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1009.0892
Chunhua Shen
Yongbin Zheng, Chunhua Shen, Richard Hartley, Xinsheng Huang
Effective Pedestrian Detection Using Center-symmetric Local Binary/Trinary Patterns
11 pages
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Accurately detecting pedestrians in images plays a critically important role in many computer vision applications. Extraction of effective features is the key to this task. Promising features should be discriminative, robust to various variations and easy to compute. In this work, we present novel features, termed de...
[ { "version": "v1", "created": "Sun, 5 Sep 2010 05:16:11 GMT" }, { "version": "v2", "created": "Fri, 17 Sep 2010 01:58:29 GMT" } ]
2010-09-20T00:00:00
[ [ "Zheng", "Yongbin", "" ], [ "Shen", "Chunhua", "" ], [ "Hartley", "Richard", "" ], [ "Huang", "Xinsheng", "" ] ]
TITLE: Effective Pedestrian Detection Using Center-symmetric Local Binary/Trinary Patterns ABSTRACT: Accurately detecting pedestrians in images plays a critically important role in many computer vision applications. Extraction of effective features is the key to this task. Promising features should be discriminat...
1009.2722
Myung Jin Choi
Myung Jin Choi, Vincent Y. F. Tan, Animashree Anandkumar, Alan S. Willsky
Learning Latent Tree Graphical Models
null
null
null
null
stat.ML cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We study the problem of learning a latent tree graphical model where samples are available only from a subset of variables. We propose two consistent and computationally efficient algorithms for learning minimal latent trees, that is, trees without any redundant hidden nodes. Unlike many existing methods, the observe...
[ { "version": "v1", "created": "Tue, 14 Sep 2010 17:37:44 GMT" } ]
2010-09-15T00:00:00
[ [ "Choi", "Myung Jin", "" ], [ "Tan", "Vincent Y. F.", "" ], [ "Anandkumar", "Animashree", "" ], [ "Willsky", "Alan S.", "" ] ]
TITLE: Learning Latent Tree Graphical Models ABSTRACT: We study the problem of learning a latent tree graphical model where samples are available only from a subset of variables. We propose two consistent and computationally efficient algorithms for learning minimal latent trees, that is, trees without any redundan...
1009.0861
Ameet Talwalkar
Mehryar Mohri, Ameet Talwalkar
On the Estimation of Coherence
null
null
null
null
stat.ML cs.AI cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Low-rank matrix approximations are often used to help scale standard machine learning algorithms to large-scale problems. Recently, matrix coherence has been used to characterize the ability to extract global information from a subset of matrix entries in the context of these low-rank approximations and other samplin...
[ { "version": "v1", "created": "Sat, 4 Sep 2010 19:18:54 GMT" } ]
2010-09-07T00:00:00
[ [ "Mohri", "Mehryar", "" ], [ "Talwalkar", "Ameet", "" ] ]
TITLE: On the Estimation of Coherence ABSTRACT: Low-rank matrix approximations are often used to help scale standard machine learning algorithms to large-scale problems. Recently, matrix coherence has been used to characterize the ability to extract global information from a subset of matrix entries in the context ...
1009.0384
Rahmat Widia Sembiring
Rahmat Widia Sembiring, Jasni Mohamad Zain, Abdullah Embong
Clustering high dimensional data using subspace and projected clustering algorithms
9 pages, 6 figures
International journal of computer science & information Technology (IJCSIT) Vol.2, No.4, August 2010, p.162-170
10.5121/ijcsit.2010.2414
null
cs.DB
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Problem statement: Clustering has a number of techniques that have been developed in statistics, pattern recognition, data mining, and other fields. Subspace clustering enumerates clusters of objects in all subspaces of a dataset. It tends to produce many over lapping clusters. Approach: Subspace clustering and proje...
[ { "version": "v1", "created": "Thu, 2 Sep 2010 10:47:11 GMT" } ]
2010-09-03T00:00:00
[ [ "Sembiring", "Rahmat Widia", "" ], [ "Zain", "Jasni Mohamad", "" ], [ "Embong", "Abdullah", "" ] ]
TITLE: Clustering high dimensional data using subspace and projected clustering algorithms ABSTRACT: Problem statement: Clustering has a number of techniques that have been developed in statistics, pattern recognition, data mining, and other fields. Subspace clustering enumerates clusters of objects in all subspa...
1008.4938
Randen Patterson
Yoojin Hong, Kyung Dae Ko, Gaurav Bhardwaj, Zhenhai Zhang, Damian B. van Rossum, and Randen L. Patterson
Towards Solving the Inverse Protein Folding Problem
22 pages, 11 figures
null
null
null
q-bio.QM cs.SC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Accurately assigning folds for divergent protein sequences is a major obstacle to structural studies and underlies the inverse protein folding problem. Herein, we outline our theories for fold-recognition in the "twilight-zone" of sequence similarity (<25% identity). Our analyses demonstrate that structural sequence ...
[ { "version": "v1", "created": "Sun, 29 Aug 2010 15:34:02 GMT" } ]
2010-08-31T00:00:00
[ [ "Hong", "Yoojin", "" ], [ "Ko", "Kyung Dae", "" ], [ "Bhardwaj", "Gaurav", "" ], [ "Zhang", "Zhenhai", "" ], [ "van Rossum", "Damian B.", "" ], [ "Patterson", "Randen L.", "" ] ]
TITLE: Towards Solving the Inverse Protein Folding Problem ABSTRACT: Accurately assigning folds for divergent protein sequences is a major obstacle to structural studies and underlies the inverse protein folding problem. Herein, we outline our theories for fold-recognition in the "twilight-zone" of sequence similar...
1008.3629
Dhouha Grissa
Dhouha Grissa, Sylvie Guillaume and Engelbert Mephu Nguifo
Combining Clustering techniques and Formal Concept Analysis to characterize Interestingness Measures
13 pages, 2 figures
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Formal Concept Analysis "FCA" is a data analysis method which enables to discover hidden knowledge existing in data. A kind of hidden knowledge extracted from data is association rules. Different quality measures were reported in the literature to extract only relevant association rules. Given a dataset, the choice o...
[ { "version": "v1", "created": "Sat, 21 Aug 2010 13:23:23 GMT" } ]
2010-08-24T00:00:00
[ [ "Grissa", "Dhouha", "" ], [ "Guillaume", "Sylvie", "" ], [ "Nguifo", "Engelbert Mephu", "" ] ]
TITLE: Combining Clustering techniques and Formal Concept Analysis to characterize Interestingness Measures ABSTRACT: Formal Concept Analysis "FCA" is a data analysis method which enables to discover hidden knowledge existing in data. A kind of hidden knowledge extracted from data is association rules. Different ...
1007.0437
Adrian Melott
Adrian L. Melott (University of Kansas) and Richard K. Bambach (Smithsonian Institution Museum of Natural History)
Nemesis Reconsidered
10 pages, 2 figures, accepted for publication in Monthly Notices of the Royal Astronomical Society
Monthly Notices of the Royal Astronomical Society Letters 407, L99-L102 (2010)
10.1111/j.1745-3933.2010.00913.x
null
astro-ph.SR astro-ph.EP astro-ph.GA physics.geo-ph q-bio.PE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The hypothesis of a companion object (Nemesis) orbiting the Sun was motivated by the claim of a terrestrial extinction periodicity, thought to be mediated by comet showers. The orbit of a distant companion to the Sun is expected to be perturbed by the Galactic tidal field and encounters with passing stars, which will...
[ { "version": "v1", "created": "Fri, 2 Jul 2010 19:59:47 GMT" } ]
2010-08-20T00:00:00
[ [ "Melott", "Adrian L.", "", "University of Kansas" ], [ "Bambach", "Richard K.", "", "Smithsonian Institution Museum of Natural History" ] ]
TITLE: Nemesis Reconsidered ABSTRACT: The hypothesis of a companion object (Nemesis) orbiting the Sun was motivated by the claim of a terrestrial extinction periodicity, thought to be mediated by comet showers. The orbit of a distant companion to the Sun is expected to be perturbed by the Galactic tidal field and e...
1008.2877
Dr. Wolfgang A. Rolke
Wolfgang Rolke and Angel Lopez
A Test for Equality of Distributions in High Dimensions
12 pages, 4 figures
null
null
null
physics.data-an astro-ph.IM hep-ex stat.ME
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present a method which tests whether or not two datasets (one of which could be Monte Carlo generated) might come from the same distribution. Our method works in arbitrarily high dimensions.
[ { "version": "v1", "created": "Tue, 17 Aug 2010 12:27:16 GMT" } ]
2010-08-18T00:00:00
[ [ "Rolke", "Wolfgang", "" ], [ "Lopez", "Angel", "" ] ]
TITLE: A Test for Equality of Distributions in High Dimensions ABSTRACT: We present a method which tests whether or not two datasets (one of which could be Monte Carlo generated) might come from the same distribution. Our method works in arbitrarily high dimensions.
1008.2574
Jinyoung Han
Jinyoung Han, Taejoong Chung, Seungbae Kim, Hyun-chul Kim, Ted "Taekyoung" Kwon, Yanghee Choi
An Empirical Study on Content Bundling in BitTorrent Swarming System
null
null
null
null
cs.NI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Despite the tremendous success of BitTorrent, its swarming system suffers from a fundamental limitation: lower or no availability of unpopular contents. Recently, Menasche et al. has shown that bundling is a promising solution to mitigate this availability problem; it improves the availability and reduces download ti...
[ { "version": "v1", "created": "Mon, 16 Aug 2010 05:25:19 GMT" } ]
2010-08-17T00:00:00
[ [ "Han", "Jinyoung", "" ], [ "Chung", "Taejoong", "" ], [ "Kim", "Seungbae", "" ], [ "Kim", "Hyun-chul", "" ], [ "Kwon", "Ted \"Taekyoung\"", "" ], [ "Choi", "Yanghee", "" ] ]
TITLE: An Empirical Study on Content Bundling in BitTorrent Swarming System ABSTRACT: Despite the tremendous success of BitTorrent, its swarming system suffers from a fundamental limitation: lower or no availability of unpopular contents. Recently, Menasche et al. has shown that bundling is a promising solution to ...
1008.2626
Jan Van den Bussche
Eveline Hoekx and Jan Van den Bussche
Mining tree-query associations in graphs
Full version of two earlier conference papers presented at KDD 2005 and ICDM 2006
null
null
null
cs.DB cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
New applications of data mining, such as in biology, bioinformatics, or sociology, are faced with large datasetsstructured as graphs. We introduce a novel class of tree-shapedpatterns called tree queries, and present algorithms for miningtree queries and tree-query associations in a large data graph. Novel about our ...
[ { "version": "v1", "created": "Mon, 16 Aug 2010 11:35:59 GMT" } ]
2010-08-17T00:00:00
[ [ "Hoekx", "Eveline", "" ], [ "Bussche", "Jan Van den", "" ] ]
TITLE: Mining tree-query associations in graphs ABSTRACT: New applications of data mining, such as in biology, bioinformatics, or sociology, are faced with large datasetsstructured as graphs. We introduce a novel class of tree-shapedpatterns called tree queries, and present algorithms for miningtree queries and tre...
1008.1253
Wojciech Galuba
Daniel M. Romero, Wojciech Galuba, Sitaram Asur and Bernardo A. Huberman
Influence and Passivity in Social Media
null
null
null
null
cs.CY physics.soc-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The ever-increasing amount of information flowing through Social Media forces the members of these networks to compete for attention and influence by relying on other people to spread their message. A large study of information propagation within Twitter reveals that the majority of users act as passive information c...
[ { "version": "v1", "created": "Fri, 6 Aug 2010 18:54:10 GMT" } ]
2010-08-09T00:00:00
[ [ "Romero", "Daniel M.", "" ], [ "Galuba", "Wojciech", "" ], [ "Asur", "Sitaram", "" ], [ "Huberman", "Bernardo A.", "" ] ]
TITLE: Influence and Passivity in Social Media ABSTRACT: The ever-increasing amount of information flowing through Social Media forces the members of these networks to compete for attention and influence by relying on other people to spread their message. A large study of information propagation within Twitter reve...
1007.3564
Dacheng Tao
Tianyi Zhou, Dacheng Tao, Xindong Wu
Manifold Elastic Net: A Unified Framework for Sparse Dimension Reduction
33 pages, 12 figures
Journal of Data Mining and Knowledge Discovery, 2010
10.1007/s10618-010-0182-x
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
It is difficult to find the optimal sparse solution of a manifold learning based dimensionality reduction algorithm. The lasso or the elastic net penalized manifold learning based dimensionality reduction is not directly a lasso penalized least square problem and thus the least angle regression (LARS) (Efron et al. \...
[ { "version": "v1", "created": "Wed, 21 Jul 2010 05:50:47 GMT" }, { "version": "v2", "created": "Sat, 24 Jul 2010 03:48:30 GMT" }, { "version": "v3", "created": "Tue, 27 Jul 2010 03:01:09 GMT" } ]
2010-07-28T00:00:00
[ [ "Zhou", "Tianyi", "" ], [ "Tao", "Dacheng", "" ], [ "Wu", "Xindong", "" ] ]
TITLE: Manifold Elastic Net: A Unified Framework for Sparse Dimension Reduction ABSTRACT: It is difficult to find the optimal sparse solution of a manifold learning based dimensionality reduction algorithm. The lasso or the elastic net penalized manifold learning based dimensionality reduction is not directly a las...
1001.1122
Alexander Gorban
A. N. Gorban, A. Zinovyev
Principal manifolds and graphs in practice: from molecular biology to dynamical systems
12 pages, 9 figures
International Journal of Neural Systems, Vol. 20, No. 3 (2010) 219-232
10.1142/S0129065710002383
null
cs.NE cs.AI
http://creativecommons.org/licenses/by/3.0/
We present several applications of non-linear data modeling, using principal manifolds and principal graphs constructed using the metaphor of elasticity (elastic principal graph approach). These approaches are generalizations of the Kohonen's self-organizing maps, a class of artificial neural networks. On several exa...
