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1209.1411
Chaoming Song Dr.
Chaoming Song, Dashun Wang, Albert-Laszlo Barabasi
Connections between Human Dynamics and Network Science
null
null
null
null
physics.soc-ph cond-mat.stat-mech cs.SI physics.data-an
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The increasing availability of large-scale data on human behavior has catalyzed simultaneous advances in network theory, capturing the scaling properties of the interactions between a large number of individuals, and human dynamics, quantifying the temporal characteristics of human activity patterns. These two areas ...
[ { "version": "v1", "created": "Thu, 6 Sep 2012 21:04:21 GMT" }, { "version": "v2", "created": "Mon, 8 Apr 2013 20:01:21 GMT" } ]
2013-04-10T00:00:00
[ [ "Song", "Chaoming", "" ], [ "Wang", "Dashun", "" ], [ "Barabasi", "Albert-Laszlo", "" ] ]
TITLE: Connections between Human Dynamics and Network Science ABSTRACT: The increasing availability of large-scale data on human behavior has catalyzed simultaneous advances in network theory, capturing the scaling properties of the interactions between a large number of individuals, and human dynamics, quantifying...
1304.2604
Jean Souviron
Jean Souviron
On the predictability of the number of convex vertices
6 pages, 6 figures
null
null
null
cs.CG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Convex hulls are a fundamental geometric tool used in a number of algorithms. As a side-effect of exhaustive tests for an algorithm for which a convex hull computation was the first step, interesting experimental results were found and are the sunject of this paper. They establish that the number of convex vertices o...
[ { "version": "v1", "created": "Tue, 9 Apr 2013 14:17:12 GMT" } ]
2013-04-10T00:00:00
[ [ "Souviron", "Jean", "" ] ]
TITLE: On the predictability of the number of convex vertices ABSTRACT: Convex hulls are a fundamental geometric tool used in a number of algorithms. As a side-effect of exhaustive tests for an algorithm for which a convex hull computation was the first step, interesting experimental results were found and are the ...
1303.7390
Aasa Feragen
Aasa Feragen, Jens Petersen, Dominik Grimm, Asger Dirksen, Jesper Holst Pedersen, Karsten Borgwardt and Marleen de Bruijne
Geometric tree kernels: Classification of COPD from airway tree geometry
12 pages
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Methodological contributions: This paper introduces a family of kernels for analyzing (anatomical) trees endowed with vector valued measurements made along the tree. While state-of-the-art graph and tree kernels use combinatorial tree/graph structure with discrete node and edge labels, the kernels presented in this p...
[ { "version": "v1", "created": "Fri, 29 Mar 2013 13:25:17 GMT" }, { "version": "v2", "created": "Mon, 8 Apr 2013 12:11:24 GMT" } ]
2013-04-09T00:00:00
[ [ "Feragen", "Aasa", "" ], [ "Petersen", "Jens", "" ], [ "Grimm", "Dominik", "" ], [ "Dirksen", "Asger", "" ], [ "Pedersen", "Jesper Holst", "" ], [ "Borgwardt", "Karsten", "" ], [ "de Bruijne", "Marleen", ""...
TITLE: Geometric tree kernels: Classification of COPD from airway tree geometry ABSTRACT: Methodological contributions: This paper introduces a family of kernels for analyzing (anatomical) trees endowed with vector valued measurements made along the tree. While state-of-the-art graph and tree kernels use combinator...
1304.1924
Shuguang Han
Shuguang Han, Zhen Yue, Daqing He
Automatic Detection of Search Tactic in Individual Information Seeking: A Hidden Markov Model Approach
5 pages, 3 figures, 3 tables
null
null
null
cs.IR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Information seeking process is an important topic in information seeking behavior research. Both qualitative and empirical methods have been adopted in analyzing information seeking processes, with major focus on uncovering the latent search tactics behind user behaviors. Most of the existing works require defining s...
[ { "version": "v1", "created": "Sat, 6 Apr 2013 19:13:41 GMT" } ]
2013-04-09T00:00:00
[ [ "Han", "Shuguang", "" ], [ "Yue", "Zhen", "" ], [ "He", "Daqing", "" ] ]
TITLE: Automatic Detection of Search Tactic in Individual Information Seeking: A Hidden Markov Model Approach ABSTRACT: Information seeking process is an important topic in information seeking behavior research. Both qualitative and empirical methods have been adopted in analyzing information seeking processes, w...
1304.1979
Esteban Moro
Giovanna Miritello, Rub\'en Lara, Manuel Cebri\'an, and Esteban Moro
Limited communication capacity unveils strategies for human interaction
Main Text: 8 pages, 5 figures. Supplementary info: 8 pages, 8 figures
null
null
null
physics.soc-ph cs.SI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Social connectivity is the key process that characterizes the structural properties of social networks and in turn processes such as navigation, influence or information diffusion. Since time, attention and cognition are inelastic resources, humans should have a predefined strategy to manage their social interactions...
[ { "version": "v1", "created": "Sun, 7 Apr 2013 11:00:16 GMT" } ]
2013-04-09T00:00:00
[ [ "Miritello", "Giovanna", "" ], [ "Lara", "Rubén", "" ], [ "Cebrián", "Manuel", "" ], [ "Moro", "Esteban", "" ] ]
TITLE: Limited communication capacity unveils strategies for human interaction ABSTRACT: Social connectivity is the key process that characterizes the structural properties of social networks and in turn processes such as navigation, influence or information diffusion. Since time, attention and cognition are inelas...
1304.2133
Conrad Sanderson
Yongkang Wong, Conrad Sanderson, Sandra Mau, Brian C. Lovell
Dynamic Amelioration of Resolution Mismatches for Local Feature Based Identity Inference
null
International Conference on Pattern Recognition (ICPR), pp. 1200-1203, 2010
10.1109/ICPR.2010.299
null
cs.CV cs.IR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
While existing face recognition systems based on local features are robust to issues such as misalignment, they can exhibit accuracy degradation when comparing images of differing resolutions. This is common in surveillance environments where a gallery of high resolution mugshots is compared to low resolution CCTV pr...
[ { "version": "v1", "created": "Mon, 8 Apr 2013 08:36:55 GMT" } ]
2013-04-09T00:00:00
[ [ "Wong", "Yongkang", "" ], [ "Sanderson", "Conrad", "" ], [ "Mau", "Sandra", "" ], [ "Lovell", "Brian C.", "" ] ]
TITLE: Dynamic Amelioration of Resolution Mismatches for Local Feature Based Identity Inference ABSTRACT: While existing face recognition systems based on local features are robust to issues such as misalignment, they can exhibit accuracy degradation when comparing images of differing resolutions. This is common ...
1304.1712
Michele Coscia
Michele Coscia
Competition and Success in the Meme Pool: a Case Study on Quickmeme.com
null
International Conference of Weblogs and Social Media, 2013
null
null
physics.soc-ph cs.SI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The advent of social media has provided data and insights about how people relate to information and culture. While information is composed by bits and its fundamental building bricks are relatively well understood, the same cannot be said for culture. The fundamental cultural unit has been defined as a "meme". Memes...
[ { "version": "v1", "created": "Fri, 5 Apr 2013 13:52:55 GMT" } ]
2013-04-08T00:00:00
[ [ "Coscia", "Michele", "" ] ]
TITLE: Competition and Success in the Meme Pool: a Case Study on Quickmeme.com ABSTRACT: The advent of social media has provided data and insights about how people relate to information and culture. While information is composed by bits and its fundamental building bricks are relatively well understood, the same ca...
1204.1259
Bal\'azs Hidasi
Bal\'azs Hidasi, Domonkos Tikk
Fast ALS-based tensor factorization for context-aware recommendation from implicit feedback
Accepted for ECML/PKDD 2012, presented on 25th September 2012, Bristol, UK
Proceedings of the 2012 European conference on Machine Learning and Knowledge Discovery in Databases - Volume Part II
10.1007/978-3-642-33486-3_5
null
cs.LG cs.IR cs.NA
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Albeit, the implicit feedback based recommendation problem - when only the user history is available but there are no ratings - is the most typical setting in real-world applications, it is much less researched than the explicit feedback case. State-of-the-art algorithms that are efficient on the explicit case cannot...
[ { "version": "v1", "created": "Thu, 5 Apr 2012 15:34:30 GMT" }, { "version": "v2", "created": "Thu, 4 Apr 2013 15:33:31 GMT" } ]
2013-04-05T00:00:00
[ [ "Hidasi", "Balázs", "" ], [ "Tikk", "Domonkos", "" ] ]
TITLE: Fast ALS-based tensor factorization for context-aware recommendation from implicit feedback ABSTRACT: Albeit, the implicit feedback based recommendation problem - when only the user history is available but there are no ratings - is the most typical setting in real-world applications, it is much less resea...
1206.4813
Adrian Buzatu
Adrian Buzatu, Andreas Warburton, Nils Krumnack, Wei-Ming Yao
A Novel in situ Trigger Combination Method
17 pages, 2 figures, 6 tables, accepted by Nuclear Instruments and Methods in Physics Research A
Nucl.Instrum.Meth. A711 (2013) 111-120
10.1016/j.nima.2013.01.034
FERMILAB-PUB-12-296-E
physics.ins-det hep-ex physics.data-an
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Searches for rare physics processes using particle detectors in high-luminosity colliding hadronic beam environments require the use of multi-level trigger systems to reject colossal background rates in real time. In analyses like the search for the Higgs boson, there is a need to maximize the signal acceptance by co...
[ { "version": "v1", "created": "Thu, 21 Jun 2012 09:14:15 GMT" }, { "version": "v2", "created": "Thu, 4 Apr 2013 13:28:58 GMT" } ]
2013-04-05T00:00:00
[ [ "Buzatu", "Adrian", "" ], [ "Warburton", "Andreas", "" ], [ "Krumnack", "Nils", "" ], [ "Yao", "Wei-Ming", "" ] ]
TITLE: A Novel in situ Trigger Combination Method ABSTRACT: Searches for rare physics processes using particle detectors in high-luminosity colliding hadronic beam environments require the use of multi-level trigger systems to reject colossal background rates in real time. In analyses like the search for the Higgs ...
1304.1262
Conrad Sanderson
Arnold Wiliem, Yongkang Wong, Conrad Sanderson, Peter Hobson, Shaokang Chen, Brian C. Lovell
Classification of Human Epithelial Type 2 Cell Indirect Immunofluoresence Images via Codebook Based Descriptors
null
IEEE Workshop on Applications of Computer Vision (WACV), pp. 95-102, 2013
10.1109/WACV.2013.6475005
null
q-bio.CB cs.CV q-bio.QM
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The Anti-Nuclear Antibody (ANA) clinical pathology test is commonly used to identify the existence of various diseases. A hallmark method for identifying the presence of ANAs is the Indirect Immunofluorescence method on Human Epithelial (HEp-2) cells, due to its high sensitivity and the large range of antigens that c...
[ { "version": "v1", "created": "Thu, 4 Apr 2013 07:51:32 GMT" } ]
2013-04-05T00:00:00
[ [ "Wiliem", "Arnold", "" ], [ "Wong", "Yongkang", "" ], [ "Sanderson", "Conrad", "" ], [ "Hobson", "Peter", "" ], [ "Chen", "Shaokang", "" ], [ "Lovell", "Brian C.", "" ] ]
TITLE: Classification of Human Epithelial Type 2 Cell Indirect Immunofluoresence Images via Codebook Based Descriptors ABSTRACT: The Anti-Nuclear Antibody (ANA) clinical pathology test is commonly used to identify the existence of various diseases. A hallmark method for identifying the presence of ANAs is the Ind...
1304.1391
Sachin Talathi
Manu Nandan, Pramod P. Khargonekar, Sachin S. Talathi
Fast SVM training using approximate extreme points
The manuscript in revised form has been submitted to J. Machine Learning Research
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Applications of non-linear kernel Support Vector Machines (SVMs) to large datasets is seriously hampered by its excessive training time. We propose a modification, called the approximate extreme points support vector machine (AESVM), that is aimed at overcoming this burden. Our approach relies on conducting the SVM o...
[ { "version": "v1", "created": "Thu, 4 Apr 2013 15:08:31 GMT" } ]
2013-04-05T00:00:00
[ [ "Nandan", "Manu", "" ], [ "Khargonekar", "Pramod P.", "" ], [ "Talathi", "Sachin S.", "" ] ]
TITLE: Fast SVM training using approximate extreme points ABSTRACT: Applications of non-linear kernel Support Vector Machines (SVMs) to large datasets is seriously hampered by its excessive training time. We propose a modification, called the approximate extreme points support vector machine (AESVM), that is aimed ...
1302.6396
Michael Schreiber
Michael Schreiber
How to derive an advantage from the arbitrariness of the g-index
13 pages, 3 tables, 3 figures, accepted for publication in Journal of Informetrics
Journal of Informetrics, 7, 555-561 (2013)
10.1016/j.joi.2013.02.003
null
physics.soc-ph cs.DL
http://creativecommons.org/licenses/by-nc-sa/3.0/
The definition of the g-index is as arbitrary as that of the h-index, because the threshold number g^2 of citations to the g most cited papers can be modified by a prefactor at one's discretion, thus taking into account more or less of the highly cited publications within a dataset. In a case study I investigate the ...
[ { "version": "v1", "created": "Tue, 26 Feb 2013 11:24:25 GMT" } ]
2013-04-04T00:00:00
[ [ "Schreiber", "Michael", "" ] ]
TITLE: How to derive an advantage from the arbitrariness of the g-index ABSTRACT: The definition of the g-index is as arbitrary as that of the h-index, because the threshold number g^2 of citations to the g most cited papers can be modified by a prefactor at one's discretion, thus taking into account more or less o...
1304.0886
Conrad Sanderson
Vikas Reddy, Conrad Sanderson, Brian C. Lovell
Improved Anomaly Detection in Crowded Scenes via Cell-based Analysis of Foreground Speed, Size and Texture
null
IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pp. 55-61, 2011
10.1109/CVPRW.2011.5981799
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A robust and efficient anomaly detection technique is proposed, capable of dealing with crowded scenes where traditional tracking based approaches tend to fail. Initial foreground segmentation of the input frames confines the analysis to foreground objects and effectively ignores irrelevant background dynamics. Input...
