno Goncalves, Fabio Ciulla, Alessandro Vespignani
Characterizing scientific production and consumption in Physics
null
Nature Scientific Reports 3, 1640 (2013)
10.1038/srep01640
null
physics.soc-ph cs.DL cs.SI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We analyze the entire publication database of the American Physical Society generating longitudinal (50 years) citation networks geolocalized at the level of single urban areas. We define the knowledge diffusion proxy, and scientific production ranking algorithms to capture the spatio-temporal dynamics of Physics kno...
[ { "version": "v1", "created": "Tue, 26 Feb 2013 20:33:51 GMT" } ]
2013-04-11T00:00:00
[ [ "Zhang", "Qian", "" ], [ "Perra", "Nicola", "" ], [ "Goncalves", "Bruno", "" ], [ "Ciulla", "Fabio", "" ], [ "Vespignani", "Alessandro", "" ] ]
TITLE: Characterizing scientific production and consumption in Physics ABSTRACT: We analyze the entire publication database of the American Physical Society generating longitudinal (50 years) citation networks geolocalized at the level of single urban areas. We define the knowledge diffusion proxy, and scientific p...
1303.3087
Togerchety Hitendra sarma
Mallikarjun Hangarge, K.C. Santosh, Srikanth Doddamani, Rajmohan Pardeshi
Statistical Texture Features based Handwritten and Printed Text Classification in South Indian Documents
Appeared in ICECIT-2102
null
null
Volume 1,Number 32
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we use statistical texture features for handwritten and printed text classification. We primarily aim for word level classification in south Indian scripts. Words are first extracted from the scanned document. For each extracted word, statistical texture features are computed such as mean, standard dev...
[ { "version": "v1", "created": "Wed, 13 Mar 2013 04:51:22 GMT" } ]
2013-04-11T00:00:00
[ [ "Hangarge", "Mallikarjun", "" ], [ "Santosh", "K. C.", "" ], [ "Doddamani", "Srikanth", "" ], [ "Pardeshi", "Rajmohan", "" ] ]
TITLE: Statistical Texture Features based Handwritten and Printed Text Classification in South Indian Documents ABSTRACT: In this paper, we use statistical texture features for handwritten and printed text classification. We primarily aim for word level classification in south Indian scripts. Words are first extr...