[ { "version": "v1", "created": "Thu, 7 Jan 2010 17:46:17 GMT" }, { "version": "v2", "created": "Sun, 25 Jul 2010 19:30:37 GMT" } ]
2010-07-27T00:00:00
[ [ "Gorban", "A. N.", "" ], [ "Zinovyev", "A.", "" ] ]
TITLE: Principal manifolds and graphs in practice: from molecular biology to dynamical systems ABSTRACT: We present several applications of non-linear data modeling, using principal manifolds and principal graphs constructed using the metaphor of elasticity (elastic principal graph approach). These approaches are...
1007.0824
Remi Flamary
R\'emi Flamary (LITIS), Benjamin Labb\'e (LITIS), Alain Rakotomamonjy (LITIS)
Filtrage vaste marge pour l'\'etiquetage s\'equentiel \`a noyaux de signaux
null
Conf\'erence Francophone sur l'Apprentissage Automatique, Clermont Ferrand : France (2010)
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We address in this paper the problem of multi-channel signal sequence labeling. In particular, we consider the problem where the signals are contaminated by noise or may present some dephasing with respect to their labels. For that, we propose to jointly learn a SVM sample classifier with a temporal filtering of the ...
[ { "version": "v1", "created": "Tue, 6 Jul 2010 07:47:00 GMT" } ]
2010-07-26T00:00:00
[ [ "Flamary", "Rémi", "", "LITIS" ], [ "Labbé", "Benjamin", "", "LITIS" ], [ "Rakotomamonjy", "Alain", "", "LITIS" ] ]
TITLE: Filtrage vaste marge pour l'\'etiquetage s\'equentiel \`a noyaux de signaux ABSTRACT: We address in this paper the problem of multi-channel signal sequence labeling. In particular, we consider the problem where the signals are contaminated by noise or may present some dephasing with respect to their labels...
1003.0470
Krishnakumar Balasubramanian
Krishnakumar Balasubramanian, Pinar Donmez, Guy Lebanon
Unsupervised Supervised Learning II: Training Margin Based Classifiers without Labels
22 pages, 43 figures
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Many popular linear classifiers, such as logistic regression, boosting, or SVM, are trained by optimizing a margin-based risk function. Traditionally, these risk functions are computed based on a labeled dataset. We develop a novel technique for estimating such risks using only unlabeled data and the marginal label d...
[ { "version": "v1", "created": "Mon, 1 Mar 2010 22:32:18 GMT" }, { "version": "v2", "created": "Wed, 21 Jul 2010 21:19:35 GMT" } ]
2010-07-23T00:00:00
[ [ "Balasubramanian", "Krishnakumar", "" ], [ "Donmez", "Pinar", "" ], [ "Lebanon", "Guy", "" ] ]
TITLE: Unsupervised Supervised Learning II: Training Margin Based Classifiers without Labels ABSTRACT: Many popular linear classifiers, such as logistic regression, boosting, or SVM, are trained by optimizing a margin-based risk function. Traditionally, these risk functions are computed based on a labeled dataset...
1007.3553
Francois Meyer
Kye M. Taylor, Michael J. Procopio, Christopher J. Young, and Francois G. Meyer
Exploring the Manifold of Seismic Waves: Application to the Estimation of Arrival-Times
21 pages, 13 figures
null
null
null
physics.data-an nlin.CD physics.geo-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We propose a new method to analyze seismic time series and estimate the arrival-times of seismic waves. Our approach combines two ingredients: the times series are first lifted into a high-dimensional space using time-delay embedding; the resulting phase space is then parametrized using a nonlinear method based on th...
[ { "version": "v1", "created": "Wed, 21 Jul 2010 02:46:30 GMT" }, { "version": "v2", "created": "Thu, 22 Jul 2010 00:39:21 GMT" } ]
2010-07-23T00:00:00
[ [ "Taylor", "Kye M.", "" ], [ "Procopio", "Michael J.", "" ], [ "Young", "Christopher J.", "" ], [ "Meyer", "Francois G.", "" ] ]
TITLE: Exploring the Manifold of Seismic Waves: Application to the Estimation of Arrival-Times ABSTRACT: We propose a new method to analyze seismic time series and estimate the arrival-times of seismic waves. Our approach combines two ingredients: the times series are first lifted into a high-dimensional space us...
1007.3680
Alain Barrat
Ciro Cattuto, Wouter Van den Broeck, Alain Barrat, Vittoria Colizza, Jean-Fran\c{c}ois Pinton, Alessandro Vespignani
Dynamics of person-to-person interactions from distributed RFID sensor networks
see also http://www.sociopatterns.org
PLoS ONE 5(7): e11596 (2010)
10.1371/journal.pone.0011596
null
physics.soc-ph cond-mat.stat-mech cs.HC q-bio.OT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Digital networks, mobile devices, and the possibility of mining the ever-increasing amount of digital traces that we leave behind in our daily activities are changing the way we can approach the study of human and social interactions. Large-scale datasets, however, are mostly available for collective and statistical ...
[ { "version": "v1", "created": "Wed, 21 Jul 2010 15:35:18 GMT" } ]
2010-07-22T00:00:00
[ [ "Cattuto", "Ciro", "" ], [ "Broeck", "Wouter Van den", "" ], [ "Barrat", "Alain", "" ], [ "Colizza", "Vittoria", "" ], [ "Pinton", "Jean-François", "" ], [ "Vespignani", "Alessandro", "" ] ]
TITLE: Dynamics of person-to-person interactions from distributed RFID sensor networks ABSTRACT: Digital networks, mobile devices, and the possibility of mining the ever-increasing amount of digital traces that we leave behind in our daily activities are changing the way we can approach the study of human and soc...
1007.2958
Hoang Trinh
Hoang Trinh
A Machine Learning Approach to Recovery of Scene Geometry from Images
null
null
null
null
cs.CV cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recovering the 3D structure of the scene from images yields useful information for tasks such as shape and scene recognition, object detection, or motion planning and object grasping in robotics. In this thesis, we introduce a general machine learning approach called unsupervised CRF learning based on maximizing the ...
[ { "version": "v1", "created": "Sat, 17 Jul 2010 19:59:11 GMT" } ]
2010-07-20T00:00:00
[ [ "Trinh", "Hoang", "" ] ]
TITLE: A Machine Learning Approach to Recovery of Scene Geometry from Images ABSTRACT: Recovering the 3D structure of the scene from images yields useful information for tasks such as shape and scene recognition, object detection, or motion planning and object grasping in robotics. In this thesis, we introduce a ge...
1007.2545
Anirban Chakraborti
Kimmo Kaski
Social Complexity: can it be analyzed and modelled?
5 pages, 2 figures, REVTeX. To appear in "Econophysics", a special issue in Science and Culture (Kolkata, India) to celebrate 15 years of Econophysics
null
null
null
physics.soc-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Over the past decade network theory has turned out to be a powerful methodology to investigate complex systems of various sorts. Through data analysis, modeling, and simulation quite an unparalleled insight into their structure, function, and response can be obtained. In human societies individuals are linked through...
[ { "version": "v1", "created": "Thu, 15 Jul 2010 12:43:35 GMT" } ]
2010-07-16T00:00:00
[ [ "Kaski", "Kimmo", "" ] ]
TITLE: Social Complexity: can it be analyzed and modelled? ABSTRACT: Over the past decade network theory has turned out to be a powerful methodology to investigate complex systems of various sorts. Through data analysis, modeling, and simulation quite an unparalleled insight into their structure, function, and resp...
1005.4496
Secretary Aircc Journal
Dewan Md. Farid(1), Nouria Harbi(1), and Mohammad Zahidur Rahman(2), ((1)University Lumiere Lyon 2 - France, (2)Jahangirnagar University, Bangladesh)
Combining Naive Bayes and Decision Tree for Adaptive Intrusion Detection
14 Pages, IJNSA
International Journal of Network Security & Its Applications 2.2 (2010) 12-25
10.5121/ijnsa.2010.2202
null
cs.AI
http://creativecommons.org/licenses/by-nc-sa/3.0/
In this paper, a new learning algorithm for adaptive network intrusion detection using naive Bayesian classifier and decision tree is presented, which performs balance detections and keeps false positives at acceptable level for different types of network attacks, and eliminates redundant attributes as well as contra...
[ { "version": "v1", "created": "Tue, 25 May 2010 07:47:00 GMT" } ]
2010-07-15T00:00:00
[ [ "Farid", "Dewan Md.", "" ], [ "Harbi", "Nouria", "" ], [ "Rahman", "Mohammad Zahidur", "" ] ]
TITLE: Combining Naive Bayes and Decision Tree for Adaptive Intrusion Detection ABSTRACT: In this paper, a new learning algorithm for adaptive network intrusion detection using naive Bayesian classifier and decision tree is presented, which performs balance detections and keeps false positives at acceptable level f...
1005.5434
Secretary Aircc Journal
B.N. Keshavamurthy, Mitesh Sharma and Durga Toshniwal
Efficient Support Coupled Frequent Pattern Mining Over Progressive Databases
10 Pages, IJDMS
International Journal of Database Management Systems 2.2 (2010) 73-82
10.5121/ijdms.2010.2205
null
cs.DB
http://creativecommons.org/licenses/by-nc-sa/3.0/
There have been many recent studies on sequential pattern mining. The sequential pattern mining on progressive databases is relatively very new, in which we progressively discover the sequential patterns in period of interest. Period of interest is a sliding window continuously advancing as the time goes by. As the f...
[ { "version": "v1", "created": "Sat, 29 May 2010 07:38:51 GMT" } ]
2010-07-15T00:00:00
[ [ "Keshavamurthy", "B. N.", "" ], [ "Sharma", "Mitesh", "" ], [ "Toshniwal", "Durga", "" ] ]
TITLE: Efficient Support Coupled Frequent Pattern Mining Over Progressive Databases ABSTRACT: There have been many recent studies on sequential pattern mining. The sequential pattern mining on progressive databases is relatively very new, in which we progressively discover the sequential patterns in period of int...
1007.1268
Huy Nguyen
Huy Nguyen and Deokjai Choi
Application of Data Mining to Network Intrusion Detection: Classifier Selection Model
Presented at The 11th Asia-Pacific Network Operations and Management Symposium (APNOMS 2008)
null
null
null
cs.NI cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
As network attacks have increased in number and severity over the past few years, intrusion detection system (IDS) is increasingly becoming a critical component to secure the network. Due to large volumes of security audit data as well as complex and dynamic properties of intrusion behaviors, optimizing performance o...
[ { "version": "v1", "created": "Thu, 8 Jul 2010 00:23:40 GMT" } ]
2010-07-09T00:00:00
[ [ "Nguyen", "Huy", "" ], [ "Choi", "Deokjai", "" ] ]
TITLE: Application of Data Mining to Network Intrusion Detection: Classifier Selection Model ABSTRACT: As network attacks have increased in number and severity over the past few years, intrusion detection system (IDS) is increasingly becoming a critical component to secure the network. Due to large volumes of sec...
0803.1568
Uwe Aickelin
Qi Chen and Uwe Aickelin
Dempster-Shafer for Anomaly Detection
null
Proceedings of the International Conference on Data Mining (DMIN 2006), pp 232-238, Las Vegas, USA 2006
null
null
cs.NE cs.AI cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we implement an anomaly detection system using the Dempster-Shafer method. Using two standard benchmark problems we show that by combining multiple signals it is possible to achieve better results than by using a single signal. We further show that by applying this approach to a real-world email datase...
[ { "version": "v1", "created": "Tue, 11 Mar 2008 12:39:01 GMT" } ]
2010-07-05T00:00:00
[ [ "Chen", "Qi", "" ], [ "Aickelin", "Uwe", "" ] ]
TITLE: Dempster-Shafer for Anomaly Detection ABSTRACT: In this paper, we implement an anomaly detection system using the Dempster-Shafer method. Using two standard benchmark problems we show that by combining multiple signals it is possible to achieve better results than by using a single signal. We further show th...
0803.2973
Uwe Aickelin
Uwe Aickelin, Jamie Twycross and Thomas Hesketh-Roberts
Rule Generalisation in Intrusion Detection Systems using Snort
null
International Journal of Electronic Security and Digital Forensics, 1 (1), pp 101-116, 2007
10.1504/IJESDF.2007.013596,
null
cs.NE cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Intrusion Detection Systems (ids)provide an important layer of security for computer systems and networks, and are becoming more and more necessary as reliance on Internet services increases and systems with sensitive data are more commonly open to Internet access. An ids responsibility is to detect suspicious or una...
[ { "version": "v1", "created": "Thu, 20 Mar 2008 11:59:27 GMT" }, { "version": "v2", "created": "Fri, 16 May 2008 10:42:09 GMT" } ]
2010-07-05T00:00:00
[ [ "Aickelin", "Uwe", "" ], [ "Twycross", "Jamie", "" ], [ "Hesketh-Roberts", "Thomas", "" ] ]
TITLE: Rule Generalisation in Intrusion Detection Systems using Snort ABSTRACT: Intrusion Detection Systems (ids)provide an important layer of security for computer systems and networks, and are becoming more and more necessary as reliance on Internet services increases and systems with sensitive data are more comm...
1004.3708
Uwe Aickelin
Yongnan Ji, Pierre-Yves Herve, Uwe Aickelin, Alain Pitiot
Parcellation of fMRI Datasets with ICA and PLS-A Data Driven Approach
8 pages, 5 figures, P12th International Conference of Medical Image Computing and Computer-Assisted Intervention (MICCAI 2009)
Proceedings of the 12th International Conference of Medical Image Computing and Computer-Assisted Intervention (MICCAI 2009), Part I, Lecture Notes in Computer Science 5761, London, UK, 2009
null
null
cs.CV cs.AI cs.NE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Inter-subject parcellation of functional Magnetic Resonance Imaging (fMRI) data based on a standard General Linear Model (GLM)and spectral clustering was recently proposed as a means to alleviate the issues associated with spatial normalization in fMRI. However, for all its appeal, a GLM-based parcellation approach i...