[ { "version": "v1", "created": "Wed, 3 Apr 2013 09:31:27 GMT" } ]
2013-04-04T00:00:00
[ [ "Reddy", "Vikas", "" ], [ "Sanderson", "Conrad", "" ], [ "Lovell", "Brian C.", "" ] ]
TITLE: Improved Anomaly Detection in Crowded Scenes via Cell-based Analysis of Foreground Speed, Size and Texture ABSTRACT: A robust and efficient anomaly detection technique is proposed, capable of dealing with crowded scenes where traditional tracking based approaches tend to fail. Initial foreground segmentati...
1304.0913
Morteza Ansarinia
Ahmad Salahi, Morteza Ansarinia
Predicting Network Attacks Using Ontology-Driven Inference
9 pages
International Journal of Information and Communication Technology (IJICT), Volume 4, Issue 1, 2012
null
null
cs.AI cs.CR cs.NI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Graph knowledge models and ontologies are very powerful modeling and re asoning tools. We propose an effective approach to model network attacks and attack prediction which plays important roles in security management. The goals of this study are: First we model network attacks, their prerequisites and consequences u...
[ { "version": "v1", "created": "Wed, 3 Apr 2013 11:04:38 GMT" } ]
2013-04-04T00:00:00
[ [ "Salahi", "Ahmad", "" ], [ "Ansarinia", "Morteza", "" ] ]
TITLE: Predicting Network Attacks Using Ontology-Driven Inference ABSTRACT: Graph knowledge models and ontologies are very powerful modeling and re asoning tools. We propose an effective approach to model network attacks and attack prediction which plays important roles in security management. The goals of this stu...
1212.0142
Pierre Sermanet
Pierre Sermanet and Koray Kavukcuoglu and Soumith Chintala and Yann LeCun
Pedestrian Detection with Unsupervised Multi-Stage Feature Learning
12 pages
null
null
null
cs.CV cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Pedestrian detection is a problem of considerable practical interest. Adding to the list of successful applications of deep learning methods to vision, we report state-of-the-art and competitive results on all major pedestrian datasets with a convolutional network model. The model uses a few new twists, such as multi...
[ { "version": "v1", "created": "Sat, 1 Dec 2012 18:13:03 GMT" }, { "version": "v2", "created": "Tue, 2 Apr 2013 18:05:46 GMT" } ]
2013-04-03T00:00:00
[ [ "Sermanet", "Pierre", "" ], [ "Kavukcuoglu", "Koray", "" ], [ "Chintala", "Soumith", "" ], [ "LeCun", "Yann", "" ] ]
TITLE: Pedestrian Detection with Unsupervised Multi-Stage Feature Learning ABSTRACT: Pedestrian detection is a problem of considerable practical interest. Adding to the list of successful applications of deep learning methods to vision, we report state-of-the-art and competitive results on all major pedestrian data...
1304.0725
Ashok P
P. Ashok, G.M Kadhar Nawaz, E. Elayaraja, V. Vadivel
Improved Performance of Unsupervised Method by Renovated K-Means
7 pages, to strengthen the k means algorithm
null
null
null
cs.LG cs.CV stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Clustering is a separation of data into groups of similar objects. Every group called cluster consists of objects that are similar to one another and dissimilar to objects of other groups. In this paper, the K-Means algorithm is implemented by three distance functions and to identify the optimal distance function for...
[ { "version": "v1", "created": "Mon, 11 Mar 2013 05:28:06 GMT" } ]
2013-04-03T00:00:00
[ [ "Ashok", "P.", "" ], [ "Nawaz", "G. M Kadhar", "" ], [ "Elayaraja", "E.", "" ], [ "Vadivel", "V.", "" ] ]
TITLE: Improved Performance of Unsupervised Method by Renovated K-Means ABSTRACT: Clustering is a separation of data into groups of similar objects. Every group called cluster consists of objects that are similar to one another and dissimilar to objects of other groups. In this paper, the K-Means algorithm is imple...
1303.7012
Abedelaziz Mohaisen
Abedelaziz Mohaisen and Omar Alrawi
Unveiling Zeus
Accepted to SIMPLEX 2013 (a workshop held in conjunction with WWW 2013)
null
null
null
cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Malware family classification is an age old problem that many Anti-Virus (AV) companies have tackled. There are two common techniques used for classification, signature based and behavior based. Signature based classification uses a common sequence of bytes that appears in the binary code to identify and detect a fam...
[ { "version": "v1", "created": "Thu, 28 Mar 2013 00:11:54 GMT" } ]
2013-03-29T00:00:00
[ [ "Mohaisen", "Abedelaziz", "" ], [ "Alrawi", "Omar", "" ] ]
TITLE: Unveiling Zeus ABSTRACT: Malware family classification is an age old problem that many Anti-Virus (AV) companies have tackled. There are two common techniques used for classification, signature based and behavior based. Signature based classification uses a common sequence of bytes that appears in the binary...
1303.6886
Jordan Raddick
M. Jordan Raddick, Georgia Bracey, Pamela L. Gay, Chris J. Lintott, Carie Cardamone, Phil Murray, Kevin Schawinski, Alexander S. Szalay, Jan Vandenberg
Galaxy Zoo: Motivations of Citizen Scientists
41 pages, including 6 figures and one appendix. In press at Astronomy Education Review
null
null
null
physics.ed-ph astro-ph.CO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Citizen science, in which volunteers work with professional scientists to conduct research, is expanding due to large online datasets. To plan projects, it is important to understand volunteers' motivations for participating. This paper analyzes results from an online survey of nearly 11,000 volunteers in Galaxy Zoo,...
[ { "version": "v1", "created": "Wed, 27 Mar 2013 16:28:51 GMT" } ]
2013-03-28T00:00:00
[ [ "Raddick", "M. Jordan", "" ], [ "Bracey", "Georgia", "" ], [ "Gay", "Pamela L.", "" ], [ "Lintott", "Chris J.", "" ], [ "Cardamone", "Carie", "" ], [ "Murray", "Phil", "" ], [ "Schawinski", "Kevin", "" ],...
TITLE: Galaxy Zoo: Motivations of Citizen Scientists ABSTRACT: Citizen science, in which volunteers work with professional scientists to conduct research, is expanding due to large online datasets. To plan projects, it is important to understand volunteers' motivations for participating. This paper analyzes results...
0812.0146
Vladimir Pestov
Vladimir Pestov
Lower Bounds on Performance of Metric Tree Indexing Schemes for Exact Similarity Search in High Dimensions
21 pages, revised submission to Algorithmica, an improved and extended journal version of the conference paper arXiv:0812.0146v3 [cs.DS], with lower bounds strengthened, and the proof of the main Theorem 4 simplified
Algorithmica 66 (2013), 310-328
null
null
cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Within a mathematically rigorous model, we analyse the curse of dimensionality for deterministic exact similarity search in the context of popular indexing schemes: metric trees. The datasets $X$ are sampled randomly from a domain $\Omega$, equipped with a distance, $\rho$, and an underlying probability distribution,...
[ { "version": "v1", "created": "Sun, 30 Nov 2008 15:17:22 GMT" }, { "version": "v2", "created": "Fri, 20 Aug 2010 03:42:50 GMT" }, { "version": "v3", "created": "Tue, 10 May 2011 16:17:39 GMT" }, { "version": "v4", "created": "Fri, 24 Feb 2012 18:38:50 GMT" } ]
2013-03-27T00:00:00
[ [ "Pestov", "Vladimir", "" ] ]
TITLE: Lower Bounds on Performance of Metric Tree Indexing Schemes for Exact Similarity Search in High Dimensions ABSTRACT: Within a mathematically rigorous model, we analyse the curse of dimensionality for deterministic exact similarity search in the context of popular indexing schemes: metric trees. The dataset...
1006.2761
Yuliang Jin
Yuliang Jin, Dmitrij Turaev, Thomas Weinmaier, Thomas Rattei, Hernan A. Makse
The evolutionary dynamics of protein-protein interaction networks inferred from the reconstruction of ancient networks
null
PLoS ONE 2013, Volume 8, Issue 3, e58134
10.1371/journal.pone.0058134
null
q-bio.MN cond-mat.dis-nn physics.bio-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Cellular functions are based on the complex interplay of proteins, therefore the structure and dynamics of these protein-protein interaction (PPI) networks are the key to the functional understanding of cells. In the last years, large-scale PPI networks of several model organisms were investigated. Methodological imp...
[ { "version": "v1", "created": "Mon, 14 Jun 2010 16:40:39 GMT" }, { "version": "v2", "created": "Tue, 19 Feb 2013 15:36:49 GMT" } ]
2013-03-27T00:00:00
[ [ "Jin", "Yuliang", "" ], [ "Turaev", "Dmitrij", "" ], [ "Weinmaier", "Thomas", "" ], [ "Rattei", "Thomas", "" ], [ "Makse", "Hernan A.", "" ] ]
TITLE: The evolutionary dynamics of protein-protein interaction networks inferred from the reconstruction of ancient networks ABSTRACT: Cellular functions are based on the complex interplay of proteins, therefore the structure and dynamics of these protein-protein interaction (PPI) networks are the key to the fun...
1303.4969
Jeff Jones Dr
Jeff Jones, Andrew Adamatzky
Computation of the Travelling Salesman Problem by a Shrinking Blob
27 Pages, 13 Figures. 25-03-13: Amended typos
null
null
null
cs.ET cs.CG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The Travelling Salesman Problem (TSP) is a well known and challenging combinatorial optimisation problem. Its computational intractability has attracted a number of heuristic approaches to generate satisfactory, if not optimal, candidate solutions. In this paper we demonstrate a simple unconventional computation meth...
[ { "version": "v1", "created": "Wed, 20 Mar 2013 15:36:54 GMT" }, { "version": "v2", "created": "Mon, 25 Mar 2013 17:45:47 GMT" } ]
2013-03-27T00:00:00
[ [ "Jones", "Jeff", "" ], [ "Adamatzky", "Andrew", "" ] ]
TITLE: Computation of the Travelling Salesman Problem by a Shrinking Blob ABSTRACT: The Travelling Salesman Problem (TSP) is a well known and challenging combinatorial optimisation problem. Its computational intractability has attracted a number of heuristic approaches to generate satisfactory, if not optimal, cand...
1303.6271
Marcel Blattner
J\'er\^ome Kunegis, Marcel Blattner, Christine Moser
Preferential Attachment in Online Networks: Measurement and Explanations
10 pages, 5 figures, Accepted for the WebSci'13 Conference, Paris, 2013
null
null
null
physics.soc-ph cs.SI physics.data-an
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We perform an empirical study of the preferential attachment phenomenon in temporal networks and show that on the Web, networks follow a nonlinear preferential attachment model in which the exponent depends on the type of network considered. The classical preferential attachment model for networks by Barab\'asi and A...
[ { "version": "v1", "created": "Sat, 23 Mar 2013 09:23:39 GMT" } ]
2013-03-27T00:00:00
[ [ "Kunegis", "Jérôme", "" ], [ "Blattner", "Marcel", "" ], [ "Moser", "Christine", "" ] ]
TITLE: Preferential Attachment in Online Networks: Measurement and Explanations ABSTRACT: We perform an empirical study of the preferential attachment phenomenon in temporal networks and show that on the Web, networks follow a nonlinear preferential attachment model in which the exponent depends on the type of netw...
1303.6361
Conrad Sanderson
Sandra Mau, Shaokang Chen, Conrad Sanderson, Brian C. Lovell
Video Face Matching using Subset Selection and Clustering of Probabilistic Multi-Region Histograms
null
International Conference of Image and Vision Computing New Zealand (IVCNZ), 2010
10.1109/IVCNZ.2010.6148860
null
cs.CV cs.IR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Balancing computational efficiency with recognition accuracy is one of the major challenges in real-world video-based face recognition. A significant design decision for any such system is whether to process and use all possible faces detected over the video frames, or whether to select only a few "best" faces. This ...
[ { "version": "v1", "created": "Tue, 26 Mar 2013 01:34:42 GMT" } ]
2013-03-27T00:00:00
[ [ "Mau", "Sandra", "" ], [ "Chen", "Shaokang", "" ], [ "Sanderson", "Conrad", "" ], [ "Lovell", "Brian C.", "" ] ]
TITLE: Video Face Matching using Subset Selection and Clustering of Probabilistic Multi-Region Histograms ABSTRACT: Balancing computational efficiency with recognition accuracy is one of the major challenges in real-world video-based face recognition. A significant design decision for any such system is whether t...
1302.5235
Adrien Guille
Adrien Guille, Hakim Hacid, C\'ecile Favre
Predicting the Temporal Dynamics of Information Diffusion in Social Networks
10 pages; (corrected typos)
null
null
ERIC Laboratory Report RI-ERIC-13/001
cs.SI physics.soc-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Online social networks play a major role in the spread of information at very large scale and it becomes essential to provide means to analyse this phenomenon. In this paper we address the issue of predicting the temporal dynamics of the information diffusion process. We develop a graph-based approach built on the as...
[ { "version": "v1", "created": "Thu, 21 Feb 2013 10:06:35 GMT" }, { "version": "v2", "created": "Fri, 1 Mar 2013 10:21:08 GMT" } ]
2013-03-26T00:00:00
[ [ "Guille", "Adrien", "" ], [ "Hacid", "Hakim", "" ], [ "Favre", "Cécile", "" ] ]
TITLE: Predicting the Temporal Dynamics of Information Diffusion in Social Networks ABSTRACT: Online social networks play a major role in the spread of information at very large scale and it becomes essential to provide means to analyse this phenomenon. In this paper we address the issue of predicting the tempora...
1303.5926
Sourish Dasgupta
Sourish Dasgupta, Satish Bhat, Yugyung Lee
STC: Semantic Taxonomical Clustering for Service Category Learning
14 pages
null
null
null
cs.SE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Service discovery is one of the key problems that has been widely researched in the area of Service Oriented Architecture (SOA) based systems. Service category learning is a technique for efficiently facilitating service discovery. Most approaches for service category learning are based on suitable similarity distanc...
[ { "version": "v1", "created": "Sun, 24 Mar 2013 08:30:44 GMT" } ]
2013-03-26T00:00:00
[ [ "Dasgupta", "Sourish", "" ], [ "Bhat", "Satish", "" ], [ "Lee", "Yugyung", "" ] ]
TITLE: STC: Semantic Taxonomical Clustering for Service Category Learning ABSTRACT: Service discovery is one of the key problems that has been widely researched in the area of Service Oriented Architecture (SOA) based systems. Service category learning is a technique for efficiently facilitating service discovery. ...
1303.6021
Conrad Sanderson
Andres Sanin, Conrad Sanderson, Mehrtash T. Harandi, Brian C. Lovell
Spatio-Temporal Covariance Descriptors for Action and Gesture Recognition
null
IEEE Workshop on Applications of Computer Vision, pp. 103-110, 2013
10.1109/WACV.2013.6475006
null
cs.CV cs.HC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We propose a new action and gesture recognition method based on spatio-temporal covariance descriptors and a weighted Riemannian locality preserving projection approach that takes into account the curved space formed by the descriptors. The weighted projection is then exploited during boosting to create a final multi...
[ { "version": "v1", "created": "Mon, 25 Mar 2013 03:16:08 GMT" } ]
2013-03-26T00:00:00
[ [ "Sanin", "Andres", "" ], [ "Sanderson", "Conrad", "" ], [ "Harandi", "Mehrtash T.", "" ], [ "Lovell", "Brian C.", "" ] ]
TITLE: Spatio-Temporal Covariance Descriptors for Action and Gesture Recognition ABSTRACT: We propose a new action and gesture recognition method based on spatio-temporal covariance descriptors and a weighted Riemannian locality preserving projection approach that takes into account the curved space formed by the...
1301.7192
Michael Schreiber
Michael Schreiber
Empirical Evidence for the Relevance of Fractional Scoring in the Calculation of Percentile Rank Scores
10 pages, 4 tables, accepted for publication in Journal of American Society for Information Science and Technology
Journal of the American Society for Information Science and Technology, 64(4), 861-867 (2013)
10.1002/asi.22774
null
cs.DL physics.soc-ph stat.AP
http://creativecommons.org/licenses/by-nc-sa/3.0/
Fractional scoring has been proposed to avoid inconsistencies in the attribution of publications to percentile rank classes. Uncertainties and ambiguities in the evaluation of percentile ranks can be demonstrated most easily with small datasets. But for larger datasets an often large number of papers with the same ci...
[ { "version": "v1", "created": "Wed, 30 Jan 2013 10:49:39 GMT" } ]
2013-03-25T00:00:00
[ [ "Schreiber", "Michael", "" ] ]
TITLE: Empirical Evidence for the Relevance of Fractional Scoring in the Calculation of Percentile Rank Scores ABSTRACT: Fractional scoring has been proposed to avoid inconsistencies in the attribution of publications to percentile rank classes. Uncertainties and ambiguities in the evaluation of percentile ranks ...
1301.3485
Antoine Bordes
Xavier Glorot and Antoine Bordes and Jason Weston and Yoshua Bengio
A Semantic Matching Energy Function for Learning with Multi-relational Data
null
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Large-scale relational learning becomes crucial for handling the huge amounts of structured data generated daily in many application domains ranging from computational biology or information retrieval, to natural language processing. In this paper, we present a new neural network architecture designed to embed multi-...
[ { "version": "v1", "created": "Tue, 15 Jan 2013 20:52:50 GMT" }, { "version": "v2", "created": "Thu, 21 Mar 2013 17:02:48 GMT" } ]
2013-03-22T00:00:00
[ [ "Glorot", "Xavier", "" ], [ "Bordes", "Antoine", "" ], [ "Weston", "Jason", "" ], [ "Bengio", "Yoshua", "" ] ]
TITLE: A Semantic Matching Energy Function for Learning with Multi-relational Data ABSTRACT: Large-scale relational learning becomes crucial for handling the huge amounts of structured data generated daily in many application domains ranging from computational biology or information retrieval, to natural language...
1303.5177
Nabila Shikoun
Nabila Shikoun, Mohamed El Nahas and Samar Kassim
Model Based Framework for Estimating Mutation Rate of Hepatitis C Virus in Egypt
6 pages, 5 figures
null
null
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Hepatitis C virus (HCV) is a widely spread disease all over the world. HCV has very high mutation rate that makes it resistant to antibodies. Modeling HCV to identify the virus mutation process is essential to its detection and predicting its evolution. This paper presents a model based framework for estimating mutat...
[ { "version": "v1", "created": "Thu, 21 Mar 2013 06:49:05 GMT" } ]
2013-03-22T00:00:00
[ [ "Shikoun", "Nabila", "" ], [ "Nahas", "Mohamed El", "" ], [ "Kassim", "Samar", "" ] ]
TITLE: Model Based Framework for Estimating Mutation Rate of Hepatitis C Virus in Egypt ABSTRACT: Hepatitis C virus (HCV) is a widely spread disease all over the world. HCV has very high mutation rate that makes it resistant to antibodies. Modeling HCV to identify the virus mutation process is essential to its de...
1206.5829
Alexandre Bartel
Alexandre Bartel (SnT), Jacques Klein (SnT), Martin Monperrus (INRIA Lille - Nord Europe), Yves Le Traon (SnT)
Automatically Securing Permission-Based Software by Reducing the Attack Surface: An Application to Android
null
null
null
ISBN: 978-2-87971-107-2
cs.CR cs.SE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A common security architecture, called the permission-based security model (used e.g. in Android and Blackberry), entails intrinsic risks. For instance, applications can be granted more permissions than they actually need, what we call a "permission gap". Malware can leverage the unused permissions for achieving thei...
[ { "version": "v1", "created": "Tue, 22 May 2012 13:58:03 GMT" }, { "version": "v2", "created": "Wed, 20 Mar 2013 19:43:56 GMT" } ]
2013-03-21T00:00:00
[ [ "Bartel", "Alexandre", "", "SnT" ], [ "Klein", "Jacques", "", "SnT" ], [ "Monperrus", "Martin", "", "INRIA\n Lille - Nord Europe" ], [ "Traon", "Yves Le", "", "SnT" ] ]
TITLE: Automatically Securing Permission-Based Software by Reducing the Attack Surface: An Application to Android ABSTRACT: A common security architecture, called the permission-based security model (used e.g. in Android and Blackberry), entails intrinsic risks. For instance, applications can be granted more perm...
1303.4803
Chunhua Shen
Xi Li, Weiming Hu, Chunhua Shen, Zhongfei Zhang, Anthony Dick, Anton van den Hengel
A Survey of Appearance Models in Visual Object Tracking
Appearing in ACM Transactions on Intelligent Systems and Technology, 2013
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Visual object tracking is a significant computer vision task which can be applied to many domains such as visual surveillance, human computer interaction, and video compression. In the literature, researchers have proposed a variety of 2D appearance models. To help readers swiftly learn the recent advances in 2D appe...
[ { "version": "v1", "created": "Wed, 20 Mar 2013 01:08:33 GMT" } ]
2013-03-21T00:00:00
[ [ "Li", "Xi", "" ], [ "Hu", "Weiming", "" ], [ "Shen", "Chunhua", "" ], [ "Zhang", "Zhongfei", "" ], [ "Dick", "Anthony", "" ], [ "Hengel", "Anton van den", "" ] ]
TITLE: A Survey of Appearance Models in Visual Object Tracking ABSTRACT: Visual object tracking is a significant computer vision task which can be applied to many domains such as visual surveillance, human computer interaction, and video compression. In the literature, researchers have proposed a variety of 2D appe...
1303.4994
Albert Wegener
Albert Wegener
Universal Numerical Encoder and Profiler Reduces Computing's Memory Wall with Software, FPGA, and SoC Implementations
10 pages, 4 figures, 3 tables, 19 references
null
null
null
cs.OH
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In the multicore era, the time to computational results is increasingly determined by how quickly operands are accessed by cores, rather than by the speed of computation per operand. From high-performance computing (HPC) to mobile application processors, low multicore utilization rates result from the slowness of acc...
[ { "version": "v1", "created": "Wed, 20 Mar 2013 17:11:12 GMT" } ]
2013-03-21T00:00:00
[ [ "Wegener", "Albert", "" ] ]
TITLE: Universal Numerical Encoder and Profiler Reduces Computing's Memory Wall with Software, FPGA, and SoC Implementations ABSTRACT: In the multicore era, the time to computational results is increasingly determined by how quickly operands are accessed by cores, rather than by the speed of computation per opera...
1301.3527
Vamsi Potluru
Vamsi K. Potluru, Sergey M. Plis, Jonathan Le Roux, Barak A. Pearlmutter, Vince D. Calhoun, Thomas P. Hayes
Block Coordinate Descent for Sparse NMF
null
null
null
null
cs.LG cs.NA
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Nonnegative matrix factorization (NMF) has become a ubiquitous tool for data analysis. An important variant is the sparse NMF problem which arises when we explicitly require the learnt features to be sparse. A natural measure of sparsity is the L$_0$ norm, however its optimization is NP-hard. Mixed norms, such as L$_...
[ { "version": "v1", "created": "Tue, 15 Jan 2013 23:11:05 GMT" }, { "version": "v2", "created": "Mon, 18 Mar 2013 22:42:11 GMT" } ]
2013-03-20T00:00:00
[ [ "Potluru", "Vamsi K.", "" ], [ "Plis", "Sergey M.", "" ], [ "Roux", "Jonathan Le", "" ], [ "Pearlmutter", "Barak A.", "" ], [ "Calhoun", "Vince D.", "" ], [ "Hayes", "Thomas P.", "" ] ]
TITLE: Block Coordinate Descent for Sparse NMF ABSTRACT: Nonnegative matrix factorization (NMF) has become a ubiquitous tool for data analysis. An important variant is the sparse NMF problem which arises when we explicitly require the learnt features to be sparse. A natural measure of sparsity is the L$_0$ norm, ho...
1303.4402
Julian McAuley
Julian McAuley and Jure Leskovec
From Amateurs to Connoisseurs: Modeling the Evolution of User Expertise through Online Reviews
11 pages, 7 figures
null
null
null
cs.SI cs.IR physics.soc-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recommending products to consumers means not only understanding their tastes, but also understanding their level of experience. For example, it would be a mistake to recommend the iconic film Seven Samurai simply because a user enjoys other action movies; rather, we might conclude that they will eventually enjoy it -...
[ { "version": "v1", "created": "Mon, 18 Mar 2013 20:01:19 GMT" } ]
2013-03-20T00:00:00
[ [ "McAuley", "Julian", "" ], [ "Leskovec", "Jure", "" ] ]
TITLE: From Amateurs to Connoisseurs: Modeling the Evolution of User Expertise through Online Reviews ABSTRACT: Recommending products to consumers means not only understanding their tastes, but also understanding their level of experience. For example, it would be a mistake to recommend the iconic film Seven Samu...
1303.4614
Santosh K.C.
Abdel Bela\"id (LORIA), K.C. Santosh (LORIA), Vincent Poulain D'Andecy
Handwritten and Printed Text Separation in Real Document
Machine Vision Applications (2013)
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The aim of the paper is to separate handwritten and printed text from a real document embedded with noise, graphics including annotations. Relying on run-length smoothing algorithm (RLSA), the extracted pseudo-lines and pseudo-words are used as basic blocks for classification. To handle this, a multi-class support ve...
[ { "version": "v1", "created": "Tue, 19 Mar 2013 14:23:24 GMT" } ]
2013-03-20T00:00:00
[ [ "Belaïd", "Abdel", "", "LORIA" ], [ "Santosh", "K. C.", "", "LORIA" ], [ "D'Andecy", "Vincent Poulain", "" ] ]
TITLE: Handwritten and Printed Text Separation in Real Document ABSTRACT: The aim of the paper is to separate handwritten and printed text from a real document embedded with noise, graphics including annotations. Relying on run-length smoothing algorithm (RLSA), the extracted pseudo-lines and pseudo-words are used ...
1303.3664
Weicong Ding
Weicong Ding, Mohammad H. Rohban, Prakash Ishwar, Venkatesh Saligrama
Topic Discovery through Data Dependent and Random Projections
null
null
null
null
stat.ML cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present algorithms for topic modeling based on the geometry of cross-document word-frequency patterns. This perspective gains significance under the so called separability condition. This is a condition on existence of novel-words that are unique to each topic. We present a suite of highly efficient algorithms bas...
[ { "version": "v1", "created": "Fri, 15 Mar 2013 02:37:19 GMT" }, { "version": "v2", "created": "Mon, 18 Mar 2013 13:11:02 GMT" } ]
2013-03-19T00:00:00
[ [ "Ding", "Weicong", "" ], [ "Rohban", "Mohammad H.", "" ], [ "Ishwar", "Prakash", "" ], [ "Saligrama", "Venkatesh", "" ] ]
TITLE: Topic Discovery through Data Dependent and Random Projections ABSTRACT: We present algorithms for topic modeling based on the geometry of cross-document word-frequency patterns. This perspective gains significance under the so called separability condition. This is a condition on existence of novel-words tha...
1303.4087
Rafi Muhammad
Muhammad Rafi, Mohammad Shahid Shaikh
An improved semantic similarity measure for document clustering based on topic maps
5 pages
null
null
null
cs.IR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A major computational burden, while performing document clustering, is the calculation of similarity measure between a pair of documents. Similarity measure is a function that assigns a real number between 0 and 1 to a pair of documents, depending upon the degree of similarity between them. A value of zero means that...
[ { "version": "v1", "created": "Sun, 17 Mar 2013 18:28:02 GMT" } ]
2013-03-19T00:00:00
[ [ "Rafi", "Muhammad", "" ], [ "Shaikh", "Mohammad Shahid", "" ] ]
TITLE: An improved semantic similarity measure for document clustering based on topic maps ABSTRACT: A major computational burden, while performing document clustering, is the calculation of similarity measure between a pair of documents. Similarity measure is a function that assigns a real number between 0 and 1...