[ { "version": "v1", "created": "Wed, 21 Apr 2010 13:50:55 GMT" } ]
2010-07-05T00:00:00
[ [ "Ji", "Yongnan", "" ], [ "Herve", "Pierre-Yves", "" ], [ "Aickelin", "Uwe", "" ], [ "Pitiot", "Alain", "" ] ]
TITLE: Parcellation of fMRI Datasets with ICA and PLS-A Data Driven Approach ABSTRACT: Inter-subject parcellation of functional Magnetic Resonance Imaging (fMRI) data based on a standard General Linear Model (GLM)and spectral clustering was recently proposed as a means to alleviate the issues associated with spatia...
1006.1512
Uwe Aickelin
Julie Greensmith, Uwe Aickelin
The Deterministic Dendritic Cell Algorithm
12 pages, 1 algorithm, 1 figure, 2 tables, 7th International Conference on Artificial Immune Systems (ICARIS 2008)
Proceedings of the 7th International Conference on Artificial Immune Systems (ICARIS 2008), Phuket, Thailand, p 291-303
null
null
cs.AI cs.NE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The Dendritic Cell Algorithm is an immune-inspired algorithm orig- inally based on the function of natural dendritic cells. The original instantiation of the algorithm is a highly stochastic algorithm. While the performance of the algorithm is good when applied to large real-time datasets, it is difficult to anal- ys...
[ { "version": "v1", "created": "Tue, 8 Jun 2010 10:07:34 GMT" } ]
2010-07-05T00:00:00
[ [ "Greensmith", "Julie", "" ], [ "Aickelin", "Uwe", "" ] ]
TITLE: The Deterministic Dendritic Cell Algorithm ABSTRACT: The Dendritic Cell Algorithm is an immune-inspired algorithm orig- inally based on the function of natural dendritic cells. The original instantiation of the algorithm is a highly stochastic algorithm. While the performance of the algorithm is good when ap...
1006.5060
Xiaohui Xie
Gui-Bo Ye and Xiaohui Xie
Learning sparse gradients for variable selection and dimension reduction
null
null
null
null
stat.ML cs.LG stat.ME
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Variable selection and dimension reduction are two commonly adopted approaches for high-dimensional data analysis, but have traditionally been treated separately. Here we propose an integrated approach, called sparse gradient learning (SGL), for variable selection and dimension reduction via learning the gradients of...
[ { "version": "v1", "created": "Fri, 25 Jun 2010 20:27:00 GMT" }, { "version": "v2", "created": "Thu, 1 Jul 2010 05:06:43 GMT" } ]
2010-07-02T00:00:00
[ [ "Ye", "Gui-Bo", "" ], [ "Xie", "Xiaohui", "" ] ]
TITLE: Learning sparse gradients for variable selection and dimension reduction ABSTRACT: Variable selection and dimension reduction are two commonly adopted approaches for high-dimensional data analysis, but have traditionally been treated separately. Here we propose an integrated approach, called sparse gradient ...
1005.4032
Debotosh Bhattacharjee
Sandhya Arora, Debotosh Bhattacharjee, Mita Nasipuri, Dipak Kumar Basu, and Mahantapas Kundu
Combining Multiple Feature Extraction Techniques for Handwritten Devnagari Character Recognition
6 pages, 8-10 December 2008
ICIIS 2008
null
null
cs.CV cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper we present an OCR for Handwritten Devnagari Characters. Basic symbols are recognized by neural classifier. We have used four feature extraction techniques namely, intersection, shadow feature, chain code histogram and straight line fitting features. Shadow features are computed globally for character im...
[ { "version": "v1", "created": "Fri, 21 May 2010 17:57:50 GMT" } ]
2010-07-01T00:00:00
[ [ "Arora", "Sandhya", "" ], [ "Bhattacharjee", "Debotosh", "" ], [ "Nasipuri", "Mita", "" ], [ "Basu", "Dipak Kumar", "" ], [ "Kundu", "Mahantapas", "" ] ]
TITLE: Combining Multiple Feature Extraction Techniques for Handwritten Devnagari Character Recognition ABSTRACT: In this paper we present an OCR for Handwritten Devnagari Characters. Basic symbols are recognized by neural classifier. We have used four feature extraction techniques namely, intersection, shadow fe...
1006.5913
Debotosh Bhattacharjee
Sandhya Arora, Debotosh Bhattacharjee, Mita Nasipuri, Dipak Kumar Basu, and Mahantapas Kundu
Multiple Classifier Combination for Off-line Handwritten Devnagari Character Recognition
null
ICSC 2008
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This work presents the application of weighted majority voting technique for combination of classification decision obtained from three Multi_Layer Perceptron(MLP) based classifiers for Recognition of Handwritten Devnagari characters using three different feature sets. The features used are intersection, shadow featu...
[ { "version": "v1", "created": "Wed, 30 Jun 2010 16:38:02 GMT" } ]
2010-07-01T00:00:00
[ [ "Arora", "Sandhya", "" ], [ "Bhattacharjee", "Debotosh", "" ], [ "Nasipuri", "Mita", "" ], [ "Basu", "Dipak Kumar", "" ], [ "Kundu", "Mahantapas", "" ] ]
TITLE: Multiple Classifier Combination for Off-line Handwritten Devnagari Character Recognition ABSTRACT: This work presents the application of weighted majority voting technique for combination of classification decision obtained from three Multi_Layer Perceptron(MLP) based classifiers for Recognition of Handwri...
1006.5927
Debotosh Bhattacharjee
Sandhya Arora, Latesh Malik, Debotosh Bhattacharjee, and Mita Nasipuri
Classification Of Gradient Change Features Using MLP For Handwritten Character Recognition
null
EAIT 2006
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A novel, generic scheme for off-line handwritten English alphabets character images is proposed. The advantage of the technique is that it can be applied in a generic manner to different applications and is expected to perform better in uncertain and noisy environments. The recognition scheme is using a multilayer pe...
[ { "version": "v1", "created": "Wed, 30 Jun 2010 17:14:40 GMT" } ]
2010-07-01T00:00:00
[ [ "Arora", "Sandhya", "" ], [ "Malik", "Latesh", "" ], [ "Bhattacharjee", "Debotosh", "" ], [ "Nasipuri", "Mita", "" ] ]
TITLE: Classification Of Gradient Change Features Using MLP For Handwritten Character Recognition ABSTRACT: A novel, generic scheme for off-line handwritten English alphabets character images is proposed. The advantage of the technique is that it can be applied in a generic manner to different applications and is...
1006.5188
Nicola Di Mauro
Nicola Di Mauro and Teresa M.A. Basile and Stefano Ferilli and Floriana Esposito
Feature Construction for Relational Sequence Learning
15 pages
null
null
null
cs.AI cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We tackle the problem of multi-class relational sequence learning using relevant patterns discovered from a set of labelled sequences. To deal with this problem, firstly each relational sequence is mapped into a feature vector using the result of a feature construction method. Since, the efficacy of sequence learning...
[ { "version": "v1", "created": "Sun, 27 Jun 2010 08:56:11 GMT" } ]
2010-06-29T00:00:00
[ [ "Di Mauro", "Nicola", "" ], [ "Basile", "Teresa M. A.", "" ], [ "Ferilli", "Stefano", "" ], [ "Esposito", "Floriana", "" ] ]
TITLE: Feature Construction for Relational Sequence Learning ABSTRACT: We tackle the problem of multi-class relational sequence learning using relevant patterns discovered from a set of labelled sequences. To deal with this problem, firstly each relational sequence is mapped into a feature vector using the result o...
1006.5041
Yoshinobu Kawahara
Yoshinobu Kawahara, Kenneth Bollen, Shohei Shimizu and Takashi Washio
GroupLiNGAM: Linear non-Gaussian acyclic models for sets of variables
null
null
null
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Finding the structure of a graphical model has been received much attention in many fields. Recently, it is reported that the non-Gaussianity of data enables us to identify the structure of a directed acyclic graph without any prior knowledge on the structure. In this paper, we propose a novel non-Gaussianity based a...
[ { "version": "v1", "created": "Thu, 24 Jun 2010 13:09:36 GMT" } ]
2010-06-28T00:00:00
[ [ "Kawahara", "Yoshinobu", "" ], [ "Bollen", "Kenneth", "" ], [ "Shimizu", "Shohei", "" ], [ "Washio", "Takashi", "" ] ]
TITLE: GroupLiNGAM: Linear non-Gaussian acyclic models for sets of variables ABSTRACT: Finding the structure of a graphical model has been received much attention in many fields. Recently, it is reported that the non-Gaussianity of data enables us to identify the structure of a directed acyclic graph without any pr...
1006.5051
Ping Li
Ping Li
Fast ABC-Boost for Multi-Class Classification
null
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Abc-boost is a new line of boosting algorithms for multi-class classification, by utilizing the commonly used sum-to-zero constraint. To implement abc-boost, a base class must be identified at each boosting step. Prior studies used a very expensive procedure based on exhaustive search for determining the base class a...
[ { "version": "v1", "created": "Fri, 25 Jun 2010 19:48:50 GMT" } ]
2010-06-28T00:00:00
[ [ "Li", "Ping", "" ] ]
TITLE: Fast ABC-Boost for Multi-Class Classification ABSTRACT: Abc-boost is a new line of boosting algorithms for multi-class classification, by utilizing the commonly used sum-to-zero constraint. To implement abc-boost, a base class must be identified at each boosting step. Prior studies used a very expensive proc...
1006.4540
William Jackson
N. Suguna and K. Thanushkodi
A Novel Rough Set Reduct Algorithm for Medical Domain Based on Bee Colony Optimization
IEEE Publication Format, https://sites.google.com/site/journalofcomputing/
Journal of Computing, Vol. 2, No. 6, June 2010, NY, USA, ISSN 2151-9617
null
null
cs.LG cs.AI cs.NE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Feature selection refers to the problem of selecting relevant features which produce the most predictive outcome. In particular, feature selection task is involved in datasets containing huge number of features. Rough set theory has been one of the most successful methods used for feature selection. However, this met...
[ { "version": "v1", "created": "Wed, 23 Jun 2010 14:53:33 GMT" } ]
2010-06-24T00:00:00
[ [ "Suguna", "N.", "" ], [ "Thanushkodi", "K.", "" ] ]
TITLE: A Novel Rough Set Reduct Algorithm for Medical Domain Based on Bee Colony Optimization ABSTRACT: Feature selection refers to the problem of selecting relevant features which produce the most predictive outcome. In particular, feature selection task is involved in datasets containing huge number of features...
1006.3679
Hossein Mobahi
Hossein Mobahi, Shankar R. Rao, Allen Y. Yang, Shankar S. Sastry and Yi Ma
Segmentation of Natural Images by Texture and Boundary Compression
null
null
null
null
cs.CV cs.IT cs.LG math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present a novel algorithm for segmentation of natural images that harnesses the principle of minimum description length (MDL). Our method is based on observations that a homogeneously textured region of a natural image can be well modeled by a Gaussian distribution and the region boundary can be effectively coded ...
[ { "version": "v1", "created": "Fri, 18 Jun 2010 12:37:28 GMT" } ]
2010-06-21T00:00:00
[ [ "Mobahi", "Hossein", "" ], [ "Rao", "Shankar R.", "" ], [ "Yang", "Allen Y.", "" ], [ "Sastry", "Shankar S.", "" ], [ "Ma", "Yi", "" ] ]
TITLE: Segmentation of Natural Images by Texture and Boundary Compression ABSTRACT: We present a novel algorithm for segmentation of natural images that harnesses the principle of minimum description length (MDL). Our method is based on observations that a homogeneously textured region of a natural image can be wel...
1006.2734
Ariel Baya
Ariel E. Baya and Pablo M. Granitto
Penalized K-Nearest-Neighbor-Graph Based Metrics for Clustering
null
null
null
null
cs.CV
http://creativecommons.org/licenses/by-nc-sa/3.0/
A difficult problem in clustering is how to handle data with a manifold structure, i.e. data that is not shaped in the form of compact clouds of points, forming arbitrary shapes or paths embedded in a high-dimensional space. In this work we introduce the Penalized k-Nearest-Neighbor-Graph (PKNNG) based metric, a new ...
[ { "version": "v1", "created": "Mon, 14 Jun 2010 15:07:45 GMT" } ]
2010-06-15T00:00:00
[ [ "Baya", "Ariel E.", "" ], [ "Granitto", "Pablo M.", "" ] ]
TITLE: Penalized K-Nearest-Neighbor-Graph Based Metrics for Clustering ABSTRACT: A difficult problem in clustering is how to handle data with a manifold structure, i.e. data that is not shaped in the form of compact clouds of points, forming arbitrary shapes or paths embedded in a high-dimensional space. In this wo...
1005.5516
David J Brenes
David J. Brenes, Daniel Gayo-Avello and Rodrigo Garcia
On the Fly Query Entity Decomposition Using Snippets
Extended version of paper submitted to CERI 2010
null
null
null
cs.IR
http://creativecommons.org/licenses/by-nc-sa/3.0/
One of the most important issues in Information Retrieval is inferring the intents underlying users' queries. Thus, any tool to enrich or to better contextualized queries can proof extremely valuable. Entity extraction, provided it is done fast, can be one of such tools. Such techniques usually rely on a prior traini...
[ { "version": "v1", "created": "Sun, 30 May 2010 11:41:43 GMT" }, { "version": "v2", "created": "Sun, 6 Jun 2010 11:36:05 GMT" } ]
2010-06-14T00:00:00
[ [ "Brenes", "David J.", "" ], [ "Gayo-Avello", "Daniel", "" ], [ "Garcia", "Rodrigo", "" ] ]
TITLE: On the Fly Query Entity Decomposition Using Snippets ABSTRACT: One of the most important issues in Information Retrieval is inferring the intents underlying users' queries. Thus, any tool to enrich or to better contextualized queries can proof extremely valuable. Entity extraction, provided it is done fast, ...