1303.4160
Conrad Sanderson
Vikas Reddy, Conrad Sanderson, Brian C. Lovell
Improved Foreground Detection via Block-based Classifier Cascade with Probabilistic Decision Integration
null
IEEE Transactions on Circuits and Systems for Video Technology, Vol. 23, No. 1, pp. 83-93, 2013
10.1109/TCSVT.2012.2203199
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Background subtraction is a fundamental low-level processing task in numerous computer vision applications. The vast majority of algorithms process images on a pixel-by-pixel basis, where an independent decision is made for each pixel. A general limitation of such processing is that rich contextual information is not...
[ { "version": "v1", "created": "Mon, 18 Mar 2013 05:48:40 GMT" } ]
2013-03-19T00:00:00
[ [ "Reddy", "Vikas", "" ], [ "Sanderson", "Conrad", "" ], [ "Lovell", "Brian C.", "" ] ]
TITLE: Improved Foreground Detection via Block-based Classifier Cascade with Probabilistic Decision Integration ABSTRACT: Background subtraction is a fundamental low-level processing task in numerous computer vision applications. The vast majority of algorithms process images on a pixel-by-pixel basis, where an i...
1301.3583
Yann Dauphin
Yann N. Dauphin, Yoshua Bengio
Big Neural Networks Waste Capacity
null
null
null
null
cs.LG cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This article exposes the failure of some big neural networks to leverage added capacity to reduce underfitting. Past research suggest diminishing returns when increasing the size of neural networks. Our experiments on ImageNet LSVRC-2010 show that this may be due to the fact there are highly diminishing returns for c...
[ { "version": "v1", "created": "Wed, 16 Jan 2013 04:45:29 GMT" }, { "version": "v2", "created": "Thu, 17 Jan 2013 18:11:34 GMT" }, { "version": "v3", "created": "Wed, 27 Feb 2013 23:07:05 GMT" }, { "version": "v4", "created": "Thu, 14 Mar 2013 20:49:20 GMT" } ]
2013-03-18T00:00:00
[ [ "Dauphin", "Yann N.", "" ], [ "Bengio", "Yoshua", "" ] ]
TITLE: Big Neural Networks Waste Capacity ABSTRACT: This article exposes the failure of some big neural networks to leverage added capacity to reduce underfitting. Past research suggest diminishing returns when increasing the size of neural networks. Our experiments on ImageNet LSVRC-2010 show that this may be due ...
1303.3751
Michael (Micky) Fire
Michael Fire, Dima Kagan, Aviad Elyashar, and Yuval Elovici
Friend or Foe? Fake Profile Identification in Online Social Networks
Draft Version
null
null
null
cs.SI physics.soc-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The amount of personal information unwillingly exposed by users on online social networks is staggering, as shown in recent research. Moreover, recent reports indicate that these networks are infested with tens of millions of fake users profiles, which may jeopardize the users' security and privacy. To identify fake ...
[ { "version": "v1", "created": "Fri, 15 Mar 2013 12:17:10 GMT" } ]
2013-03-18T00:00:00
[ [ "Fire", "Michael", "" ], [ "Kagan", "Dima", "" ], [ "Elyashar", "Aviad", "" ], [ "Elovici", "Yuval", "" ] ]
TITLE: Friend or Foe? Fake Profile Identification in Online Social Networks ABSTRACT: The amount of personal information unwillingly exposed by users on online social networks is staggering, as shown in recent research. Moreover, recent reports indicate that these networks are infested with tens of millions of fake...
1301.2820
Eugenio Culurciello Eugenio Culurciello
Eugenio Culurciello, Jordan Bates, Aysegul Dundar, Jose Carrasco, Clement Farabet
Clustering Learning for Robotic Vision
Code for this paper is available here: https://github.com/culurciello/CL_paper1_code
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present the clustering learning technique applied to multi-layer feedforward deep neural networks. We show that this unsupervised learning technique can compute network filters with only a few minutes and a much reduced set of parameters. The goal of this paper is to promote the technique for general-purpose robot...
[ { "version": "v1", "created": "Sun, 13 Jan 2013 20:49:30 GMT" }, { "version": "v2", "created": "Wed, 23 Jan 2013 14:53:21 GMT" }, { "version": "v3", "created": "Wed, 13 Mar 2013 22:48:38 GMT" } ]
2013-03-15T00:00:00
[ [ "Culurciello", "Eugenio", "" ], [ "Bates", "Jordan", "" ], [ "Dundar", "Aysegul", "" ], [ "Carrasco", "Jose", "" ], [ "Farabet", "Clement", "" ] ]
TITLE: Clustering Learning for Robotic Vision ABSTRACT: We present the clustering learning technique applied to multi-layer feedforward deep neural networks. We show that this unsupervised learning technique can compute network filters with only a few minutes and a much reduced set of parameters. The goal of this p...
1301.3572
Camille Couprie
Camille Couprie, Cl\'ement Farabet, Laurent Najman and Yann LeCun
Indoor Semantic Segmentation using depth information
8 pages, 3 figures
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This work addresses multi-class segmentation of indoor scenes with RGB-D inputs. While this area of research has gained much attention recently, most works still rely on hand-crafted features. In contrast, we apply a multiscale convolutional network to learn features directly from the images and the depth information...
[ { "version": "v1", "created": "Wed, 16 Jan 2013 03:31:30 GMT" }, { "version": "v2", "created": "Thu, 14 Mar 2013 18:18:17 GMT" } ]
2013-03-15T00:00:00
[ [ "Couprie", "Camille", "" ], [ "Farabet", "Clément", "" ], [ "Najman", "Laurent", "" ], [ "LeCun", "Yann", "" ] ]
TITLE: Indoor Semantic Segmentation using depth information ABSTRACT: This work addresses multi-class segmentation of indoor scenes with RGB-D inputs. While this area of research has gained much attention recently, most works still rely on hand-crafted features. In contrast, we apply a multiscale convolutional netw...
1303.3517
Yingyi Bu Yingyi Bu
Joshua Rosen, Neoklis Polyzotis, Vinayak Borkar, Yingyi Bu, Michael J. Carey, Markus Weimer, Tyson Condie, Raghu Ramakrishnan
Iterative MapReduce for Large Scale Machine Learning
null
null
null
null
cs.DC cs.DB cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Large datasets ("Big Data") are becoming ubiquitous because the potential value in deriving insights from data, across a wide range of business and scientific applications, is increasingly recognized. In particular, machine learning - one of the foundational disciplines for data analysis, summarization and inference ...
[ { "version": "v1", "created": "Wed, 13 Mar 2013 04:24:12 GMT" } ]
2013-03-15T00:00:00
[ [ "Rosen", "Joshua", "" ], [ "Polyzotis", "Neoklis", "" ], [ "Borkar", "Vinayak", "" ], [ "Bu", "Yingyi", "" ], [ "Carey", "Michael J.", "" ], [ "Weimer", "Markus", "" ], [ "Condie", "Tyson", "" ], [ ...
TITLE: Iterative MapReduce for Large Scale Machine Learning ABSTRACT: Large datasets ("Big Data") are becoming ubiquitous because the potential value in deriving insights from data, across a wide range of business and scientific applications, is increasingly recognized. In particular, machine learning - one of the ...
1303.3164
Uma Sawant
Uma Sawant and Soumen Chakrabarti
Features and Aggregators for Web-scale Entity Search
10 pages, 12 figures including tables
null
null
null
cs.IR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We focus on two research issues in entity search: scoring a document or snippet that potentially supports a candidate entity, and aggregating scores from different snippets into an entity score. Proximity scoring has been studied in IR outside the scope of entity search. However, aggregation has been hardwired except...
[ { "version": "v1", "created": "Wed, 13 Mar 2013 14:06:49 GMT" } ]
2013-03-14T00:00:00
[ [ "Sawant", "Uma", "" ], [ "Chakrabarti", "Soumen", "" ] ]
TITLE: Features and Aggregators for Web-scale Entity Search ABSTRACT: We focus on two research issues in entity search: scoring a document or snippet that potentially supports a candidate entity, and aggregating scores from different snippets into an entity score. Proximity scoring has been studied in IR outside th...
1303.2751
Togerchety Hitendra sarma
Mallikarjun Hangarge
Gaussian Mixture Model for Handwritten Script Identification
Appeared in ICECIT-2012
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper presents a Gaussian Mixture Model (GMM) to identify the script of handwritten words of Roman, Devanagari, Kannada and Telugu scripts. It emphasizes the significance of directional energies for identification of script of the word. It is robust to varied image sizes and different styles of writing. A GMM is...
[ { "version": "v1", "created": "Tue, 12 Mar 2013 02:32:02 GMT" } ]
2013-03-13T00:00:00
[ [ "Hangarge", "Mallikarjun", "" ] ]
TITLE: Gaussian Mixture Model for Handwritten Script Identification ABSTRACT: This paper presents a Gaussian Mixture Model (GMM) to identify the script of handwritten words of Roman, Devanagari, Kannada and Telugu scripts. It emphasizes the significance of directional energies for identification of script of the wo...
1303.2783
Conrad Sanderson
Conrad Sanderson, Mehrtash T. Harandi, Yongkang Wong, Brian C. Lovell
Combined Learning of Salient Local Descriptors and Distance Metrics for Image Set Face Verification
null
IEEE International Conference on Advanced Video and Signal-Based Surveillance (AVSS), pp, 294-299, 2012
10.1109/AVSS.2012.23
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In contrast to comparing faces via single exemplars, matching sets of face images increases robustness and discrimination performance. Recent image set matching approaches typically measure similarities between subspaces or manifolds, while representing faces in a rigid and holistic manner. Such representations are e...
[ { "version": "v1", "created": "Tue, 12 Mar 2013 06:12:59 GMT" } ]
2013-03-13T00:00:00
[ [ "Sanderson", "Conrad", "" ], [ "Harandi", "Mehrtash T.", "" ], [ "Wong", "Yongkang", "" ], [ "Lovell", "Brian C.", "" ] ]
TITLE: Combined Learning of Salient Local Descriptors and Distance Metrics for Image Set Face Verification ABSTRACT: In contrast to comparing faces via single exemplars, matching sets of face images increases robustness and discrimination performance. Recent image set matching approaches typically measure similar...
1209.2178
Sutanay Choudhury
Sutanay Choudhury, Lawrence B. Holder, Abhik Ray, George Chin Jr., John T. Feo
Continuous Queries for Multi-Relational Graphs
Withdrawn because for information disclosure considerations
null
null
PNNL-SA-90326
cs.DB cs.SI
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": "Mon, 10 Sep 2012 23:23:16 GMT" }, { "version": "v2", "created": "Sat, 9 Mar 2013 00:28:38 GMT" } ]
2013-03-12T00:00:00
[ [ "Choudhury", "Sutanay", "" ], [ "Holder", "Lawrence B.", "" ], [ "Ray", "Abhik", "" ], [ "Chin", "George", "Jr." ], [ "Feo", "John T.", "" ] ]
TITLE: Continuous Queries for 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 that...
1302.6556
Theodoros Rekatsinas
Theodoros Rekatsinas, Amol Deshpande, Ashwin Machanavajjhala
On Sharing Private Data with Multiple Non-Colluding Adversaries
14 pages, 6 figures, 2 tables
null
null
null
cs.DB
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present SPARSI, a theoretical framework for partitioning sensitive data across multiple non-colluding adversaries. Most work in privacy-aware data sharing has considered disclosing summaries where the aggregate information about the data is preserved, but sensitive user information is protected. Nonetheless, there...
[ { "version": "v1", "created": "Tue, 26 Feb 2013 19:49:55 GMT" }, { "version": "v2", "created": "Thu, 28 Feb 2013 20:48:52 GMT" }, { "version": "v3", "created": "Mon, 11 Mar 2013 15:41:40 GMT" } ]
2013-03-12T00:00:00
[ [ "Rekatsinas", "Theodoros", "" ], [ "Deshpande", "Amol", "" ], [ "Machanavajjhala", "Ashwin", "" ] ]
TITLE: On Sharing Private Data with Multiple Non-Colluding Adversaries ABSTRACT: We present SPARSI, a theoretical framework for partitioning sensitive data across multiple non-colluding adversaries. Most work in privacy-aware data sharing has considered disclosing summaries where the aggregate information about the...
1303.0045
Bogdan State
Bogdan State, Patrick Park, Ingmar Weber, Yelena Mejova, Michael Macy
The Mesh of Civilizations and International Email Flows
10 pages, 3 figures
null
null
null
cs.SI physics.soc-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In The Clash of Civilizations, Samuel Huntington argued that the primary axis of global conflict was no longer ideological or economic but cultural and religious, and that this division would characterize the "battle lines of the future." In contrast to the "top down" approach in previous research focused on the rela...
[ { "version": "v1", "created": "Thu, 28 Feb 2013 23:29:11 GMT" }, { "version": "v2", "created": "Sun, 10 Mar 2013 19:15:12 GMT" } ]
2013-03-12T00:00:00
[ [ "State", "Bogdan", "" ], [ "Park", "Patrick", "" ], [ "Weber", "Ingmar", "" ], [ "Mejova", "Yelena", "" ], [ "Macy", "Michael", "" ] ]
TITLE: The Mesh of Civilizations and International Email Flows ABSTRACT: In The Clash of Civilizations, Samuel Huntington argued that the primary axis of global conflict was no longer ideological or economic but cultural and religious, and that this division would characterize the "battle lines of the future." In c...
1303.2277
Guilherme de Castro Mendes Gomes
Guilherme de Castro Mendes Gomes, Vitor Campos de Oliveira, Jussara Marques de Almeida and Marcos Andr\'e Gon\c{c}alves
Is Learning to Rank Worth It? A Statistical Analysis of Learning to Rank Methods
7 pages, 10 tables, 14 references. Original (short) paper published in the Brazilian Symposium on Databases, 2012 (SBBD2012). Current revision submitted to the Journal of Information and Data Management (JIDM)
null
null
null
cs.IR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The Learning to Rank (L2R) research field has experienced a fast paced growth over the last few years, with a wide variety of benchmark datasets and baselines available for experimentation. We here investigate the main assumption behind this field, which is that, the use of sophisticated L2R algorithms and models, pr...