1006.2156
Aditya Menon
Aditya Krishna Menon and Charles Elkan
Dyadic Prediction Using a Latent Feature Log-Linear Model
null
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In dyadic prediction, labels must be predicted for pairs (dyads) whose members possess unique identifiers and, sometimes, additional features called side-information. Special cases of this problem include collaborative filtering and link prediction. We present the first model for dyadic prediction that satisfies seve...
[ { "version": "v1", "created": "Thu, 10 Jun 2010 21:19:28 GMT" } ]
2010-06-14T00:00:00
[ [ "Menon", "Aditya Krishna", "" ], [ "Elkan", "Charles", "" ] ]
TITLE: Dyadic Prediction Using a Latent Feature Log-Linear Model ABSTRACT: In dyadic prediction, labels must be predicted for pairs (dyads) whose members possess unique identifiers and, sometimes, additional features called side-information. Special cases of this problem include collaborative filtering and link pre...
1006.1702
Munmun De Choudhury
Munmun De Choudhury, Hari Sundaram, Ajita John, Doree Duncan Seligmann, Aisling Kelliher
"Birds of a Feather": Does User Homophily Impact Information Diffusion in Social Media?
31 pages, 10 figures, 3 tables
null
null
null
cs.CY physics.soc-ph
http://creativecommons.org/licenses/by-nc-sa/3.0/
This article investigates the impact of user homophily on the social process of information diffusion in online social media. Over several decades, social scientists have been interested in the idea that similarity breeds connection: precisely known as "homophily". Homophily has been extensively studied in the social...
[ { "version": "v1", "created": "Wed, 9 Jun 2010 04:19:20 GMT" } ]
2010-06-10T00:00:00
[ [ "De Choudhury", "Munmun", "" ], [ "Sundaram", "Hari", "" ], [ "John", "Ajita", "" ], [ "Seligmann", "Doree Duncan", "" ], [ "Kelliher", "Aisling", "" ] ]
TITLE: "Birds of a Feather": Does User Homophily Impact Information Diffusion in Social Media? ABSTRACT: This article investigates the impact of user homophily on the social process of information diffusion in online social media. Over several decades, social scientists have been interested in the idea that simil...
1006.1328
Jonathan Huang
Jonathan Huang and Carlos Guestrin
Uncovering the Riffled Independence Structure of Rankings
65 pages
null
null
null
cs.LG cs.AI stat.AP stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Representing distributions over permutations can be a daunting task due to the fact that the number of permutations of $n$ objects scales factorially in $n$. One recent way that has been used to reduce storage complexity has been to exploit probabilistic independence, but as we argue, full independence assumptions im...
[ { "version": "v1", "created": "Mon, 7 Jun 2010 18:45:46 GMT" } ]
2010-06-08T00:00:00
[ [ "Huang", "Jonathan", "" ], [ "Guestrin", "Carlos", "" ] ]
TITLE: Uncovering the Riffled Independence Structure of Rankings ABSTRACT: Representing distributions over permutations can be a daunting task due to the fact that the number of permutations of $n$ objects scales factorially in $n$. One recent way that has been used to reduce storage complexity has been to exploit ...
1005.0390
Adam Gauci
Adam Gauci, Kristian Zarb Adami, John Abela
Machine Learning for Galaxy Morphology Classification
null
null
null
null
astro-ph.GA cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this work, decision tree learning algorithms and fuzzy inferencing systems are applied for galaxy morphology classification. In particular, the CART, the C4.5, the Random Forest and fuzzy logic algorithms are studied and reliable classifiers are developed to distinguish between spiral galaxies, elliptical galaxies...
[ { "version": "v1", "created": "Mon, 3 May 2010 20:01:38 GMT" }, { "version": "v2", "created": "Tue, 1 Jun 2010 07:54:29 GMT" } ]
2010-06-02T00:00:00
[ [ "Gauci", "Adam", "" ], [ "Adami", "Kristian Zarb", "" ], [ "Abela", "John", "" ] ]
TITLE: Machine Learning for Galaxy Morphology Classification ABSTRACT: In this work, decision tree learning algorithms and fuzzy inferencing systems are applied for galaxy morphology classification. In particular, the CART, the C4.5, the Random Forest and fuzzy logic algorithms are studied and reliable classifiers ...
1005.4963
Anon Plangprasopchok
Anon Plangprasopchok, Kristina Lerman, Lise Getoor
Integrating Structured Metadata with Relational Affinity Propagation
6 Pages, To appear at AAAI Workshop on Statistical Relational AI
null
null
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Structured and semi-structured data describing entities, taxonomies and ontologies appears in many domains. There is a huge interest in integrating structured information from multiple sources; however integrating structured data to infer complex common structures is a difficult task because the integration must aggr...
[ { "version": "v1", "created": "Wed, 26 May 2010 23:13:05 GMT" } ]
2010-05-28T00:00:00
[ [ "Plangprasopchok", "Anon", "" ], [ "Lerman", "Kristina", "" ], [ "Getoor", "Lise", "" ] ]
TITLE: Integrating Structured Metadata with Relational Affinity Propagation ABSTRACT: Structured and semi-structured data describing entities, taxonomies and ontologies appears in many domains. There is a huge interest in integrating structured information from multiple sources; however integrating structured data ...
1005.5035
Mark Edgington
Mark Edgington, Yohannes Kassahun and Frank Kirchner
Dynamic Motion Modelling for Legged Robots
null
null
10.1109/IROS.2009.5354026
null
cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
An accurate motion model is an important component in modern-day robotic systems, but building such a model for a complex system often requires an appreciable amount of manual effort. In this paper we present a motion model representation, the Dynamic Gaussian Mixture Model (DGMM), that alleviates the need to manuall...
[ { "version": "v1", "created": "Thu, 27 May 2010 11:41:36 GMT" } ]
2010-05-28T00:00:00
[ [ "Edgington", "Mark", "" ], [ "Kassahun", "Yohannes", "" ], [ "Kirchner", "Frank", "" ] ]
TITLE: Dynamic Motion Modelling for Legged Robots ABSTRACT: An accurate motion model is an important component in modern-day robotic systems, but building such a model for a complex system often requires an appreciable amount of manual effort. In this paper we present a motion model representation, the Dynamic Gaus...
1005.4454
Bruce Berriman
Joseph C. Jacob, Daniel S. Katz, G. Bruce Berriman, John Good, Anastasia C. Laity, Ewa Deelman, Carl Kesselman, Gurmeet Singh, Mei-Hui Su, Thomas A. Prince, Roy Williams
Montage: a grid portal and software toolkit for science-grade astronomical image mosaicking
16 pages, 11 figures
Int. J. Computational Science and Engineering. 2009
null
null
astro-ph.IM cs.DC cs.SE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Montage is a portable software toolkit for constructing custom, science-grade mosaics by composing multiple astronomical images. The mosaics constructed by Montage preserve the astrometry (position) and photometry (intensity) of the sources in the input images. The mosaic to be constructed is specified by the user in...
[ { "version": "v1", "created": "Mon, 24 May 2010 23:28:51 GMT" } ]
2010-05-26T00:00:00
[ [ "Jacob", "Joseph C.", "" ], [ "Katz", "Daniel S.", "" ], [ "Berriman", "G. Bruce", "" ], [ "Good", "John", "" ], [ "Laity", "Anastasia C.", "" ], [ "Deelman", "Ewa", "" ], [ "Kesselman", "Carl", "" ], [...
TITLE: Montage: a grid portal and software toolkit for science-grade astronomical image mosaicking ABSTRACT: Montage is a portable software toolkit for constructing custom, science-grade mosaics by composing multiple astronomical images. The mosaics constructed by Montage preserve the astrometry (position) and ph...
0906.2883
Petr Chaloupka
Petr Chaloupka, Pavel Jakl, Jan Kapit\'an, J\'er\^ome Lauret and Michal Zerola
Setting up a STAR Tier 2 Site at Golias/Prague Farm
To appear in proceedings of Computing in High Energy and Nuclear Physics 2009
J.Phys.Conf.Ser.219:072031,2010
10.1088/1742-6596/219/7/072031
null
physics.comp-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
High Energy Nuclear Physics (HENP) collaborations' experience show that the computing resources available at a single site are often neither sufficient nor satisfy the need of remote collaborators. From latencies in the network connectivity to the lack of interactivity, work at distant computing centers is often inef...
[ { "version": "v1", "created": "Tue, 16 Jun 2009 09:43:25 GMT" }, { "version": "v2", "created": "Thu, 18 Jun 2009 09:55:28 GMT" } ]
2010-05-25T00:00:00
[ [ "Chaloupka", "Petr", "" ], [ "Jakl", "Pavel", "" ], [ "Kapitán", "Jan", "" ], [ "Lauret", "Jérôme", "" ], [ "Zerola", "Michal", "" ] ]
TITLE: Setting up a STAR Tier 2 Site at Golias/Prague Farm ABSTRACT: High Energy Nuclear Physics (HENP) collaborations' experience show that the computing resources available at a single site are often neither sufficient nor satisfy the need of remote collaborators. From latencies in the network connectivity to the...
1005.4270
Chriss Romy
V.Kavitha, M. Punithavalli
Clustering Time Series Data Stream - A Literature Survey
IEEE Publication format, International Journal of Computer Science and Information Security, IJCSIS, Vol. 8 No. 1, April 2010, USA. ISSN 1947 5500, http://sites.google.com/site/ijcsis/
null
null
null
cs.IR
http://creativecommons.org/licenses/by-nc-sa/3.0/
Mining Time Series data has a tremendous growth of interest in today's world. To provide an indication various implementations are studied and summarized to identify the different problems in existing applications. Clustering time series is a trouble that has applications in an extensive assortment of fields and has ...
[ { "version": "v1", "created": "Mon, 24 May 2010 07:41:29 GMT" } ]
2010-05-25T00:00:00
[ [ "Kavitha", "V.", "" ], [ "Punithavalli", "M.", "" ] ]
TITLE: Clustering Time Series Data Stream - A Literature Survey ABSTRACT: Mining Time Series data has a tremendous growth of interest in today's world. To provide an indication various implementations are studied and summarized to identify the different problems in existing applications. Clustering time series is a...
1005.0919
Rdv Ijcsis
Dewan Md. Farid, Mohammad Zahidur Rahman
Attribute Weighting with Adaptive NBTree for Reducing False Positives in Intrusion Detection
IEEE Publication format, International Journal of Computer Science and Information Security, IJCSIS, Vol. 8 No. 1, April 2010, USA. ISSN 1947 5500, http://sites.google.com/site/ijcsis/
null
null
null
cs.CR
http://creativecommons.org/licenses/by-nc-sa/3.0/
In this paper, we introduce new learning algorithms for reducing false positives in intrusion detection. It is based on decision tree-based attribute weighting with adaptive na\"ive Bayesian tree, which not only reduce the false positives (FP) at acceptable level, but also scale up the detection rates (DR) for differ...
[ { "version": "v1", "created": "Thu, 6 May 2010 08:07:01 GMT" } ]
2010-05-07T00:00:00
[ [ "Farid", "Dewan Md.", "" ], [ "Rahman", "Mohammad Zahidur", "" ] ]
TITLE: Attribute Weighting with Adaptive NBTree for Reducing False Positives in Intrusion Detection ABSTRACT: In this paper, we introduce new learning algorithms for reducing false positives in intrusion detection. It is based on decision tree-based attribute weighting with adaptive na\"ive Bayesian tree, which n...
1005.0268
Andri Mirzal M.Sc.
Andri Mirzal and Masashi Furukawa
Node-Context Network Clustering using PARAFAC Tensor Decomposition
6 pages, 4 figures, International Conference on Information & Communication Technology and Systems
null
null
null
cs.IR
http://creativecommons.org/licenses/by-nc-sa/3.0/
We describe a clustering method for labeled link network (semantic graph) that can be used to group important nodes (highly connected nodes) with their relevant link's labels by using PARAFAC tensor decomposition. In this kind of network, the adjacency matrix can not be used to fully describe all information about th...
[ { "version": "v1", "created": "Mon, 3 May 2010 12:28:42 GMT" } ]
2010-05-04T00:00:00
[ [ "Mirzal", "Andri", "" ], [ "Furukawa", "Masashi", "" ] ]
TITLE: Node-Context Network Clustering using PARAFAC Tensor Decomposition ABSTRACT: We describe a clustering method for labeled link network (semantic graph) that can be used to group important nodes (highly connected nodes) with their relevant link's labels by using PARAFAC tensor decomposition. In this kind of ne...
1004.4965
Mikhail Zaslavskiy
Mikhail Zaslavskiy (CBIO), Francis Bach (INRIA Rocquencourt, LIENS), Jean-Philippe Vert (CBIO)
Many-to-Many Graph Matching: a Continuous Relaxation Approach
19
null
null
null
stat.ML cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Graphs provide an efficient tool for object representation in various computer vision applications. Once graph-based representations are constructed, an important question is how to compare graphs. This problem is often formulated as a graph matching problem where one seeks a mapping between vertices of two graphs wh...
[ { "version": "v1", "created": "Wed, 28 Apr 2010 07:46:55 GMT" } ]
2010-04-30T00:00:00
[ [ "Zaslavskiy", "Mikhail", "", "CBIO" ], [ "Bach", "Francis", "", "INRIA Rocquencourt, LIENS" ], [ "Vert", "Jean-Philippe", "", "CBIO" ] ]
TITLE: Many-to-Many Graph Matching: a Continuous Relaxation Approach ABSTRACT: Graphs provide an efficient tool for object representation in various computer vision applications. Once graph-based representations are constructed, an important question is how to compare graphs. This problem is often formulated as a g...
1004.5370
Dell Zhang
Dell Zhang, Jun Wang, Deng Cai, Jinsong Lu
Self-Taught Hashing for Fast Similarity Search
null
null
null
null
cs.IR
http://creativecommons.org/licenses/by/3.0/
The ability of fast similarity search at large scale is of great importance to many Information Retrieval (IR) applications. A promising way to accelerate similarity search is semantic hashing which designs compact binary codes for a large number of documents so that semantically similar documents are mapped to simil...