[ { "version": "v1", "created": "Sat, 9 Mar 2013 23:28:16 GMT" } ]
2013-03-12T00:00:00
[ [ "Gomes", "Guilherme de Castro Mendes", "" ], [ "de Oliveira", "Vitor Campos", "" ], [ "de Almeida", "Jussara Marques", "" ], [ "Gonçalves", "Marcos André", "" ] ]
TITLE: Is Learning to Rank Worth It? A Statistical Analysis of Learning to Rank Methods ABSTRACT: The Learning to Rank (L2R) research field has experienced a fast paced growth over the last few years, with a wide variety of benchmark datasets and baselines available for experimentation. We here investigate the ma...
1303.2465
Conrad Sanderson
Vikas Reddy, Conrad Sanderson, Brian C. Lovell
A Low-Complexity Algorithm for Static Background Estimation from Cluttered Image Sequences in Surveillance Contexts
null
EURASIP Journal on Image and Video Processing, 2011
10.1155/2011/164956
null
cs.CV
http://creativecommons.org/licenses/by/3.0/
For the purposes of foreground estimation, the true background model is unavailable in many practical circumstances and needs to be estimated from cluttered image sequences. We propose a sequential technique for static background estimation in such conditions, with low computational and memory requirements. Image seq...
[ { "version": "v1", "created": "Mon, 11 Mar 2013 09:57:49 GMT" } ]
2013-03-12T00:00:00
[ [ "Reddy", "Vikas", "" ], [ "Sanderson", "Conrad", "" ], [ "Lovell", "Brian C.", "" ] ]
TITLE: A Low-Complexity Algorithm for Static Background Estimation from Cluttered Image Sequences in Surveillance Contexts ABSTRACT: For the purposes of foreground estimation, the true background model is unavailable in many practical circumstances and needs to be estimated from cluttered image sequences. We prop...
1303.2593
Adeel Ansari
Adeel Ansari, Afza Bt Shafie, Abas B Md Said, Seema Ansari
Independent Component Analysis for Filtering Airwaves in Seabed Logging Application
7 pages, 13 figures
International Journal of Advanced Studies in Computers, Science and Engineering (IJASCSE), 2013
null
null
cs.OH physics.geo-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Marine controlled source electromagnetic (CSEM) sensing method used for the detection of hydrocarbons based reservoirs in seabed logging application does not perform well due to the presence of the airwaves (or sea-surface). These airwaves interfere with the signal that comes from the subsurface seafloor and also ten...
[ { "version": "v1", "created": "Mon, 4 Mar 2013 16:18:51 GMT" } ]
2013-03-12T00:00:00
[ [ "Ansari", "Adeel", "" ], [ "Shafie", "Afza Bt", "" ], [ "Said", "Abas B Md", "" ], [ "Ansari", "Seema", "" ] ]
TITLE: Independent Component Analysis for Filtering Airwaves in Seabed Logging Application ABSTRACT: Marine controlled source electromagnetic (CSEM) sensing method used for the detection of hydrocarbons based reservoirs in seabed logging application does not perform well due to the presence of the airwaves (or se...
1208.3719
Chris Thornton
Chris Thornton and Frank Hutter and Holger H. Hoos and Kevin Leyton-Brown
Auto-WEKA: Combined Selection and Hyperparameter Optimization of Classification Algorithms
9 pages, 3 figures
null
null
Technical Report TR-2012-05
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Many different machine learning algorithms exist; taking into account each algorithm's hyperparameters, there is a staggeringly large number of possible alternatives overall. We consider the problem of simultaneously selecting a learning algorithm and setting its hyperparameters, going beyond previous work that addre...
[ { "version": "v1", "created": "Sat, 18 Aug 2012 02:14:47 GMT" }, { "version": "v2", "created": "Wed, 6 Mar 2013 23:27:04 GMT" } ]
2013-03-08T00:00:00
[ [ "Thornton", "Chris", "" ], [ "Hutter", "Frank", "" ], [ "Hoos", "Holger H.", "" ], [ "Leyton-Brown", "Kevin", "" ] ]
TITLE: Auto-WEKA: Combined Selection and Hyperparameter Optimization of Classification Algorithms ABSTRACT: Many different machine learning algorithms exist; taking into account each algorithm's hyperparameters, there is a staggeringly large number of possible alternatives overall. We consider the problem of simu...
1303.1585
Swaminathan Sankararaman
Swaminathan Sankararaman, Pankaj K. Agarwal, Thomas M{\o}lhave, Arnold P. Boedihardjo
Computing Similarity between a Pair of Trajectories
null
null
null
null
cs.CG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
With recent advances in sensing and tracking technology, trajectory data is becoming increasingly pervasive and analysis of trajectory data is becoming exceedingly important. A fundamental problem in analyzing trajectory data is that of identifying common patterns between pairs or among groups of trajectories. In thi...
[ { "version": "v1", "created": "Thu, 7 Mar 2013 01:37:22 GMT" } ]
2013-03-08T00:00:00
[ [ "Sankararaman", "Swaminathan", "" ], [ "Agarwal", "Pankaj K.", "" ], [ "Mølhave", "Thomas", "" ], [ "Boedihardjo", "Arnold P.", "" ] ]
TITLE: Computing Similarity between a Pair of Trajectories ABSTRACT: With recent advances in sensing and tracking technology, trajectory data is becoming increasingly pervasive and analysis of trajectory data is becoming exceedingly important. A fundamental problem in analyzing trajectory data is that of identifyin...
1303.1741
Emilio Ferrara
Pasquale De Meo, Emilio Ferrara, Giacomo Fiumara, Alessandro Provetti
Enhancing community detection using a network weighting strategy
28 pages, 2 figures
Information Sciences, 222:648-668, 2013
10.1016/j.ins.2012.08.001
null
cs.SI cs.DS physics.soc-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A community within a network is a group of vertices densely connected to each other but less connected to the vertices outside. The problem of detecting communities in large networks plays a key role in a wide range of research areas, e.g. Computer Science, Biology and Sociology. Most of the existing algorithms to fi...
[ { "version": "v1", "created": "Thu, 7 Mar 2013 16:43:30 GMT" } ]
2013-03-08T00:00:00
[ [ "De Meo", "Pasquale", "" ], [ "Ferrara", "Emilio", "" ], [ "Fiumara", "Giacomo", "" ], [ "Provetti", "Alessandro", "" ] ]
TITLE: Enhancing community detection using a network weighting strategy ABSTRACT: A community within a network is a group of vertices densely connected to each other but less connected to the vertices outside. The problem of detecting communities in large networks plays a key role in a wide range of research areas,...
1303.1747
Emilio Ferrara
Pasquale De Meo, Emilio Ferrara, Giacomo Fiumara, Angela Ricciardello
A Novel Measure of Edge Centrality in Social Networks
28 pages, 5 figures
Knowledge-based Systems, 30:136-150, 2012
10.1016/j.knosys.2012.01.007
null
cs.SI cs.DS physics.soc-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The problem of assigning centrality values to nodes and edges in graphs has been widely investigated during last years. Recently, a novel measure of node centrality has been proposed, called k-path centrality index, which is based on the propagation of messages inside a network along paths consisting of at most k edg...
[ { "version": "v1", "created": "Thu, 7 Mar 2013 16:54:34 GMT" } ]
2013-03-08T00:00:00
[ [ "De Meo", "Pasquale", "" ], [ "Ferrara", "Emilio", "" ], [ "Fiumara", "Giacomo", "" ], [ "Ricciardello", "Angela", "" ] ]
TITLE: A Novel Measure of Edge Centrality in Social Networks ABSTRACT: The problem of assigning centrality values to nodes and edges in graphs has been widely investigated during last years. Recently, a novel measure of node centrality has been proposed, called k-path centrality index, which is based on the propaga...
1303.1280
Remi Lajugie
R\'emi Lajugie (LIENS), Sylvain Arlot (LIENS), Francis Bach (LIENS)
Large-Margin Metric Learning for Partitioning Problems
null
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we consider unsupervised partitioning problems, such as clustering, image segmentation, video segmentation and other change-point detection problems. We focus on partitioning problems based explicitly or implicitly on the minimization of Euclidean distortions, which include mean-based change-point dete...
[ { "version": "v1", "created": "Wed, 6 Mar 2013 09:23:45 GMT" } ]
2013-03-07T00:00:00
[ [ "Lajugie", "Rémi", "", "LIENS" ], [ "Arlot", "Sylvain", "", "LIENS" ], [ "Bach", "Francis", "", "LIENS" ] ]
TITLE: Large-Margin Metric Learning for Partitioning Problems ABSTRACT: In this paper, we consider unsupervised partitioning problems, such as clustering, image segmentation, video segmentation and other change-point detection problems. We focus on partitioning problems based explicitly or implicitly on the minimiz...
1103.2068
Tamara Kolda
Justin D. Basilico and M. Arthur Munson and Tamara G. Kolda and Kevin R. Dixon and W. Philip Kegelmeyer
COMET: A Recipe for Learning and Using Large Ensembles on Massive Data
null
ICDM 2011: Proceedings of the 2011 IEEE International Conference on Data Mining, pp. 41-50, 2011
10.1109/ICDM.2011.39
null
cs.LG cs.DC stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
COMET is a single-pass MapReduce algorithm for learning on large-scale data. It builds multiple random forest ensembles on distributed blocks of data and merges them into a mega-ensemble. This approach is appropriate when learning from massive-scale data that is too large to fit on a single machine. To get the best a...
[ { "version": "v1", "created": "Thu, 10 Mar 2011 16:15:42 GMT" }, { "version": "v2", "created": "Thu, 8 Sep 2011 16:20:45 GMT" } ]
2013-03-06T00:00:00
[ [ "Basilico", "Justin D.", "" ], [ "Munson", "M. Arthur", "" ], [ "Kolda", "Tamara G.", "" ], [ "Dixon", "Kevin R.", "" ], [ "Kegelmeyer", "W. Philip", "" ] ]
TITLE: COMET: A Recipe for Learning and Using Large Ensembles on Massive Data ABSTRACT: COMET is a single-pass MapReduce algorithm for learning on large-scale data. It builds multiple random forest ensembles on distributed blocks of data and merges them into a mega-ensemble. This approach is appropriate when learni...
1208.4289
Marcelo Serraro Zanetti
Marcelo Serrano Zanetti, Emre Sarigol, Ingo Scholtes, Claudio Juan Tessone, Frank Schweitzer
A Quantitative Study of Social Organisation in Open Source Software Communities
null
ICCSW 2012, pp. 116--122
10.4230/OASIcs.ICCSW.2012.116
null
cs.SE cs.SI nlin.AO physics.soc-ph
http://creativecommons.org/licenses/by/3.0/
The success of open source projects crucially depends on the voluntary contributions of a sufficiently large community of users. Apart from the mere size of the community, interesting questions arise when looking at the evolution of structural features of collaborations between community members. In this article, we ...
[ { "version": "v1", "created": "Tue, 21 Aug 2012 15:34:35 GMT" }, { "version": "v2", "created": "Tue, 27 Nov 2012 10:55:11 GMT" }, { "version": "v3", "created": "Mon, 4 Mar 2013 13:17:21 GMT" } ]
2013-03-05T00:00:00
[ [ "Zanetti", "Marcelo Serrano", "" ], [ "Sarigol", "Emre", "" ], [ "Scholtes", "Ingo", "" ], [ "Tessone", "Claudio Juan", "" ], [ "Schweitzer", "Frank", "" ] ]
TITLE: A Quantitative Study of Social Organisation in Open Source Software Communities ABSTRACT: The success of open source projects crucially depends on the voluntary contributions of a sufficiently large community of users. Apart from the mere size of the community, interesting questions arise when looking at t...
1301.7015
Entong Shen
Entong Shen, Ting Yu
Mining Frequent Graph Patterns with Differential Privacy
null
null
null
null
cs.DB
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Discovering frequent graph patterns in a graph database offers valuable information in a variety of applications. However, if the graph dataset contains sensitive data of individuals such as mobile phone-call graphs and web-click graphs, releasing discovered frequent patterns may present a threat to the privacy of in...
[ { "version": "v1", "created": "Tue, 29 Jan 2013 18:37:35 GMT" }, { "version": "v2", "created": "Fri, 1 Mar 2013 21:43:20 GMT" } ]
2013-03-05T00:00:00
[ [ "Shen", "Entong", "" ], [ "Yu", "Ting", "" ] ]
TITLE: Mining Frequent Graph Patterns with Differential Privacy ABSTRACT: Discovering frequent graph patterns in a graph database offers valuable information in a variety of applications. However, if the graph dataset contains sensitive data of individuals such as mobile phone-call graphs and web-click graphs, rele...
1303.0339
Chunhua Shen
Xi Li and Guosheng Lin and Chunhua Shen and Anton van den Hengel and Anthony Dick
Learning Hash Functions Using Column Generation
9 pages, published in International Conf. Machine Learning, 2013
null
null
null
cs.LG
http://creativecommons.org/licenses/by/3.0/
Fast nearest neighbor searching is becoming an increasingly important tool in solving many large-scale problems. Recently a number of approaches to learning data-dependent hash functions have been developed. In this work, we propose a column generation based method for learning data-dependent hash functions on the ba...
[ { "version": "v1", "created": "Sat, 2 Mar 2013 03:01:46 GMT" } ]
2013-03-05T00:00:00
[ [ "Li", "Xi", "" ], [ "Lin", "Guosheng", "" ], [ "Shen", "Chunhua", "" ], [ "Hengel", "Anton van den", "" ], [ "Dick", "Anthony", "" ] ]
TITLE: Learning Hash Functions Using Column Generation ABSTRACT: Fast nearest neighbor searching is becoming an increasingly important tool in solving many large-scale problems. Recently a number of approaches to learning data-dependent hash functions have been developed. In this work, we propose a column generatio...
1303.0566
Taher Zaki
T. Zaki (1 and 2), M. Amrouch (1), D. Mammass (1), A. Ennaji (2) ((1) IRFSIC Laboratory, Ibn Zohr University Agadir Morocco, (2) LITIS Laboratory, University of Rouen France)
Arabic documents classification using fuzzy R.B.F. classifier with sliding window
5 pages, 2 figures
Journal of Computing , eISSN 2151-9617 , Volume 5, Issue 1, January 2013
null
null
cs.IR
http://creativecommons.org/licenses/publicdomain/
In this paper, we propose a system for contextual and semantic Arabic documents classification by improving the standard fuzzy model. Indeed, promoting neighborhood semantic terms that seems absent in this model by using a radial basis modeling. In order to identify the relevant documents to the query. This approach ...
[ { "version": "v1", "created": "Sun, 3 Mar 2013 20:50:12 GMT" } ]
2013-03-05T00:00:00
[ [ "Zaki", "T.", "", "1 and 2" ], [ "Amrouch", "M.", "" ], [ "Mammass", "D.", "" ], [ "Ennaji", "A.", "" ] ]
TITLE: Arabic documents classification using fuzzy R.B.F. classifier with sliding window ABSTRACT: In this paper, we propose a system for contextual and semantic Arabic documents classification by improving the standard fuzzy model. Indeed, promoting neighborhood semantic terms that seems absent in this model by ...
1303.0647
Meena Kabilan
A. Meena and R. Raja
Spatial Fuzzy C Means PET Image Segmentation of Neurodegenerative Disorder
null
Indian Journal of Computer Science and Engineering (IJCSE), ISSN : 0976-5166 Vol. 4 No.1 Feb-Mar 2013, pp.no: 50-55
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Nuclear image has emerged as a promising research work in medical field. Images from different modality meet its own challenge. Positron Emission Tomography (PET) image may help to precisely localize disease to assist in planning the right treatment for each case and saving valuable time. In this paper, a novel appro...
[ { "version": "v1", "created": "Mon, 4 Mar 2013 09:08:34 GMT" } ]
2013-03-05T00:00:00
[ [ "Meena", "A.", "" ], [ "Raja", "R.", "" ] ]
TITLE: Spatial Fuzzy C Means PET Image Segmentation of Neurodegenerative Disorder ABSTRACT: Nuclear image has emerged as a promising research work in medical field. Images from different modality meet its own challenge. Positron Emission Tomography (PET) image may help to precisely localize disease to assist in p...
1206.5065
Sofia Zaidenberg
Sofia Zaidenberg (INRIA Sophia Antipolis), Bernard Boulay (INRIA Sophia Antipolis), Fran\c{c}ois Bremond (INRIA Sophia Antipolis)
A generic framework for video understanding applied to group behavior recognition
(20/03/2012)
9th IEEE International Conference on Advanced Video and Signal-Based Surveillance (AVSS 2012) (2012) 136 -142
10.1109/AVSS.2012.1
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper presents an approach to detect and track groups of people in video-surveillance applications, and to automatically recognize their behavior. This method keeps track of individuals moving together by maintaining a spacial and temporal group coherence. First, people are individually detected and tracked. Sec...
[ { "version": "v1", "created": "Fri, 22 Jun 2012 06:24:30 GMT" } ]
2013-03-04T00:00:00
[ [ "Zaidenberg", "Sofia", "", "INRIA Sophia Antipolis" ], [ "Boulay", "Bernard", "", "INRIA\n Sophia Antipolis" ], [ "Bremond", "François", "", "INRIA Sophia Antipolis" ] ]
TITLE: A generic framework for video understanding applied to group behavior recognition ABSTRACT: This paper presents an approach to detect and track groups of people in video-surveillance applications, and to automatically recognize their behavior. This method keeps track of individuals moving together by maint...
1301.5160
Claudio Gentile
Fabio Vitale, Nicolo Cesa-Bianchi, Claudio Gentile, Giovanni Zappella
See the Tree Through the Lines: The Shazoo Algorithm -- Full Version --
null
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Predicting the nodes of a given graph is a fascinating theoretical problem with applications in several domains. Since graph sparsification via spanning trees retains enough information while making the task much easier, trees are an important special case of this problem. Although it is known how to predict the node...
[ { "version": "v1", "created": "Tue, 22 Jan 2013 11:59:04 GMT" }, { "version": "v2", "created": "Thu, 28 Feb 2013 17:31:08 GMT" } ]
2013-03-01T00:00:00
[ [ "Vitale", "Fabio", "" ], [ "Cesa-Bianchi", "Nicolo", "" ], [ "Gentile", "Claudio", "" ], [ "Zappella", "Giovanni", "" ] ]
TITLE: See the Tree Through the Lines: The Shazoo Algorithm -- Full Version -- ABSTRACT: Predicting the nodes of a given graph is a fascinating theoretical problem with applications in several domains. Since graph sparsification via spanning trees retains enough information while making the task much easier, trees ...
1302.7043
Evangelos Papalexakis
Evangelos E. Papalexakis, Tom M. Mitchell, Nicholas D. Sidiropoulos, Christos Faloutsos, Partha Pratim Talukdar, Brian Murphy
Scoup-SMT: Scalable Coupled Sparse Matrix-Tensor Factorization
9 pages
null
null
null
stat.ML cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
How can we correlate neural activity in the human brain as it responds to words, with behavioral data expressed as answers to questions about these same words? In short, we want to find latent variables, that explain both the brain activity, as well as the behavioral responses. We show that this is an instance of the...
[ { "version": "v1", "created": "Thu, 28 Feb 2013 00:37:29 GMT" } ]
2013-03-01T00:00:00
[ [ "Papalexakis", "Evangelos E.", "" ], [ "Mitchell", "Tom M.", "" ], [ "Sidiropoulos", "Nicholas D.", "" ], [ "Faloutsos", "Christos", "" ], [ "Talukdar", "Partha Pratim", "" ], [ "Murphy", "Brian", "" ] ]
TITLE: Scoup-SMT: Scalable Coupled Sparse Matrix-Tensor Factorization ABSTRACT: How can we correlate neural activity in the human brain as it responds to words, with behavioral data expressed as answers to questions about these same words? In short, we want to find latent variables, that explain both the brain acti...
1302.6582
Michael Schreiber
Michael Schreiber
A Case Study of the Arbitrariness of the h-Index and the Highly-Cited-Publications Indicator
16 pages, 3 tables, 5 figures. arXiv admin note: text overlap with arXiv:1302.6396
Journal of Informetrics, 7(2), 379-387 (2013)
10.1016/j.joi.2012.12.006
null
physics.soc-ph cs.DL
http://creativecommons.org/licenses/by-nc-sa/3.0/
The arbitrariness of the h-index becomes evident, when one requires q*h instead of h citations as the threshold for the definition of the index, thus changing the size of the core of the most influential publications of a dataset. I analyze the citation records of 26 physicists in order to determine how much the pref...
[ { "version": "v1", "created": "Tue, 26 Feb 2013 11:49:29 GMT" } ]
2013-02-28T00:00:00
[ [ "Schreiber", "Michael", "" ] ]
TITLE: A Case Study of the Arbitrariness of the h-Index and the Highly-Cited-Publications Indicator ABSTRACT: The arbitrariness of the h-index becomes evident, when one requires q*h instead of h citations as the threshold for the definition of the index, thus changing the size of the core of the most influential ...
1302.6613
Ratnadip Adhikari
Ratnadip Adhikari, R. K. Agrawal
An Introductory Study on Time Series Modeling and Forecasting
67 pages, 29 figures, 33 references, book
LAP Lambert Academic Publishing, Germany, 2013
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Time series modeling and forecasting has fundamental importance to various practical domains. Thus a lot of active research works is going on in this subject during several years. Many important models have been proposed in literature for improving the accuracy and effectiveness of time series forecasting. The aim of...
[ { "version": "v1", "created": "Tue, 26 Feb 2013 22:18:55 GMT" } ]
2013-02-28T00:00:00
[ [ "Adhikari", "Ratnadip", "" ], [ "Agrawal", "R. K.", "" ] ]
TITLE: An Introductory Study on Time Series Modeling and Forecasting ABSTRACT: Time series modeling and forecasting has fundamental importance to various practical domains. Thus a lot of active research works is going on in this subject during several years. Many important models have been proposed in literature fo...
1302.6666
Yan Huang
Yan Huang, Ruoming Jin, Favyen Bastani, Xiaoyang Sean Wang
Large Scale Real-time Ridesharing with Service Guarantee on Road Networks
null
null
null
null
cs.DS
http://creativecommons.org/licenses/by-nc-sa/3.0/
The mean occupancy rates of personal vehicle trips in the United States is only 1.6 persons per vehicle mile. Urban traffic gridlock is a familiar scene. Ridesharing has the potential to solve many environmental, congestion, and energy problems. In this paper, we introduce the problem of large scale real-time ridesha...
[ { "version": "v1", "created": "Wed, 27 Feb 2013 05:41:49 GMT" } ]
2013-02-28T00:00:00
[ [ "Huang", "Yan", "" ], [ "Jin", "Ruoming", "" ], [ "Bastani", "Favyen", "" ], [ "Wang", "Xiaoyang Sean", "" ] ]
TITLE: Large Scale Real-time Ridesharing with Service Guarantee on Road Networks ABSTRACT: The mean occupancy rates of personal vehicle trips in the United States is only 1.6 persons per vehicle mile. Urban traffic gridlock is a familiar scene. Ridesharing has the potential to solve many environmental, congestion...
1302.6957
Jayaraman J. Thiagarajan
Karthikeyan Natesan Ramamurthy, Jayaraman J. Thiagarajan, Prasanna Sattigeri and Andreas Spanias
Ensemble Sparse Models for Image Analysis
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Sparse representations with learned dictionaries have been successful in several image analysis applications. In this paper, we propose and analyze the framework of ensemble sparse models, and demonstrate their utility in image restoration and unsupervised clustering. The proposed ensemble model approximates the data...
[ { "version": "v1", "created": "Wed, 27 Feb 2013 18:58:36 GMT" } ]
2013-02-28T00:00:00
[ [ "Ramamurthy", "Karthikeyan Natesan", "" ], [ "Thiagarajan", "Jayaraman J.", "" ], [ "Sattigeri", "Prasanna", "" ], [ "Spanias", "Andreas", "" ] ]
TITLE: Ensemble Sparse Models for Image Analysis ABSTRACT: Sparse representations with learned dictionaries have been successful in several image analysis applications. In this paper, we propose and analyze the framework of ensemble sparse models, and demonstrate their utility in image restoration and unsupervised ...
1302.6210
Ratnadip Adhikari
Ratnadip Adhikari, R. K. Agrawal
A Homogeneous Ensemble of Artificial Neural Networks for Time Series Forecasting
8 pages, 4 figures, 2 tables, 26 references, international journal
International Journal of Computer Applications, Vol. 32, No. 7, October 2011, pp. 1-8
10.5120/3913-5505
null
cs.NE cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Enhancing the robustness and accuracy of time series forecasting models is an active area of research. Recently, Artificial Neural Networks (ANNs) have found extensive applications in many practical forecasting problems. However, the standard backpropagation ANN training algorithm has some critical issues, e.g. it ha...
[ { "version": "v1", "created": "Mon, 25 Feb 2013 20:09:19 GMT" } ]
2013-02-27T00:00:00
[ [ "Adhikari", "Ratnadip", "" ], [ "Agrawal", "R. K.", "" ] ]
TITLE: A Homogeneous Ensemble of Artificial Neural Networks for Time Series Forecasting ABSTRACT: Enhancing the robustness and accuracy of time series forecasting models is an active area of research. Recently, Artificial Neural Networks (ANNs) have found extensive applications in many practical forecasting probl...
1302.5101
Jeremiah Blocki
Jeremiah Blocki and Saranga Komanduri and Ariel Procaccia and Or Sheffet
Optimizing Password Composition Policies
null
null
null
null
cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A password composition policy restricts the space of allowable passwords to eliminate weak passwords that are vulnerable to statistical guessing attacks. Usability studies have demonstrated that existing password composition policies can sometimes result in weaker password distributions; hence a more principled appro...
[ { "version": "v1", "created": "Wed, 20 Feb 2013 20:53:41 GMT" }, { "version": "v2", "created": "Mon, 25 Feb 2013 19:44:50 GMT" } ]
2013-02-26T00:00:00
[ [ "Blocki", "Jeremiah", "" ], [ "Komanduri", "Saranga", "" ], [ "Procaccia", "Ariel", "" ], [ "Sheffet", "Or", "" ] ]
TITLE: Optimizing Password Composition Policies ABSTRACT: A password composition policy restricts the space of allowable passwords to eliminate weak passwords that are vulnerable to statistical guessing attacks. Usability studies have demonstrated that existing password composition policies can sometimes result in ...
1302.5771
Anil Bhardwaj
Y. Futaana, S. Barabash, M. Wieser, C. Lue, P. Wurz, A. Vorburger, A. Bhardwaj, K. Asamura
Remote Energetic Neutral Atom Imaging of Electric Potential Over a Lunar Magnetic Anomaly
19 pages, 3 figures
Geophys. Res. Lett., 40, doi:10.1002/grl.50135, 2013
10.1002/grl.50135
null
physics.space-ph astro-ph.EP physics.plasm-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The formation of electric potential over lunar magnetized regions is essential for understanding fundamental lunar science, for understanding the lunar environment, and for planning human exploration on the Moon. A large positive electric potential was predicted and detected from single point measurements. Here, we d...
[ { "version": "v1", "created": "Sat, 23 Feb 2013 07:35:28 GMT" } ]
2013-02-26T00:00:00
[ [ "Futaana", "Y.", "" ], [ "Barabash", "S.", "" ], [ "Wieser", "M.", "" ], [ "Lue", "C.", "" ], [ "Wurz", "P.", "" ], [ "Vorburger", "A.", "" ], [ "Bhardwaj", "A.", "" ], [ "Asamura", "K.", ""...
TITLE: Remote Energetic Neutral Atom Imaging of Electric Potential Over a Lunar Magnetic Anomaly ABSTRACT: The formation of electric potential over lunar magnetized regions is essential for understanding fundamental lunar science, for understanding the lunar environment, and for planning human exploration on the ...
1302.5985
Xiaodi Hou
Xiaodi Hou and Alan Yuille and Christof Koch
A Meta-Theory of Boundary Detection Benchmarks
NIPS 2012 Workshop on Human Computation for Science and Computational Sustainability
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Human labeled datasets, along with their corresponding evaluation algorithms, play an important role in boundary detection. We here present a psychophysical experiment that addresses the reliability of such benchmarks. To find better remedies to evaluate the performance of any boundary detection algorithm, we propose...