[ { "version": "v1", "created": "Thu, 29 Apr 2010 19:25:17 GMT" } ]
2010-04-30T00:00:00
[ [ "Zhang", "Dell", "" ], [ "Wang", "Jun", "" ], [ "Cai", "Deng", "" ], [ "Lu", "Jinsong", "" ] ]
TITLE: Self-Taught Hashing for Fast Similarity Search ABSTRACT: The ability of fast similarity search at large scale is of great importance to many Information Retrieval (IR) applications. A promising way to accelerate similarity search is semantic hashing which designs compact binary codes for a large number of do...
1002.3724
Francesco Silvestri
Sara Nasso (1), Francesco Silvestri (1), Francesco Tisiot (1), Barbara Di Camillo (1), Andrea Pietracaprina (1) and Gianna Maria Toffolo (1) ((1) Department of Information Engineering, University of Padova)
An Optimized Data Structure for High Throughput 3D Proteomics Data: mzRTree
Paper details: 10 pages, 7 figures, 2 tables. To be published in Journal of Proteomics. Source code available at http://www.dei.unipd.it/mzrtree
Journal of Proteomics 73(6) (2010) 1176-1182
10.1016/j.jprot.2010.02.006
null
cs.CE cs.DS q-bio.QM
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
As an emerging field, MS-based proteomics still requires software tools for efficiently storing and accessing experimental data. In this work, we focus on the management of LC-MS data, which are typically made available in standard XML-based portable formats. The structures that are currently employed to manage these...
[ { "version": "v1", "created": "Fri, 19 Feb 2010 17:17:02 GMT" }, { "version": "v2", "created": "Mon, 22 Feb 2010 08:18:47 GMT" } ]
2010-04-27T00:00:00
[ [ "Nasso", "Sara", "" ], [ "Silvestri", "Francesco", "" ], [ "Tisiot", "Francesco", "" ], [ "Di Camillo", "Barbara", "" ], [ "Pietracaprina", "Andrea", "" ], [ "Toffolo", "Gianna Maria", "" ] ]
TITLE: An Optimized Data Structure for High Throughput 3D Proteomics Data: mzRTree ABSTRACT: As an emerging field, MS-based proteomics still requires software tools for efficiently storing and accessing experimental data. In this work, we focus on the management of LC-MS data, which are typically made available i...
1004.3568
Vishal Goyal
Vikram Singh, Sapna Nagpal
Integrating User's Domain Knowledge with Association Rule Mining
International Journal of Computer Science Issues online at http://ijcsi.org/articles/Integrating-Users-Domain-Knowledge-with-Association-Rule-Mining.php
IJCSI, Volume 7, Issue 2, March 2010
null
null
cs.DB cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper presents a variation of Apriori algorithm that includes the role of domain expert to guide and speed up the overall knowledge discovery task. Usually, the user is interested in finding relationships between certain attributes instead of the whole dataset. Moreover, he can help the mining algorithm to selec...
[ { "version": "v1", "created": "Tue, 20 Apr 2010 20:37:32 GMT" } ]
2010-04-22T00:00:00
[ [ "Singh", "Vikram", "" ], [ "Nagpal", "Sapna", "" ] ]
TITLE: Integrating User's Domain Knowledge with Association Rule Mining ABSTRACT: This paper presents a variation of Apriori algorithm that includes the role of domain expert to guide and speed up the overall knowledge discovery task. Usually, the user is interested in finding relationships between certain attribut...
0906.4582
Patrick J. Wolfe
Mohamed-Ali Belabbas and Patrick J. Wolfe
On landmark selection and sampling in high-dimensional data analysis
18 pages, 6 figures, submitted for publication
Philosophical Transactions of the Royal Society, Series A, vol. 367, pp. 4295-4312, 2009
10.1098/rsta.2009.0161
null
stat.ML cs.CV cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In recent years, the spectral analysis of appropriately defined kernel matrices has emerged as a principled way to extract the low-dimensional structure often prevalent in high-dimensional data. Here we provide an introduction to spectral methods for linear and nonlinear dimension reduction, emphasizing ways to overc...
[ { "version": "v1", "created": "Wed, 24 Jun 2009 23:40:22 GMT" } ]
2010-04-20T00:00:00
[ [ "Belabbas", "Mohamed-Ali", "" ], [ "Wolfe", "Patrick J.", "" ] ]
TITLE: On landmark selection and sampling in high-dimensional data analysis ABSTRACT: In recent years, the spectral analysis of appropriately defined kernel matrices has emerged as a principled way to extract the low-dimensional structure often prevalent in high-dimensional data. Here we provide an introduction to ...
1004.3175
Eva Kranz
Eva Kranz
Structural Stability and Immunogenicity of Peptides
null
null
null
null
q-bio.BM cs.CG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We investigated the role of peptide folding stability in peptide immunogenicity. It was the aim of this thesis to implement a stability criterion based on energy computations using an AMBER force field, and to test the implementation with a large dataset.
[ { "version": "v1", "created": "Mon, 19 Apr 2010 12:43:55 GMT" } ]
2010-04-20T00:00:00
[ [ "Kranz", "Eva", "" ] ]
TITLE: Structural Stability and Immunogenicity of Peptides ABSTRACT: We investigated the role of peptide folding stability in peptide immunogenicity. It was the aim of this thesis to implement a stability criterion based on energy computations using an AMBER force field, and to test the implementation with a large ...
1004.2447
Jeremy Faden Mr.
J. Faden, R. S. Weigel, J. Merka, R. H. W. Friedel
Autoplot: A browser for scientific data on the web
16 pages
null
10.1007/s12145-010-0049-0
null
cs.GR physics.data-an physics.space-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Autoplot is software developed for the Virtual Observatories in Heliophysics to provide intelligent and automated plotting capabilities for many typical data products that are stored in a variety of file formats or databases. Autoplot has proven to be a flexible tool for exploring, accessing, and viewing data resourc...
[ { "version": "v1", "created": "Wed, 14 Apr 2010 16:40:41 GMT" } ]
2010-04-15T00:00:00
[ [ "Faden", "J.", "" ], [ "Weigel", "R. S.", "" ], [ "Merka", "J.", "" ], [ "Friedel", "R. H. W.", "" ] ]
TITLE: Autoplot: A browser for scientific data on the web ABSTRACT: Autoplot is software developed for the Virtual Observatories in Heliophysics to provide intelligent and automated plotting capabilities for many typical data products that are stored in a variety of file formats or databases. Autoplot has proven to...
1004.1743
Rdv Ijcsis
G. Nathiya, S. C. Punitha, M. Punithavalli
An Analytical Study on Behavior of Clusters Using K Means, EM and K* Means Algorithm
IEEE Publication format, ISSN 1947 5500, http://sites.google.com/site/ijcsis/
IJCSIS, Vol. 7 No. 3, March 2010, 185-190
null
null
cs.LG cs.IR
http://creativecommons.org/licenses/by-nc-sa/3.0/
Clustering is an unsupervised learning method that constitutes a cornerstone of an intelligent data analysis process. It is used for the exploration of inter-relationships among a collection of patterns, by organizing them into homogeneous clusters. Clustering has been dynamically applied to a variety of tasks in the...
[ { "version": "v1", "created": "Sat, 10 Apr 2010 21:58:16 GMT" } ]
2010-04-13T00:00:00
[ [ "Nathiya", "G.", "" ], [ "Punitha", "S. C.", "" ], [ "Punithavalli", "M.", "" ] ]
TITLE: An Analytical Study on Behavior of Clusters Using K Means, EM and K* Means Algorithm ABSTRACT: Clustering is an unsupervised learning method that constitutes a cornerstone of an intelligent data analysis process. It is used for the exploration of inter-relationships among a collection of patterns, by organ...
1004.1982
Dar\'io Garc\'ia-Garc\'ia
Dar\'io Garc\'ia-Garc\'ia and Emilio Parrado-Hern\'andez and Fernando D\'iaz-de-Mar\'ia
State-Space Dynamics Distance for Clustering Sequential Data
null
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper proposes a novel similarity measure for clustering sequential data. We first construct a common state-space by training a single probabilistic model with all the sequences in order to get a unified representation for the dataset. Then, distances are obtained attending to the transition matrices induced by ...
[ { "version": "v1", "created": "Fri, 9 Apr 2010 09:36:28 GMT" } ]
2010-04-13T00:00:00
[ [ "García-García", "Darío", "" ], [ "Parrado-Hernández", "Emilio", "" ], [ "Díaz-de-María", "Fernando", "" ] ]
TITLE: State-Space Dynamics Distance for Clustering Sequential Data ABSTRACT: This paper proposes a novel similarity measure for clustering sequential data. We first construct a common state-space by training a single probabilistic model with all the sequences in order to get a unified representation for the datase...
1002.1587
Valiya Hamza M
V. M. Hamza, R. R. Cardoso, C. H. Alexandrino
A Magma Accretion Model for the Formation of Oceanic Lithosphere: Implications for Global Heat Loss
45 pages, 11 figures
null
null
null
physics.geo-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A simple magma accretion model of the oceanic lithosphere is proposed and its implications for understanding the thermal field of oceanic lithosphere examined. The new model (designated VBA) assumes existence of lateral variations in magma accretion rates and temperatures at the boundary zone between the lithosphere ...
[ { "version": "v1", "created": "Mon, 8 Feb 2010 12:25:20 GMT" }, { "version": "v2", "created": "Wed, 7 Apr 2010 10:39:10 GMT" } ]
2010-04-08T00:00:00
[ [ "Hamza", "V. M.", "" ], [ "Cardoso", "R. R.", "" ], [ "Alexandrino", "C. H.", "" ] ]
TITLE: A Magma Accretion Model for the Formation of Oceanic Lithosphere: Implications for Global Heat Loss ABSTRACT: A simple magma accretion model of the oceanic lithosphere is proposed and its implications for understanding the thermal field of oceanic lithosphere examined. The new model (designated VBA) assume...
1004.0456
Fabrice Rossi
Georges H\'ebrail and Bernard Hugueney and Yves Lechevallier and Fabrice Rossi
Exploratory Analysis of Functional Data via Clustering and Optimal Segmentation
null
Neurocomputing, Volume 73, Issues 7-9, March 2010, Pages 1125-1141
10.1016/j.neucom.2009.11.022
null
stat.ML cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We propose in this paper an exploratory analysis algorithm for functional data. The method partitions a set of functions into $K$ clusters and represents each cluster by a simple prototype (e.g., piecewise constant). The total number of segments in the prototypes, $P$, is chosen by the user and optimally distributed ...
[ { "version": "v1", "created": "Sat, 3 Apr 2010 16:28:47 GMT" } ]
2010-04-06T00:00:00
[ [ "Hébrail", "Georges", "" ], [ "Hugueney", "Bernard", "" ], [ "Lechevallier", "Yves", "" ], [ "Rossi", "Fabrice", "" ] ]
TITLE: Exploratory Analysis of Functional Data via Clustering and Optimal Segmentation ABSTRACT: We propose in this paper an exploratory analysis algorithm for functional data. The method partitions a set of functions into $K$ clusters and represents each cluster by a simple prototype (e.g., piecewise constant). ...
1003.5886
Sandip Rakshit
Sandip Rakshit, Subhadip Basu
Development of a multi-user handwriting recognition system using Tesseract open source OCR engine
Proc. International Conference on C3IT (2009) 240-247
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The objective of the paper is to recognize handwritten samples of lower case Roman script using Tesseract open source Optical Character Recognition (OCR) engine under Apache License 2.0. Handwritten data samples containing isolated and free-flow text were collected from different users. Tesseract is trained with user...
[ { "version": "v1", "created": "Tue, 30 Mar 2010 18:22:44 GMT" } ]
2010-03-31T00:00:00
[ [ "Rakshit", "Sandip", "" ], [ "Basu", "Subhadip", "" ] ]
TITLE: Development of a multi-user handwriting recognition system using Tesseract open source OCR engine ABSTRACT: The objective of the paper is to recognize handwritten samples of lower case Roman script using Tesseract open source Optical Character Recognition (OCR) engine under Apache License 2.0. Handwritten ...
1003.5897
Sandip Rakshit
Sandip Rakshit, Debkumar Ghosal, Tanmoy Das, Subhrajit Dutta, Subhadip Basu
Development of a Multi-User Recognition Engine for Handwritten Bangla Basic Characters and Digits
Proc. (CD) Int. Conf. on Information Technology and Business Intelligence (2009)
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The objective of the paper is to recognize handwritten samples of basic Bangla characters using Tesseract open source Optical Character Recognition (OCR) engine under Apache License 2.0. Handwritten data samples containing isolated Bangla basic characters and digits were collected from different users. Tesseract is t...
[ { "version": "v1", "created": "Tue, 30 Mar 2010 18:54:57 GMT" } ]
2010-03-31T00:00:00
[ [ "Rakshit", "Sandip", "" ], [ "Ghosal", "Debkumar", "" ], [ "Das", "Tanmoy", "" ], [ "Dutta", "Subhrajit", "" ], [ "Basu", "Subhadip", "" ] ]
TITLE: Development of a Multi-User Recognition Engine for Handwritten Bangla Basic Characters and Digits ABSTRACT: The objective of the paper is to recognize handwritten samples of basic Bangla characters using Tesseract open source Optical Character Recognition (OCR) engine under Apache License 2.0. Handwritten ...
1003.5898
Sandip Rakshit
Sandip Rakshit, Amitava Kundu, Mrinmoy Maity, Subhajit Mandal, Satwika Sarkar, Subhadip Basu
Recognition of handwritten Roman Numerals using Tesseract open source OCR engine
Proc. Int. Conf. on Advances in Computer Vision and Information Technology (2009) 572-577
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The objective of the paper is to recognize handwritten samples of Roman numerals using Tesseract open source Optical Character Recognition (OCR) engine. Tesseract is trained with data samples of different persons to generate one user-independent language model, representing the handwritten Roman digit-set. The system...