[ { "version": "v1", "created": "Mon, 25 Feb 2013 03:12:12 GMT" } ]
2013-02-26T00:00:00
[ [ "Hou", "Xiaodi", "" ], [ "Yuille", "Alan", "" ], [ "Koch", "Christof", "" ] ]
TITLE: A Meta-Theory of Boundary Detection Benchmarks ABSTRACT: Human labeled datasets, along with their corresponding evaluation algorithms, play an important role in boundary detection. We here present a psychophysical experiment that addresses the reliability of such benchmarks. To find better remedies to evalua...
1302.6221
Thierry Sousbie
Thierry Sousbie
DisPerSE: robust structure identification in 2D and 3D
To download DisPerSE, go to http://www2.iap.fr/users/sousbie/
null
null
null
astro-ph.CO astro-ph.IM math-ph math.MP physics.comp-ph physics.data-an
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present the DIScrete PERsistent Structures Extractor (DisPerSE), an open source software for the automatic and robust identification of structures in 2D and 3D noisy data sets. The software is designed to identify all sorts of topological structures, such as voids, peaks, sources, walls and filaments through segme...
[ { "version": "v1", "created": "Mon, 25 Feb 2013 20:47:19 GMT" } ]
2013-02-26T00:00:00
[ [ "Sousbie", "Thierry", "" ] ]
TITLE: DisPerSE: robust structure identification in 2D and 3D ABSTRACT: We present the DIScrete PERsistent Structures Extractor (DisPerSE), an open source software for the automatic and robust identification of structures in 2D and 3D noisy data sets. The software is designed to identify all sorts of topological st...
1211.3147
Keke Chen
James Powers and Keke Chen
Secure Computation of Top-K Eigenvectors for Shared Matrices in the Cloud
8 pages
null
null
null
cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
With the development of sensor network, mobile computing, and web applications, data are now collected from many distributed sources to form big datasets. Such datasets can be hosted in the cloud to achieve economical processing. However, these data might be highly sensitive requiring secure storage and processing. W...
[ { "version": "v1", "created": "Tue, 13 Nov 2012 21:59:18 GMT" }, { "version": "v2", "created": "Fri, 22 Feb 2013 05:35:22 GMT" } ]
2013-02-25T00:00:00
[ [ "Powers", "James", "" ], [ "Chen", "Keke", "" ] ]
TITLE: Secure Computation of Top-K Eigenvectors for Shared Matrices in the Cloud ABSTRACT: With the development of sensor network, mobile computing, and web applications, data are now collected from many distributed sources to form big datasets. Such datasets can be hosted in the cloud to achieve economical proce...
1301.3533
Xanadu Halkias
Xanadu Halkias, Sebastien Paris, Herve Glotin
Sparse Penalty in Deep Belief Networks: Using the Mixed Norm Constraint
8 pages, 7 figures (including subfigures), ICleaR conference
null
null
null
cs.NE cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Deep Belief Networks (DBN) have been successfully applied on popular machine learning tasks. Specifically, when applied on hand-written digit recognition, DBNs have achieved approximate accuracy rates of 98.8%. In an effort to optimize the data representation achieved by the DBN and maximize their descriptive power, ...
[ { "version": "v1", "created": "Wed, 16 Jan 2013 00:12:21 GMT" }, { "version": "v2", "created": "Fri, 22 Feb 2013 10:18:15 GMT" } ]
2013-02-25T00:00:00
[ [ "Halkias", "Xanadu", "" ], [ "Paris", "Sebastien", "" ], [ "Glotin", "Herve", "" ] ]
TITLE: Sparse Penalty in Deep Belief Networks: Using the Mixed Norm Constraint ABSTRACT: Deep Belief Networks (DBN) have been successfully applied on popular machine learning tasks. Specifically, when applied on hand-written digit recognition, DBNs have achieved approximate accuracy rates of 98.8%. In an effort to ...
1302.5125
Oren Rippel
Oren Rippel, Ryan Prescott Adams
High-Dimensional Probability Estimation with Deep Density Models
12 pages, 4 figures, 1 table. Submitted for publication
null
null
null
stat.ML cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
One of the fundamental problems in machine learning is the estimation of a probability distribution from data. Many techniques have been proposed to study the structure of data, most often building around the assumption that observations lie on a lower-dimensional manifold of high probability. It has been more diffic...
[ { "version": "v1", "created": "Wed, 20 Feb 2013 21:20:30 GMT" } ]
2013-02-22T00:00:00
[ [ "Rippel", "Oren", "" ], [ "Adams", "Ryan Prescott", "" ] ]
TITLE: High-Dimensional Probability Estimation with Deep Density Models ABSTRACT: One of the fundamental problems in machine learning is the estimation of a probability distribution from data. Many techniques have been proposed to study the structure of data, most often building around the assumption that observati...
1302.5189
Dilip K. Prasad
Dilip K. Prasad
Object Detection in Real Images
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Object detection and recognition are important problems in computer vision. Since these problems are meta-heuristic, despite a lot of research, practically usable, intelligent, real-time, and dynamic object detection/recognition methods are still unavailable. We propose a new object detection/recognition method, whic...
[ { "version": "v1", "created": "Thu, 21 Feb 2013 06:06:47 GMT" } ]
2013-02-22T00:00:00
[ [ "Prasad", "Dilip K.", "" ] ]
TITLE: Object Detection in Real Images ABSTRACT: Object detection and recognition are important problems in computer vision. Since these problems are meta-heuristic, despite a lot of research, practically usable, intelligent, real-time, and dynamic object detection/recognition methods are still unavailable. We prop...
1206.0051
Florin Rusu
Chengjie Qin, Florin Rusu
PF-OLA: A High-Performance Framework for Parallel On-Line Aggregation
36 pages
null
null
null
cs.DB cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Online aggregation provides estimates to the final result of a computation during the actual processing. The user can stop the computation as soon as the estimate is accurate enough, typically early in the execution. This allows for the interactive data exploration of the largest datasets. In this paper we introduce ...
[ { "version": "v1", "created": "Thu, 31 May 2012 23:38:36 GMT" }, { "version": "v2", "created": "Wed, 20 Feb 2013 07:10:04 GMT" } ]
2013-02-21T00:00:00
[ [ "Qin", "Chengjie", "" ], [ "Rusu", "Florin", "" ] ]
TITLE: PF-OLA: A High-Performance Framework for Parallel On-Line Aggregation ABSTRACT: Online aggregation provides estimates to the final result of a computation during the actual processing. The user can stop the computation as soon as the estimate is accurate enough, typically early in the execution. This allows ...
1302.4874
Gon\c{c}alo Sim\~oes
Gon\c{c}alo Sim\~oes, Helena Galhardas, David Matos
A Labeled Graph Kernel for Relationship Extraction
null
null
null
null
cs.CL cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we propose an approach for Relationship Extraction (RE) based on labeled graph kernels. The kernel we propose is a particularization of a random walk kernel that exploits two properties previously studied in the RE literature: (i) the words between the candidate entities or connecting them in a syntact...
[ { "version": "v1", "created": "Wed, 20 Feb 2013 11:06:25 GMT" } ]
2013-02-21T00:00:00
[ [ "Simões", "Gonçalo", "" ], [ "Galhardas", "Helena", "" ], [ "Matos", "David", "" ] ]
TITLE: A Labeled Graph Kernel for Relationship Extraction ABSTRACT: In this paper, we propose an approach for Relationship Extraction (RE) based on labeled graph kernels. The kernel we propose is a particularization of a random walk kernel that exploits two properties previously studied in the RE literature: (i) th...
1302.4932
John S. Breese
John S. Breese, Russ Blake
Automating Computer Bottleneck Detection with Belief Nets
Appears in Proceedings of the Eleventh Conference on Uncertainty in Artificial Intelligence (UAI1995)
null
null
UAI-P-1995-PG-36-45
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We describe an application of belief networks to the diagnosis of bottlenecks in computer systems. The technique relies on a high-level functional model of the interaction between application workloads, the Windows NT operating system, and system hardware. Given a workload description, the model predicts the values o...
[ { "version": "v1", "created": "Wed, 20 Feb 2013 15:19:11 GMT" } ]
2013-02-21T00:00:00
[ [ "Breese", "John S.", "" ], [ "Blake", "Russ", "" ] ]
TITLE: Automating Computer Bottleneck Detection with Belief Nets ABSTRACT: We describe an application of belief networks to the diagnosis of bottlenecks in computer systems. The technique relies on a high-level functional model of the interaction between application workloads, the Windows NT operating system, and s...
1301.0068
Guy Bresler
Guy Bresler, Ma'ayan Bresler, David Tse
Optimal Assembly for High Throughput Shotgun Sequencing
26 pages, 18 figures
null
null
null
q-bio.GN cs.DS cs.IT math.IT q-bio.QM
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present a framework for the design of optimal assembly algorithms for shotgun sequencing under the criterion of complete reconstruction. We derive a lower bound on the read length and the coverage depth required for reconstruction in terms of the repeat statistics of the genome. Building on earlier works, we desig...
[ { "version": "v1", "created": "Tue, 1 Jan 2013 08:52:44 GMT" }, { "version": "v2", "created": "Wed, 9 Jan 2013 03:51:20 GMT" }, { "version": "v3", "created": "Mon, 18 Feb 2013 17:41:09 GMT" } ]
2013-02-20T00:00:00
[ [ "Bresler", "Guy", "" ], [ "Bresler", "Ma'ayan", "" ], [ "Tse", "David", "" ] ]
TITLE: Optimal Assembly for High Throughput Shotgun Sequencing ABSTRACT: We present a framework for the design of optimal assembly algorithms for shotgun sequencing under the criterion of complete reconstruction. We derive a lower bound on the read length and the coverage depth required for reconstruction in terms ...
1302.4504
Diego Amancio Raphael
Diego R. Amancio, Osvaldo N. Oliveira Jr. and Luciano da F. Costa
On the use of topological features and hierarchical characterization for disambiguating names in collaborative networks
null
Europhysics Letters (2012) 99 48002
10.1209/0295-5075/99/48002
null
physics.soc-ph cs.DL cs.IR cs.SI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Many features of complex systems can now be unveiled by applying statistical physics methods to treat them as social networks. The power of the analysis may be limited, however, by the presence of ambiguity in names, e.g., caused by homonymy in collaborative networks. In this paper we show that the ability to disting...
[ { "version": "v1", "created": "Tue, 19 Feb 2013 02:00:01 GMT" } ]
2013-02-20T00:00:00
[ [ "Amancio", "Diego R.", "" ], [ "Oliveira", "Osvaldo N.", "Jr." ], [ "Costa", "Luciano da F.", "" ] ]
TITLE: On the use of topological features and hierarchical characterization for disambiguating names in collaborative networks ABSTRACT: Many features of complex systems can now be unveiled by applying statistical physics methods to treat them as social networks. The power of the analysis may be limited, however,...
1302.4680
Gregory Newstadt
Gregory E. Newstadt, Edmund G. Zelnio, and Alfred O. Hero III
Moving target inference with hierarchical Bayesian models in synthetic aperture radar imagery
35 pages, 8 figures, 1 algorithm, 11 tables
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In synthetic aperture radar (SAR), images are formed by focusing the response of stationary objects to a single spatial location. On the other hand, moving targets cause phase errors in the standard formation of SAR images that cause displacement and defocusing effects. SAR imagery also contains significant sources o...
[ { "version": "v1", "created": "Tue, 19 Feb 2013 17:12:53 GMT" } ]
2013-02-20T00:00:00
[ [ "Newstadt", "Gregory E.", "" ], [ "Zelnio", "Edmund G.", "" ], [ "Hero", "Alfred O.", "III" ] ]
TITLE: Moving target inference with hierarchical Bayesian models in synthetic aperture radar imagery ABSTRACT: In synthetic aperture radar (SAR), images are formed by focusing the response of stationary objects to a single spatial location. On the other hand, moving targets cause phase errors in the standard form...
1301.5809
Derek Greene
Derek Greene and P\'adraig Cunningham
Producing a Unified Graph Representation from Multiple Social Network Views
13 pages. Clarify notation
null
null
null
cs.SI physics.soc-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In many social networks, several different link relations will exist between the same set of users. Additionally, attribute or textual information will be associated with those users, such as demographic details or user-generated content. For many data analysis tasks, such as community finding and data visualisation,...
[ { "version": "v1", "created": "Thu, 24 Jan 2013 15:07:12 GMT" }, { "version": "v2", "created": "Mon, 28 Jan 2013 15:41:22 GMT" }, { "version": "v3", "created": "Mon, 18 Feb 2013 13:56:21 GMT" } ]
2013-02-19T00:00:00
[ [ "Greene", "Derek", "" ], [ "Cunningham", "Pádraig", "" ] ]
TITLE: Producing a Unified Graph Representation from Multiple Social Network Views ABSTRACT: In many social networks, several different link relations will exist between the same set of users. Additionally, attribute or textual information will be associated with those users, such as demographic details or user-g...
1302.3219
Chunhua Shen
Chunhua Shen, Junae Kim, Fayao Liu, Lei Wang, Anton van den Hengel
An Efficient Dual Approach to Distance Metric Learning
null
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Distance metric learning is of fundamental interest in machine learning because the distance metric employed can significantly affect the performance of many learning methods. Quadratic Mahalanobis metric learning is a popular approach to the problem, but typically requires solving a semidefinite programming (SDP) pr...
[ { "version": "v1", "created": "Wed, 13 Feb 2013 08:48:53 GMT" } ]
2013-02-15T00:00:00
[ [ "Shen", "Chunhua", "" ], [ "Kim", "Junae", "" ], [ "Liu", "Fayao", "" ], [ "Wang", "Lei", "" ], [ "Hengel", "Anton van den", "" ] ]
TITLE: An Efficient Dual Approach to Distance Metric Learning ABSTRACT: Distance metric learning is of fundamental interest in machine learning because the distance metric employed can significantly affect the performance of many learning methods. Quadratic Mahalanobis metric learning is a popular approach to the p...