[ { "version": "v1", "created": "Tue, 30 Mar 2010 18:59:49 GMT" } ]
2010-03-31T00:00:00
[ [ "Rakshit", "Sandip", "" ], [ "Kundu", "Amitava", "" ], [ "Maity", "Mrinmoy", "" ], [ "Mandal", "Subhajit", "" ], [ "Sarkar", "Satwika", "" ], [ "Basu", "Subhadip", "" ] ]
TITLE: Recognition of handwritten Roman Numerals using Tesseract open source OCR engine ABSTRACT: The objective of the paper is to recognize handwritten samples of Roman numerals using Tesseract open source Optical Character Recognition (OCR) engine. Tesseract is trained with data samples of different persons to ...
1002.4007
William Jackson
Ram Sarkar, Nibaran Das, Subhadip Basu, Mahantapas Kundu, Mita Nasipuri, Dipak Kumar Basu
Word level Script Identification from Bangla and Devanagri Handwritten Texts mixed with Roman Script
null
Journal of Computing, Volume 2, Issue 2, February 2010, https://sites.google.com/site/journalofcomputing/
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
India is a multi-lingual country where Roman script is often used alongside different Indic scripts in a text document. To develop a script specific handwritten Optical Character Recognition (OCR) system, it is therefore necessary to identify the scripts of handwritten text correctly. In this paper, we present a syst...
[ { "version": "v1", "created": "Sun, 21 Feb 2010 19:48:16 GMT" } ]
2010-03-25T00:00:00
[ [ "Sarkar", "Ram", "" ], [ "Das", "Nibaran", "" ], [ "Basu", "Subhadip", "" ], [ "Kundu", "Mahantapas", "" ], [ "Nasipuri", "Mita", "" ], [ "Basu", "Dipak Kumar", "" ] ]
TITLE: Word level Script Identification from Bangla and Devanagri Handwritten Texts mixed with Roman Script ABSTRACT: India is a multi-lingual country where Roman script is often used alongside different Indic scripts in a text document. To develop a script specific handwritten Optical Character Recognition (OCR)...
1002.4048
William Jackson
Satadal Saha, Subhadip Basu, Mita Nasipuri, Dipak Kr. Basu
A Hough Transform based Technique for Text Segmentation
null
Journal of Computing, Volume 2, Issue 2, February 2010, https://sites.google.com/site/journalofcomputing/
null
null
cs.IR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Text segmentation is an inherent part of an OCR system irrespective of the domain of application of it. The OCR system contains a segmentation module where the text lines, words and ultimately the characters must be segmented properly for its successful recognition. The present work implements a Hough transform based...
[ { "version": "v1", "created": "Mon, 22 Feb 2010 03:16:55 GMT" } ]
2010-03-23T00:00:00
[ [ "Saha", "Satadal", "" ], [ "Basu", "Subhadip", "" ], [ "Nasipuri", "Mita", "" ], [ "Basu", "Dipak Kr.", "" ] ]
TITLE: A Hough Transform based Technique for Text Segmentation ABSTRACT: Text segmentation is an inherent part of an OCR system irrespective of the domain of application of it. The OCR system contains a segmentation module where the text lines, words and ultimately the characters must be segmented properly for its ...
0812.5064
Qiang Li
Qiang Li, Zhuo Chen, Yan He, Jing-ping Jiang
A Novel Clustering Algorithm Based Upon Games on Evolving Network
17 pages, 5 figures, 3 tables
Expert Systems with Applications, 2010
10.1016/j.eswa.2010.02.050
null
cs.LG cs.CV cs.GT nlin.AO
http://creativecommons.org/licenses/by-nc-sa/3.0/
This paper introduces a model based upon games on an evolving network, and develops three clustering algorithms according to it. In the clustering algorithms, data points for clustering are regarded as players who can make decisions in games. On the network describing relationships among data points, an edge-removing...
[ { "version": "v1", "created": "Tue, 30 Dec 2008 13:22:31 GMT" }, { "version": "v2", "created": "Fri, 19 Mar 2010 13:30:08 GMT" } ]
2010-03-22T00:00:00
[ [ "Li", "Qiang", "" ], [ "Chen", "Zhuo", "" ], [ "He", "Yan", "" ], [ "Jiang", "Jing-ping", "" ] ]
TITLE: A Novel Clustering Algorithm Based Upon Games on Evolving Network ABSTRACT: This paper introduces a model based upon games on an evolving network, and develops three clustering algorithms according to it. In the clustering algorithms, data points for clustering are regarded as players who can make decisions ...
1003.2424
Jure Leskovec
Jure Leskovec, Daniel Huttenlocher, Jon Kleinberg
Signed Networks in Social Media
null
CHI 2010: 28th ACM Conference on Human Factors in Computing Systems
null
null
physics.soc-ph cs.CY cs.HC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Relations between users on social media sites often reflect a mixture of positive (friendly) and negative (antagonistic) interactions. In contrast to the bulk of research on social networks that has focused almost exclusively on positive interpretations of links between people, we study how the interplay between posi...
[ { "version": "v1", "created": "Thu, 11 Mar 2010 21:11:26 GMT" } ]
2010-03-15T00:00:00
[ [ "Leskovec", "Jure", "" ], [ "Huttenlocher", "Daniel", "" ], [ "Kleinberg", "Jon", "" ] ]
TITLE: Signed Networks in Social Media ABSTRACT: Relations between users on social media sites often reflect a mixture of positive (friendly) and negative (antagonistic) interactions. In contrast to the bulk of research on social networks that has focused almost exclusively on positive interpretations of links betw...
1003.2429
Jure Leskovec
Jure Leskovec, Daniel Huttenlocher, Jon Kleinberg
Predicting Positive and Negative Links in Online Social Networks
null
WWW 2010: ACM WWW International conference on World Wide Web, 2010
null
null
physics.soc-ph cs.AI cs.CY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We study online social networks in which relationships can be either positive (indicating relations such as friendship) or negative (indicating relations such as opposition or antagonism). Such a mix of positive and negative links arise in a variety of online settings; we study datasets from Epinions, Slashdot and Wi...
[ { "version": "v1", "created": "Thu, 11 Mar 2010 21:27:11 GMT" } ]
2010-03-15T00:00:00
[ [ "Leskovec", "Jure", "" ], [ "Huttenlocher", "Daniel", "" ], [ "Kleinberg", "Jon", "" ] ]
TITLE: Predicting Positive and Negative Links in Online Social Networks ABSTRACT: We study online social networks in which relationships can be either positive (indicating relations such as friendship) or negative (indicating relations such as opposition or antagonism). Such a mix of positive and negative links ari...
0909.3472
J\'er\^oAme Kunegis
J\'er\^ome Kunegis, Alan Said, Winfried Umbrath
The Universal Recommender
17 pages; typo and references fixed
null
null
null
cs.IR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We describe the Universal Recommender, a recommender system for semantic datasets that generalizes domain-specific recommenders such as content-based, collaborative, social, bibliographic, lexicographic, hybrid and other recommenders. In contrast to existing recommender systems, the Universal Recommender applies to a...
[ { "version": "v1", "created": "Fri, 18 Sep 2009 15:54:51 GMT" }, { "version": "v2", "created": "Tue, 9 Mar 2010 12:43:28 GMT" } ]
2010-03-13T00:00:00
[ [ "Kunegis", "Jérôme", "" ], [ "Said", "Alan", "" ], [ "Umbrath", "Winfried", "" ] ]
TITLE: The Universal Recommender ABSTRACT: We describe the Universal Recommender, a recommender system for semantic datasets that generalizes domain-specific recommenders such as content-based, collaborative, social, bibliographic, lexicographic, hybrid and other recommenders. In contrast to existing recommender sy...
1003.1814
Rdv Ijcsis
Alok Ranjan, Harish Verma, Eatesh Kandpal, Joydip Dhar
An Analytical Approach to Document Clustering Based on Internal Criterion Function
Pages IEEE format, International Journal of Computer Science and Information Security, IJCSIS, Vol. 7 No. 2, February 2010, USA. ISSN 1947 5500, http://sites.google.com/site/ijcsis/
null
null
null
cs.IR
http://creativecommons.org/licenses/by-nc-sa/3.0/
Fast and high quality document clustering is an important task in organizing information, search engine results obtaining from user query, enhancing web crawling and information retrieval. With the large amount of data available and with a goal of creating good quality clusters, a variety of algorithms have been deve...
[ { "version": "v1", "created": "Tue, 9 Mar 2010 07:28:07 GMT" } ]
2010-03-11T00:00:00
[ [ "Ranjan", "Alok", "" ], [ "Verma", "Harish", "" ], [ "Kandpal", "Eatesh", "" ], [ "Dhar", "Joydip", "" ] ]
TITLE: An Analytical Approach to Document Clustering Based on Internal Criterion Function ABSTRACT: Fast and high quality document clustering is an important task in organizing information, search engine results obtaining from user query, enhancing web crawling and information retrieval. With the large amount of ...
1003.1795
Rdv Ijcsis
Vidhya. K. A, G. Aghila
A Survey of Na\"ive Bayes Machine Learning approach in Text Document Classification
Pages IEEE format, International Journal of Computer Science and Information Security, IJCSIS, Vol. 7 No. 2, February 2010, USA. ISSN 1947 5500, http://sites.google.com/site/ijcsis/
null
null
null
cs.LG cs.IR
http://creativecommons.org/licenses/by-nc-sa/3.0/
Text Document classification aims in associating one or more predefined categories based on the likelihood suggested by the training set of labeled documents. Many machine learning algorithms play a vital role in training the system with predefined categories among which Na\"ive Bayes has some intriguing facts that i...
[ { "version": "v1", "created": "Tue, 9 Mar 2010 06:41:49 GMT" } ]
2010-03-10T00:00:00
[ [ "A", "Vidhya. K.", "" ], [ "Aghila", "G.", "" ] ]
TITLE: A Survey of Na\"ive Bayes Machine Learning approach in Text Document Classification ABSTRACT: Text Document classification aims in associating one or more predefined categories based on the likelihood suggested by the training set of labeled documents. Many machine learning algorithms play a vital role in ...
0906.3585
Arnab Bhattacharya
Vishwakarma Singh, Arnab Bhattacharya, Ambuj K. Singh
Finding Significant Subregions in Large Image Databases
16 pages, 48 figures
Extending Database Technology (EDBT) 2010
null
null
cs.DB cs.CV cs.IR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Images have become an important data source in many scientific and commercial domains. Analysis and exploration of image collections often requires the retrieval of the best subregions matching a given query. The support of such content-based retrieval requires not only the formulation of an appropriate scoring funct...
[ { "version": "v1", "created": "Fri, 19 Jun 2009 06:57:51 GMT" } ]
2010-03-09T00:00:00
[ [ "Singh", "Vishwakarma", "" ], [ "Bhattacharya", "Arnab", "" ], [ "Singh", "Ambuj K.", "" ] ]
TITLE: Finding Significant Subregions in Large Image Databases ABSTRACT: Images have become an important data source in many scientific and commercial domains. Analysis and exploration of image collections often requires the retrieval of the best subregions matching a given query. The support of such content-based ...
0909.3169
Purushottam Kar
Arnab Bhattacharya, Purushottam Kar and Manjish Pal
On Low Distortion Embeddings of Statistical Distance Measures into Low Dimensional Spaces
18 pages, The short version of this paper was accepted for presentation at the 20th International Conference on Database and Expert Systems Applications, DEXA 2009
Database and Expert Systems Applications (DEXA) 2009
10.1007/978-3-642-03573-9_13
null
cs.CG cs.DB
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Statistical distance measures have found wide applicability in information retrieval tasks that typically involve high dimensional datasets. In order to reduce the storage space and ensure efficient performance of queries, dimensionality reduction while preserving the inter-point similarity is highly desirable. In th...
[ { "version": "v1", "created": "Thu, 17 Sep 2009 09:29:48 GMT" } ]
2010-03-09T00:00:00
[ [ "Bhattacharya", "Arnab", "" ], [ "Kar", "Purushottam", "" ], [ "Pal", "Manjish", "" ] ]
TITLE: On Low Distortion Embeddings of Statistical Distance Measures into Low Dimensional Spaces ABSTRACT: Statistical distance measures have found wide applicability in information retrieval tasks that typically involve high dimensional datasets. In order to reduce the storage space and ensure efficient performa...
1001.2625
Arnab Bhattacharya
Arnab Bhattacharya, Abhishek Bhowmick, Ambuj K. Singh
Finding top-k similar pairs of objects annotated with terms from an ontology
17 pages, 13 figures
null
null
null
cs.DB
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
With the growing focus on semantic searches and interpretations, an increasing number of standardized vocabularies and ontologies are being designed and used to describe data. We investigate the querying of objects described by a tree-structured ontology. Specifically, we consider the case of finding the top-k best p...
[ { "version": "v1", "created": "Fri, 15 Jan 2010 07:01:37 GMT" }, { "version": "v2", "created": "Sat, 6 Mar 2010 11:23:28 GMT" } ]
2010-03-09T00:00:00
[ [ "Bhattacharya", "Arnab", "" ], [ "Bhowmick", "Abhishek", "" ], [ "Singh", "Ambuj K.", "" ] ]
TITLE: Finding top-k similar pairs of objects annotated with terms from an ontology ABSTRACT: With the growing focus on semantic searches and interpretations, an increasing number of standardized vocabularies and ontologies are being designed and used to describe data. We investigate the querying of objects descr...
0910.0668
Ahmed Abdel-Gawad
Yuan Qi, Ahmed H. Abdel-Gawad and Thomas P. Minka
Variable sigma Gaussian processes: An expectation propagation perspective
null
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Gaussian processes (GPs) provide a probabilistic nonparametric representation of functions in regression, classification, and other problems. Unfortunately, exact learning with GPs is intractable for large datasets. A variety of approximate GP methods have been proposed that essentially map the large dataset into a s...
[ { "version": "v1", "created": "Mon, 5 Oct 2009 03:30:13 GMT" }, { "version": "v2", "created": "Wed, 7 Oct 2009 21:52:48 GMT" } ]
2010-02-23T00:00:00
[ [ "Qi", "Yuan", "" ], [ "Abdel-Gawad", "Ahmed H.", "" ], [ "Minka", "Thomas P.", "" ] ]
TITLE: Variable sigma Gaussian processes: An expectation propagation perspective ABSTRACT: Gaussian processes (GPs) provide a probabilistic nonparametric representation of functions in regression, classification, and other problems. Unfortunately, exact learning with GPs is intractable for large datasets. A varie...