1302.3123
Nizar Banu P K
P. K. Nizar Banu, H. Hannah Inbarani
An Analysis of Gene Expression Data using Penalized Fuzzy C-Means Approach
14; IJCCI, Vol. 1, Issue 2,(January-July)2011
null
null
null
cs.CV cs.CE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
With the rapid advances of microarray technologies, large amounts of high-dimensional gene expression data are being generated, which poses significant computational challenges. A first step towards addressing this challenge is the use of clustering techniques, which is essential in the data mining process to reveal ...
[ { "version": "v1", "created": "Tue, 8 Jan 2013 17:16:39 GMT" } ]
2013-02-14T00:00:00
[ [ "Banu", "P. K. Nizar", "" ], [ "Inbarani", "H. Hannah", "" ] ]
TITLE: An Analysis of Gene Expression Data using Penalized Fuzzy C-Means Approach ABSTRACT: With the rapid advances of microarray technologies, large amounts of high-dimensional gene expression data are being generated, which poses significant computational challenges. A first step towards addressing this challen...
1208.6157
Atieh Mirshahvalad
Atieh Mirshahvalad, Olivier H. Beauchesne, Eric Archambault, Martin Rosvall
Resampling effects on significance analysis of network clustering and ranking
12 pages, 7 figures
null
10.1371/journal.pone.0053943
null
physics.soc-ph cs.SI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Community detection helps us simplify the complex configuration of networks, but communities are reliable only if they are statistically significant. To detect statistically significant communities, a common approach is to resample the original network and analyze the communities. But resampling assumes independence ...
[ { "version": "v1", "created": "Thu, 30 Aug 2012 12:58:10 GMT" }, { "version": "v2", "created": "Mon, 11 Feb 2013 10:11:06 GMT" } ]
2013-02-12T00:00:00
[ [ "Mirshahvalad", "Atieh", "" ], [ "Beauchesne", "Olivier H.", "" ], [ "Archambault", "Eric", "" ], [ "Rosvall", "Martin", "" ] ]
TITLE: Resampling effects on significance analysis of network clustering and ranking ABSTRACT: Community detection helps us simplify the complex configuration of networks, but communities are reliable only if they are statistically significant. To detect statistically significant communities, a common approach is...
1302.2244
Jiping Xiong
Jiping Xiong, Jian Zhao and Lei Chen
Efficient Data Gathering in Wireless Sensor Networks Based on Matrix Completion and Compressive Sensing
null
null
null
null
cs.NI cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Gathering data in an energy efficient manner in wireless sensor networks is an important design challenge. In wireless sensor networks, the readings of sensors always exhibit intra-temporal and inter-spatial correlations. Therefore, in this letter, we use low rank matrix completion theory to explore the inter-spatial...
[ { "version": "v1", "created": "Sat, 9 Feb 2013 16:34:00 GMT" } ]
2013-02-12T00:00:00
[ [ "Xiong", "Jiping", "" ], [ "Zhao", "Jian", "" ], [ "Chen", "Lei", "" ] ]
TITLE: Efficient Data Gathering in Wireless Sensor Networks Based on Matrix Completion and Compressive Sensing ABSTRACT: Gathering data in an energy efficient manner in wireless sensor networks is an important design challenge. In wireless sensor networks, the readings of sensors always exhibit intra-temporal and...
1302.2436
Mahmood Ali Mohd
Mohd Mahmood Ali, Mohd S Qaseem, Lakshmi Rajamani, A Govardhan
Extracting useful rules through improved decision tree induction using information entropy
15 pages, 7 figures, 4 tables, International Journal of Information Sciences and Techniques (IJIST) Vol.3, No.1, January 2013
null
10.5121/ijist.2013.3103
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Classification is widely used technique in the data mining domain, where scalability and efficiency are the immediate problems in classification algorithms for large databases. We suggest improvements to the existing C4.5 decision tree algorithm. In this paper attribute oriented induction (AOI) and relevance analysis...
[ { "version": "v1", "created": "Mon, 11 Feb 2013 10:29:17 GMT" } ]
2013-02-12T00:00:00
[ [ "Ali", "Mohd Mahmood", "" ], [ "Qaseem", "Mohd S", "" ], [ "Rajamani", "Lakshmi", "" ], [ "Govardhan", "A", "" ] ]
TITLE: Extracting useful rules through improved decision tree induction using information entropy ABSTRACT: Classification is widely used technique in the data mining domain, where scalability and efficiency are the immediate problems in classification algorithms for large databases. We suggest improvements to th...
1302.2576
Oluwasanmi Koyejo
Oluwasanmi Koyejo and Cheng Lee and Joydeep Ghosh
The trace norm constrained matrix-variate Gaussian process for multitask bipartite ranking
14 pages, 9 figures, 5 tables
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We propose a novel hierarchical model for multitask bipartite ranking. The proposed approach combines a matrix-variate Gaussian process with a generative model for task-wise bipartite ranking. In addition, we employ a novel trace constrained variational inference approach to impose low rank structure on the posterior...
[ { "version": "v1", "created": "Mon, 11 Feb 2013 19:16:25 GMT" } ]
2013-02-12T00:00:00
[ [ "Koyejo", "Oluwasanmi", "" ], [ "Lee", "Cheng", "" ], [ "Ghosh", "Joydeep", "" ] ]
TITLE: The trace norm constrained matrix-variate Gaussian process for multitask bipartite ranking ABSTRACT: We propose a novel hierarchical model for multitask bipartite ranking. The proposed approach combines a matrix-variate Gaussian process with a generative model for task-wise bipartite ranking. In addition, ...
1302.1529
TongSheng Chu
TongSheng Chu, Yang Xiang
Exploring Parallelism in Learning Belief Networks
Appears in Proceedings of the Thirteenth Conference on Uncertainty in Artificial Intelligence (UAI1997)
null
null
UAI-P-1997-PG-90-98
cs.AI cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
It has been shown that a class of probabilistic domain models cannot be learned correctly by several existing algorithms which employ a single-link look ahead search. When a multi-link look ahead search is used, the computational complexity of the learning algorithm increases. We study how to use parallelism to tackl...
[ { "version": "v1", "created": "Wed, 6 Feb 2013 15:54:31 GMT" } ]
2013-02-08T00:00:00
[ [ "Chu", "TongSheng", "" ], [ "Xiang", "Yang", "" ] ]
TITLE: Exploring Parallelism in Learning Belief Networks ABSTRACT: It has been shown that a class of probabilistic domain models cannot be learned correctly by several existing algorithms which employ a single-link look ahead search. When a multi-link look ahead search is used, the computational complexity of the l...
1109.4920
Reza Farrahi Moghaddam
Reza Farrahi Moghaddam and Mohamed Cheriet
Beyond pixels and regions: A non local patch means (NLPM) method for content-level restoration, enhancement, and reconstruction of degraded document images
This paper has been withdrawn by the author to avoid duplication on the DBLP bibliography
Pattern Recognition 44 (2011) 363-374
10.1016/j.patcog.2010.07.027
null
cs.CV cs.IR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A patch-based non-local restoration and reconstruction method for preprocessing degraded document images is introduced. The method collects relative data from the whole input image, while the image data are first represented by a content-level descriptor based on patches. This patch-equivalent representation of the i...
[ { "version": "v1", "created": "Thu, 22 Sep 2011 19:24:58 GMT" }, { "version": "v2", "created": "Fri, 7 Oct 2011 16:46:52 GMT" }, { "version": "v3", "created": "Tue, 8 Nov 2011 22:33:13 GMT" } ]
2013-02-07T00:00:00
[ [ "Moghaddam", "Reza Farrahi", "" ], [ "Cheriet", "Mohamed", "" ] ]
TITLE: Beyond pixels and regions: A non local patch means (NLPM) method for content-level restoration, enhancement, and reconstruction of degraded document images ABSTRACT: A patch-based non-local restoration and reconstruction method for preprocessing degraded document images is introduced. The method collects...
1302.1007
Firas Ajil Jassim
Firas Ajil Jassim
Image Denoising Using Interquartile Range Filter with Local Averaging
5 pages, 8 figures, 2 tables
International Journal of Soft Computing and Engineering (IJSCE) ISSN: 2231-2307, Volume-2, Issue-6, January 2013
null
null
cs.CV
http://creativecommons.org/licenses/by/3.0/
Image denoising is one of the fundamental problems in image processing. In this paper, a novel approach to suppress noise from the image is conducted by applying the interquartile range (IQR) which is one of the statistical methods used to detect outlier effect from a dataset. A window of size kXk was implemented to ...
[ { "version": "v1", "created": "Tue, 5 Feb 2013 12:02:53 GMT" } ]
2013-02-06T00:00:00
[ [ "Jassim", "Firas Ajil", "" ] ]
TITLE: Image Denoising Using Interquartile Range Filter with Local Averaging ABSTRACT: Image denoising is one of the fundamental problems in image processing. In this paper, a novel approach to suppress noise from the image is conducted by applying the interquartile range (IQR) which is one of the statistical metho...
1206.1270
Benjamin Recht
Victor Bittorf and Benjamin Recht and Christopher Re and Joel A. Tropp
Factoring nonnegative matrices with linear programs
17 pages, 10 figures. Modified theorem statement for robust recovery conditions. Revised proof techniques to make arguments more elementary. Results on robustness when rows are duplicated have been superseded by arxiv.org/1211.6687
null
null
null
math.OC cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper describes a new approach, based on linear programming, for computing nonnegative matrix factorizations (NMFs). The key idea is a data-driven model for the factorization where the most salient features in the data are used to express the remaining features. More precisely, given a data matrix X, the algorit...
[ { "version": "v1", "created": "Wed, 6 Jun 2012 16:42:27 GMT" }, { "version": "v2", "created": "Sat, 2 Feb 2013 23:40:56 GMT" } ]
2013-02-05T00:00:00
[ [ "Bittorf", "Victor", "" ], [ "Recht", "Benjamin", "" ], [ "Re", "Christopher", "" ], [ "Tropp", "Joel A.", "" ] ]
TITLE: Factoring nonnegative matrices with linear programs ABSTRACT: This paper describes a new approach, based on linear programming, for computing nonnegative matrix factorizations (NMFs). The key idea is a data-driven model for the factorization where the most salient features in the data are used to express the...
1302.0413
Catarina Moreira
Catarina Moreira and P\'avel Calado and Bruno Martins
Learning to Rank for Expert Search in Digital Libraries of Academic Publications
null
Progress in Artificial Intelligence, Lecture Notes in Computer Science, Springer Berlin Heidelberg. In Proceedings of the 15th Portuguese Conference on Artificial Intelligence, 2011
null
null
cs.IR cs.DL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The task of expert finding has been getting increasing attention in information retrieval literature. However, the current state-of-the-art is still lacking in principled approaches for combining different sources of evidence in an optimal way. This paper explores the usage of learning to rank methods as a principled...
[ { "version": "v1", "created": "Sat, 2 Feb 2013 18:36:08 GMT" } ]
2013-02-05T00:00:00
[ [ "Moreira", "Catarina", "" ], [ "Calado", "Pável", "" ], [ "Martins", "Bruno", "" ] ]
TITLE: Learning to Rank for Expert Search in Digital Libraries of Academic Publications ABSTRACT: The task of expert finding has been getting increasing attention in information retrieval literature. However, the current state-of-the-art is still lacking in principled approaches for combining different sources of...
1302.0540
Harris Georgiou
Harris V. Georgiou, Michael E. Mavroforakis
A game-theoretic framework for classifier ensembles using weighted majority voting with local accuracy estimates
21 pages, 9 tables, 1 figure, 68 references
null
null
null
cs.LG
http://creativecommons.org/licenses/by-nc-sa/3.0/
In this paper, a novel approach for the optimal combination of binary classifiers is proposed. The classifier combination problem is approached from a Game Theory perspective. The proposed framework of adapted weighted majority rules (WMR) is tested against common rank-based, Bayesian and simple majority models, as w...
[ { "version": "v1", "created": "Sun, 3 Feb 2013 22:12:52 GMT" } ]
2013-02-05T00:00:00
[ [ "Georgiou", "Harris V.", "" ], [ "Mavroforakis", "Michael E.", "" ] ]
TITLE: A game-theoretic framework for classifier ensembles using weighted majority voting with local accuracy estimates ABSTRACT: In this paper, a novel approach for the optimal combination of binary classifiers is proposed. The classifier combination problem is approached from a Game Theory perspective. The prop...
1302.0739
Conrad Lee
Conrad Lee, P\'adraig Cunningham
Benchmarking community detection methods on social media data
null
null
null
null
cs.SI physics.soc-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Benchmarking the performance of community detection methods on empirical social network data has been identified as critical for improving these methods. In particular, while most current research focuses on detecting communities in data that has been digitally extracted from large social media and telecommunications...
[ { "version": "v1", "created": "Mon, 4 Feb 2013 16:12:22 GMT" } ]
2013-02-05T00:00:00
[ [ "Lee", "Conrad", "" ], [ "Cunningham", "Pádraig", "" ] ]
TITLE: Benchmarking community detection methods on social media data ABSTRACT: Benchmarking the performance of community detection methods on empirical social network data has been identified as critical for improving these methods. In particular, while most current research focuses on detecting communities in data...
1208.4586
Jeremiah Blocki
Jeremiah Blocki, Avrim Blum, Anupam Datta and Or Sheffet
Differentially Private Data Analysis of Social Networks via Restricted Sensitivity
null
null
null
null
cs.CR cs.SI physics.soc-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We introduce the notion of restricted sensitivity as an alternative to global and smooth sensitivity to improve accuracy in differentially private data analysis. The definition of restricted sensitivity is similar to that of global sensitivity except that instead of quantifying over all possible datasets, we take adv...
[ { "version": "v1", "created": "Wed, 22 Aug 2012 19:31:05 GMT" }, { "version": "v2", "created": "Fri, 1 Feb 2013 20:33:05 GMT" } ]
2013-02-04T00:00:00
[ [ "Blocki", "Jeremiah", "" ], [ "Blum", "Avrim", "" ], [ "Datta", "Anupam", "" ], [ "Sheffet", "Or", "" ] ]
TITLE: Differentially Private Data Analysis of Social Networks via Restricted Sensitivity ABSTRACT: We introduce the notion of restricted sensitivity as an alternative to global and smooth sensitivity to improve accuracy in differentially private data analysis. The definition of restricted sensitivity is similar ...