1002.3195
Mahmud Hossain
M. Shahriar Hossain, Michael Narayan and Naren Ramakrishnan
Efficiently Discovering Hammock Paths from Induced Similarity Networks
null
null
null
null
cs.AI cs.DB
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Similarity networks are important abstractions in many information management applications such as recommender systems, corpora analysis, and medical informatics. For instance, by inducing similarity networks between movies rated similarly by users, or between documents containing common terms, and or between clinica...
[ { "version": "v1", "created": "Wed, 17 Feb 2010 04:07:06 GMT" } ]
2010-02-18T00:00:00
[ [ "Hossain", "M. Shahriar", "" ], [ "Narayan", "Michael", "" ], [ "Ramakrishnan", "Naren", "" ] ]
TITLE: Efficiently Discovering Hammock Paths from Induced Similarity Networks ABSTRACT: Similarity networks are important abstractions in many information management applications such as recommender systems, corpora analysis, and medical informatics. For instance, by inducing similarity networks between movies rate...
1002.2780
Ruslan Salakhutdinov
Ruslan Salakhutdinov, Nathan Srebro
Collaborative Filtering in a Non-Uniform World: Learning with the Weighted Trace Norm
9 pages
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We show that matrix completion with trace-norm regularization can be significantly hurt when entries of the matrix are sampled non-uniformly. We introduce a weighted version of the trace-norm regularizer that works well also with non-uniform sampling. Our experimental results demonstrate that the weighted trace-norm ...
[ { "version": "v1", "created": "Sun, 14 Feb 2010 16:37:04 GMT" } ]
2010-02-16T00:00:00
[ [ "Salakhutdinov", "Ruslan", "" ], [ "Srebro", "Nathan", "" ] ]
TITLE: Collaborative Filtering in a Non-Uniform World: Learning with the Weighted Trace Norm ABSTRACT: We show that matrix completion with trace-norm regularization can be significantly hurt when entries of the matrix are sampled non-uniformly. We introduce a weighted version of the trace-norm regularizer that wo...
0908.0050
Julien Mairal
Julien Mairal (INRIA Rocquencourt), Francis Bach (INRIA Rocquencourt), Jean Ponce (INRIA Rocquencourt, LIENS), Guillermo Sapiro
Online Learning for Matrix Factorization and Sparse Coding
revised version
Journal of Machine Learning Research 11 (2010) 19--60
null
null
stat.ML cs.LG math.OC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Sparse coding--that is, modelling data vectors as sparse linear combinations of basis elements--is widely used in machine learning, neuroscience, signal processing, and statistics. This paper focuses on the large-scale matrix factorization problem that consists of learning the basis set, adapting it to specific data....
[ { "version": "v1", "created": "Sat, 1 Aug 2009 06:09:18 GMT" }, { "version": "v2", "created": "Thu, 11 Feb 2010 07:33:02 GMT" } ]
2010-02-11T00:00:00
[ [ "Mairal", "Julien", "", "INRIA Rocquencourt" ], [ "Bach", "Francis", "", "INRIA Rocquencourt" ], [ "Ponce", "Jean", "", "INRIA Rocquencourt, LIENS" ], [ "Sapiro", "Guillermo", "" ] ]
TITLE: Online Learning for Matrix Factorization and Sparse Coding ABSTRACT: Sparse coding--that is, modelling data vectors as sparse linear combinations of basis elements--is widely used in machine learning, neuroscience, signal processing, and statistics. This paper focuses on the large-scale matrix factorization ...
1002.1156
Vishal Goyal
M. Babu Reddy, L. S. S. Reddy
Dimensionality Reduction: An Empirical Study on the Usability of IFE-CF (Independent Feature Elimination- by C-Correlation and F-Correlation) Measures
International Journal of Computer Science Issues, IJCSI, Vol. 7, Issue 1, No. 1, January 2010, http://ijcsi.org
International Journal of Computer Science Issues, IJCSI, Vol. 7, Issue 1, No. 1, January 2010, http://ijcsi.org/articles/Dimensionality-Reduction-An-Empirical-Study-on-the-Usability-of-IFE-CF-(Independent-Feature-Elimination-by-C-Correlation-and-F-Correlation)-Measures.php
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The recent increase in dimensionality of data has thrown a great challenge to the existing dimensionality reduction methods in terms of their effectiveness. Dimensionality reduction has emerged as one of the significant preprocessing steps in machine learning applications and has been effective in removing inappropri...
[ { "version": "v1", "created": "Fri, 5 Feb 2010 08:59:05 GMT" } ]
2010-02-10T00:00:00
[ [ "Reddy", "M. Babu", "" ], [ "Reddy", "L. S. S.", "" ] ]
TITLE: Dimensionality Reduction: An Empirical Study on the Usability of IFE-CF (Independent Feature Elimination- by C-Correlation and F-Correlation) Measures ABSTRACT: The recent increase in dimensionality of data has thrown a great challenge to the existing dimensionality reduction methods in terms of their ef...
1002.1104
Fabio Vandin
Adam Kirsch, Michael Mitzenmacher, Andrea Pietracaprina, Geppino Pucci, Eli Upfal, Fabio Vandin
An Efficient Rigorous Approach for Identifying Statistically Significant Frequent Itemsets
A preliminary version of this work was presented in ACM PODS 2009. 20 pages, 0 figures
null
null
null
cs.DB cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
As advances in technology allow for the collection, storage, and analysis of vast amounts of data, the task of screening and assessing the significance of discovered patterns is becoming a major challenge in data mining applications. In this work, we address significance in the context of frequent itemset mining. Spe...
[ { "version": "v1", "created": "Thu, 4 Feb 2010 23:33:47 GMT" } ]
2010-02-08T00:00:00
[ [ "Kirsch", "Adam", "" ], [ "Mitzenmacher", "Michael", "" ], [ "Pietracaprina", "Andrea", "" ], [ "Pucci", "Geppino", "" ], [ "Upfal", "Eli", "" ], [ "Vandin", "Fabio", "" ] ]
TITLE: An Efficient Rigorous Approach for Identifying Statistically Significant Frequent Itemsets ABSTRACT: As advances in technology allow for the collection, storage, and analysis of vast amounts of data, the task of screening and assessing the significance of discovered patterns is becoming a major challenge i...
1002.1144
Vishal Goyal
M. Ramaswami, R. Bhaskaran
A CHAID Based Performance Prediction Model in Educational Data Mining
International Journal of Computer Science Issues, IJCSI, Vol. 7, Issue 1, No. 1, January 2010, http://ijcsi.org/articles/A-CHAID-Based-Performance-Prediction-Model-in-Educational-Data-Mining.php
International Journal of Computer Science Issues, IJCSI, Vol. 7, Issue 1, No. 1, January 2010, http://ijcsi.org/articles/A-CHAID-Based-Performance-Prediction-Model-in-Educational-Data-Mining.php
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The performance in higher secondary school education in India is a turning point in the academic lives of all students. As this academic performance is influenced by many factors, it is essential to develop predictive data mining model for students' performance so as to identify the slow learners and study the influe...
[ { "version": "v1", "created": "Fri, 5 Feb 2010 08:27:17 GMT" } ]
2010-02-08T00:00:00
[ [ "Ramaswami", "M.", "" ], [ "Bhaskaran", "R.", "" ] ]
TITLE: A CHAID Based Performance Prediction Model in Educational Data Mining ABSTRACT: The performance in higher secondary school education in India is a turning point in the academic lives of all students. As this academic performance is influenced by many factors, it is essential to develop predictive data mining...
1002.0414
Dakshina Ranjan Kisku
Dakshina Ranjan Kisku, Phalguni Gupta, Jamuna Kanta Sing
Feature Level Fusion of Biometrics Cues: Human Identification with Doddingtons Caricature
8 pages, 3 figures
null
null
null
cs.CV cs.AI
http://creativecommons.org/licenses/by/3.0/
This paper presents a multimodal biometric system of fingerprint and ear biometrics. Scale Invariant Feature Transform (SIFT) descriptor based feature sets extracted from fingerprint and ear are fused. The fused set is encoded by K-medoids partitioning approach with less number of feature points in the set. K-medoids...
[ { "version": "v1", "created": "Tue, 2 Feb 2010 08:12:23 GMT" } ]
2010-02-03T00:00:00
[ [ "Kisku", "Dakshina Ranjan", "" ], [ "Gupta", "Phalguni", "" ], [ "Sing", "Jamuna Kanta", "" ] ]
TITLE: Feature Level Fusion of Biometrics Cues: Human Identification with Doddingtons Caricature ABSTRACT: This paper presents a multimodal biometric system of fingerprint and ear biometrics. Scale Invariant Feature Transform (SIFT) descriptor based feature sets extracted from fingerprint and ear are fused. The f...
0912.2548
Grigorios Loukides
Grigorios Loukides, Aris Gkoulalas-Divanis and Bradley Malin
Towards Utility-driven Anonymization of Transactions
null
null
null
null
cs.DB cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Publishing person-specific transactions in an anonymous form is increasingly required by organizations. Recent approaches ensure that potentially identifying information (e.g., a set of diagnosis codes) cannot be used to link published transactions to persons' identities, but all are limited in application because th...
[ { "version": "v1", "created": "Sun, 13 Dec 2009 23:30:24 GMT" }, { "version": "v2", "created": "Tue, 26 Jan 2010 05:26:00 GMT" } ]
2010-01-26T00:00:00
[ [ "Loukides", "Grigorios", "" ], [ "Gkoulalas-Divanis", "Aris", "" ], [ "Malin", "Bradley", "" ] ]
TITLE: Towards Utility-driven Anonymization of Transactions ABSTRACT: Publishing person-specific transactions in an anonymous form is increasingly required by organizations. Recent approaches ensure that potentially identifying information (e.g., a set of diagnosis codes) cannot be used to link published transactio...
1001.3824
Federico Sacerdoti MSc
Federico D. Sacerdoti
Performance and Fault Tolerance in the StoreTorrent Parallel Filesystem
13 pages, 7 figures
null
null
null
cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
With a goal of supporting the timely and cost-effective analysis of Terabyte datasets on commodity components, we present and evaluate StoreTorrent, a simple distributed filesystem with integrated fault tolerance for efficient handling of small data records. Our contributions include an application-OS pipelining tech...
[ { "version": "v1", "created": "Thu, 21 Jan 2010 15:17:30 GMT" } ]
2010-01-22T00:00:00
[ [ "Sacerdoti", "Federico D.", "" ] ]
TITLE: Performance and Fault Tolerance in the StoreTorrent Parallel Filesystem ABSTRACT: With a goal of supporting the timely and cost-effective analysis of Terabyte datasets on commodity components, we present and evaluate StoreTorrent, a simple distributed filesystem with integrated fault tolerance for efficient ...
1001.2921
Loet Leydesdorff
Willem Halffman and Loet Leydesdorff
Is Inequality Among Universities Increasing? Gini Coefficients and the Elusive Rise of Elite Universities
null
null
null
null
physics.soc-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
One of the unintended consequences of the New Public Management (NPM) in universities is often feared to be a division between elite institutions focused on research and large institutions with teaching missions. However, institutional isomorphisms provide counter-incentives. For example, university rankings focus on...
[ { "version": "v1", "created": "Sun, 17 Jan 2010 19:36:29 GMT" } ]
2010-01-19T00:00:00
[ [ "Halffman", "Willem", "" ], [ "Leydesdorff", "Loet", "" ] ]
TITLE: Is Inequality Among Universities Increasing? Gini Coefficients and the Elusive Rise of Elite Universities ABSTRACT: One of the unintended consequences of the New Public Management (NPM) in universities is often feared to be a division between elite institutions focused on research and large institutions wi...
1001.2922
Louis De Barros
Louis De Barros (UCD), Christopher J. Bean (UCD), Ivan Lokmer (UCD), Gilberto Saccorotti, Luciano Zucarello, Gareth O'Brien (UCD), Jean-Philippe M\'etaxian (LGIT), Domenico Patan\`e
Source geometry from exceptionally high resolution long period event observations at Mt Etna during the 2008 eruption
null
Geophysical Research Letters 36 (2009) L24305
10.1029/2009GL041273
null
physics.geo-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
During the second half of June, 2008, 50 broadband seismic stations were deployed on Mt Etna volcano in close proximity to the summit, allowing us to observe seismic activity with exceptionally high resolution. 129 long period events (LP) with dominant frequencies ranging between 0.3 and 1.2 Hz, were extracted from t...
[ { "version": "v1", "created": "Sun, 17 Jan 2010 19:43:41 GMT" } ]
2010-01-19T00:00:00
[ [ "De Barros", "Louis", "", "UCD" ], [ "Bean", "Christopher J.", "", "UCD" ], [ "Lokmer", "Ivan", "", "UCD" ], [ "Saccorotti", "Gilberto", "", "UCD" ], [ "Zucarello", "Luciano", "", "UCD" ], [ "O'Brien", "Gar...
TITLE: Source geometry from exceptionally high resolution long period event observations at Mt Etna during the 2008 eruption ABSTRACT: During the second half of June, 2008, 50 broadband seismic stations were deployed on Mt Etna volcano in close proximity to the summit, allowing us to observe seismic activity with...
1001.1221
Paolo Piro
Paolo Piro, Richard Nock, Frank Nielsen, Michel Barlaud
Boosting k-NN for categorization of natural scenes
under revision for IJCV
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The k-nearest neighbors (k-NN) classification rule has proven extremely successful in countless many computer vision applications. For example, image categorization often relies on uniform voting among the nearest prototypes in the space of descriptors. In spite of its good properties, the classic k-NN rule suffers f...
[ { "version": "v1", "created": "Fri, 8 Jan 2010 08:30:51 GMT" } ]
2010-01-11T00:00:00
[ [ "Piro", "Paolo", "" ], [ "Nock", "Richard", "" ], [ "Nielsen", "Frank", "" ], [ "Barlaud", "Michel", "" ] ]
TITLE: Boosting k-NN for categorization of natural scenes ABSTRACT: The k-nearest neighbors (k-NN) classification rule has proven extremely successful in countless many computer vision applications. For example, image categorization often relies on uniform voting among the nearest prototypes in the space of descrip...
1001.1020
Ping Li
Ping Li
An Empirical Evaluation of Four Algorithms for Multi-Class Classification: Mart, ABC-Mart, Robust LogitBoost, and ABC-LogitBoost
null
null
null
null
cs.LG cs.AI cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This empirical study is mainly devoted to comparing four tree-based boosting algorithms: mart, abc-mart, robust logitboost, and abc-logitboost, for multi-class classification on a variety of publicly available datasets. Some of those datasets have been thoroughly tested in prior studies using a broad range of classif...
[ { "version": "v1", "created": "Thu, 7 Jan 2010 06:34:21 GMT" } ]
2010-01-08T00:00:00
[ [ "Li", "Ping", "" ] ]
TITLE: An Empirical Evaluation of Four Algorithms for Multi-Class Classification: Mart, ABC-Mart, Robust LogitBoost, and ABC-LogitBoost ABSTRACT: This empirical study is mainly devoted to comparing four tree-based boosting algorithms: mart, abc-mart, robust logitboost, and abc-logitboost, for multi-class classifi...
1001.1079
Ricardo Silva
Ricardo Silva
Measuring Latent Causal Structure
null
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Discovering latent representations of the observed world has become increasingly more relevant in data analysis. Much of the effort concentrates on building latent variables which can be used in prediction problems, such as classification and regression. A related goal of learning latent structure from data is that o...
[ { "version": "v1", "created": "Thu, 7 Jan 2010 14:41:21 GMT" } ]
2010-01-08T00:00:00
[ [ "Silva", "Ricardo", "" ] ]
TITLE: Measuring Latent Causal Structure ABSTRACT: Discovering latent representations of the observed world has become increasingly more relevant in data analysis. Much of the effort concentrates on building latent variables which can be used in prediction problems, such as classification and regression. A related ...
0904.2037
Chunhua Shen
Chunhua Shen and Hanxi Li
Boosting through Optimization of Margin Distributions
9 pages. To publish/Published in IEEE Transactions on Neural Networks, 21(7), July 2010
null
null
null
cs.LG cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Boosting has attracted much research attention in the past decade. The success of boosting algorithms may be interpreted in terms of the margin theory. Recently it has been shown that generalization error of classifiers can be obtained by explicitly taking the margin distribution of the training data into account. Mo...
[ { "version": "v1", "created": "Tue, 14 Apr 2009 01:57:12 GMT" }, { "version": "v2", "created": "Tue, 17 Nov 2009 02:24:51 GMT" }, { "version": "v3", "created": "Wed, 6 Jan 2010 09:00:26 GMT" } ]
2010-01-06T00:00:00
[ [ "Shen", "Chunhua", "" ], [ "Li", "Hanxi", "" ] ]
TITLE: Boosting through Optimization of Margin Distributions ABSTRACT: Boosting has attracted much research attention in the past decade. The success of boosting algorithms may be interpreted in terms of the margin theory. Recently it has been shown that generalization error of classifiers can be obtained by explic...
0912.5426
Xiaokui Xiao
Xiaokui Xiao, Ke Yi, Yufei Tao
The Hardness and Approximation Algorithms for L-Diversity
EDBT 2010
null
null
null
cs.DB
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The existing solutions to privacy preserving publication can be classified into the theoretical and heuristic categories. The former guarantees provably low information loss, whereas the latter incurs gigantic loss in the worst case, but is shown empirically to perform well on many real inputs. While numerous heurist...
[ { "version": "v1", "created": "Wed, 30 Dec 2009 08:31:10 GMT" } ]
2009-12-31T00:00:00
[ [ "Xiao", "Xiaokui", "" ], [ "Yi", "Ke", "" ], [ "Tao", "Yufei", "" ] ]
TITLE: The Hardness and Approximation Algorithms for L-Diversity ABSTRACT: The existing solutions to privacy preserving publication can be classified into the theoretical and heuristic categories. The former guarantees provably low information loss, whereas the latter incurs gigantic loss in the worst case, but is ...
0903.3257
Marcus Hutter
Ke Zhang and Marcus Hutter and Huidong Jin
A New Local Distance-Based Outlier Detection Approach for Scattered Real-World Data
15 LaTeX pages, 7 figures, 2 tables, 1 algorithm, 2 theorems
Proc. 13th Pacific-Asia Conf. on Knowledge Discovery and Data Mining (PAKDD 2009) pages 813-822
null
null
cs.LG cs.IR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Detecting outliers which are grossly different from or inconsistent with the remaining dataset is a major challenge in real-world KDD applications. Existing outlier detection methods are ineffective on scattered real-world datasets due to implicit data patterns and parameter setting issues. We define a novel "Local D...
[ { "version": "v1", "created": "Wed, 18 Mar 2009 23:50:29 GMT" } ]
2009-12-30T00:00:00
[ [ "Zhang", "Ke", "" ], [ "Hutter", "Marcus", "" ], [ "Jin", "Huidong", "" ] ]
TITLE: A New Local Distance-Based Outlier Detection Approach for Scattered Real-World Data ABSTRACT: Detecting outliers which are grossly different from or inconsistent with the remaining dataset is a major challenge in real-world KDD applications. Existing outlier detection methods are ineffective on scattered r...
0912.3982
William Jackson
D. Bhanu, S. Pavai Madeshwari
Retail Market analysis in targeting sales based on Consumer Behaviour using Fuzzy Clustering - A Rule Based Mode
null
Journal of Computing, Volume 1, Issue 1, pp 92-99, December 2009
null
null
cs.OH
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Product Bundling and offering products to customers is of critical importance in retail marketing. In general, product bundling and offering products to customers involves two main issues, namely identification of product taste according to demography and product evaluation and selection to increase sales. The former...
[ { "version": "v1", "created": "Sun, 20 Dec 2009 05:18:57 GMT" } ]
2009-12-22T00:00:00
[ [ "Bhanu", "D.", "" ], [ "Madeshwari", "S. Pavai", "" ] ]
TITLE: Retail Market analysis in targeting sales based on Consumer Behaviour using Fuzzy Clustering - A Rule Based Mode ABSTRACT: Product Bundling and offering products to customers is of critical importance in retail marketing. In general, product bundling and offering products to customers involves two main iss...
0912.4141
Felix Moya-Anegon Dr
Borja Gonzalez-Pereira (1), Vicente Guerrero-Bote (1) and Felix Moya-Anegon (2) ((1) University of Extremadura, Department of Information and Communication, Scimago Group, Spain (2) CSIC, CCHS, IPP, Scimago Group Spain)
The SJR indicator: A new indicator of journals' scientific prestige
21 pages with graphs and tables
null
null
null
cs.DL physics.soc-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper proposes an indicator of journals' scientific prestige, the SJR indicator, for ranking scholarly journals based on citation weighting schemes and eigenvector centrality to be used in complex and heterogeneous citation networks such Scopus. Its computation methodology is described and the results after impl...
[ { "version": "v1", "created": "Mon, 21 Dec 2009 11:32:08 GMT" } ]
2009-12-22T00:00:00
[ [ "Gonzalez-Pereira", "Borja", "" ], [ "Guerrero-Bote", "Vicente", "" ], [ "Moya-Anegon", "Felix", "" ] ]
TITLE: The SJR indicator: A new indicator of journals' scientific prestige ABSTRACT: This paper proposes an indicator of journals' scientific prestige, the SJR indicator, for ranking scholarly journals based on citation weighting schemes and eigenvector centrality to be used in complex and heterogeneous citation ne...
0912.2430
Feng Xia
Feng Xia, Zhenzhen Xu, Lin Yao, Weifeng Sun, Mingchu Li
Prediction-Based Data Transmission for Energy Conservation in Wireless Body Sensors
To appear in The Int Workshop on Ubiquitous Body Sensor Networks (UBSN), in conjunction with the 5th Annual Int Wireless Internet Conf (WICON), Singapore, March 2010
null
null
null
cs.NI cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Wireless body sensors are becoming popular in healthcare applications. Since they are either worn or implanted into human body, these sensors must be very small in size and light in weight. The energy consequently becomes an extremely scarce resource, and energy conservation turns into a first class design issue for ...
[ { "version": "v1", "created": "Sat, 12 Dec 2009 16:30:14 GMT" } ]
2009-12-15T00:00:00
[ [ "Xia", "Feng", "" ], [ "Xu", "Zhenzhen", "" ], [ "Yao", "Lin", "" ], [ "Sun", "Weifeng", "" ], [ "Li", "Mingchu", "" ] ]
TITLE: Prediction-Based Data Transmission for Energy Conservation in Wireless Body Sensors ABSTRACT: Wireless body sensors are becoming popular in healthcare applications. Since they are either worn or implanted into human body, these sensors must be very small in size and light in weight. The energy consequently...
0912.0955
Rdv Ijcsis
Nazmeen Bibi Boodoo, and R. K. Subramanian
Robust Multi biometric Recognition Using Face and Ear Images
6 pages IEEE format, International Journal of Computer Science and Information Security, IJCSIS November 2009, ISSN 1947 5500, http://sites.google.com/site/ijcsis/
International Journal of Computer Science and Information Security, IJCSIS, Vol. 6, No. 2, pp. 164-169, November 2009, USA
null
ISSN 1947 5500
cs.CR cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This study investigates the use of ear as a biometric for authentication and shows experimental results obtained on a newly created dataset of 420 images. Images are passed to a quality module in order to reduce False Rejection Rate. The Principal Component Analysis (eigen ear) approach was used, obtaining 90.7 perce...
[ { "version": "v1", "created": "Fri, 4 Dec 2009 21:51:03 GMT" } ]
2009-12-08T00:00:00
[ [ "Boodoo", "Nazmeen Bibi", "" ], [ "Subramanian", "R. K.", "" ] ]
TITLE: Robust Multi biometric Recognition Using Face and Ear Images ABSTRACT: This study investigates the use of ear as a biometric for authentication and shows experimental results obtained on a newly created dataset of 420 images. Images are passed to a quality module in order to reduce False Rejection Rate. The ...
0912.1014
Rdv Ijcsis
Shailendra Singh, Sanjay Silakari
An ensemble approach for feature selection of Cyber Attack Dataset
6 pages IEEE format, International Journal of Computer Science and Information Security, IJCSIS November 2009, ISSN 1947 5500, http://sites.google.com/site/ijcsis/
International Journal of Computer Science and Information Security, IJCSIS, Vol. 6, No. 2, pp. 297-302, November 2009, USA
null
ISSN 1947 5500
cs.CR cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Feature selection is an indispensable preprocessing step when mining huge datasets that can significantly improve the overall system performance. Therefore in this paper we focus on a hybrid approach of feature selection. This method falls into two phases. The filter phase select the features with highest information...
[ { "version": "v1", "created": "Sat, 5 Dec 2009 13:15:08 GMT" } ]
2009-12-08T00:00:00
[ [ "Singh", "Shailendra", "" ], [ "Silakari", "Sanjay", "" ] ]
TITLE: An ensemble approach for feature selection of Cyber Attack Dataset ABSTRACT: Feature selection is an indispensable preprocessing step when mining huge datasets that can significantly improve the overall system performance. Therefore in this paper we focus on a hybrid approach of feature selection. This metho...
0912.0717
Karol Gregor
Karol Gregor, Gregory Griffin
Behavior and performance of the deep belief networks on image classification
8 pages, 9 figures
null
null
null
cs.NE cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We apply deep belief networks of restricted Boltzmann machines to bags of words of sift features obtained from databases of 13 Scenes, 15 Scenes and Caltech 256 and study experimentally their behavior and performance. We find that the final performance in the supervised phase is reached much faster if the system is p...
[ { "version": "v1", "created": "Thu, 3 Dec 2009 19:20:14 GMT" } ]
2009-12-04T00:00:00
[ [ "Gregor", "Karol", "" ], [ "Griffin", "Gregory", "" ] ]
TITLE: Behavior and performance of the deep belief networks on image classification ABSTRACT: We apply deep belief networks of restricted Boltzmann machines to bags of words of sift features obtained from databases of 13 Scenes, 15 Scenes and Caltech 256 and study experimentally their behavior and performance. We...
0903.2870
Patrick Erik Bradley
Patrick Erik Bradley
On $p$-adic Classification
16 pages, 7 figures, 1 table; added reference, corrected typos, minor content changes
p-Adic Numbers, Ultrametric Analysis, and Applications, Vol. 1, No. 4 (2009), 271-285
10.1134/S2070046609040013
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A $p$-adic modification of the split-LBG classification method is presented in which first clusterings and then cluster centers are computed which locally minimise an energy function. The outcome for a fixed dataset is independent of the prime number $p$ with finitely many exceptions. The methods are applied to the c...
[ { "version": "v1", "created": "Mon, 16 Mar 2009 22:52:06 GMT" }, { "version": "v2", "created": "Wed, 24 Jun 2009 14:10:45 GMT" } ]
2009-12-01T00:00:00
[ [ "Bradley", "Patrick Erik", "" ] ]
TITLE: On $p$-adic Classification ABSTRACT: A $p$-adic modification of the split-LBG classification method is presented in which first clusterings and then cluster centers are computed which locally minimise an energy function. The outcome for a fixed dataset is independent of the prime number $p$ with finitely man...
0712.2063
Vladimir Pestov
Vladimir Pestov
An axiomatic approach to intrinsic dimension of a dataset
10 pages, 5 figures, latex 2e with Elsevier macros, final submission to Neural Networks with referees' comments taken into account
Neural Networks 21, 2-3 (2008), 204-213.
null
null
cs.IR
null
We perform a deeper analysis of an axiomatic approach to the concept of intrinsic dimension of a dataset proposed by us in the IJCNN'07 paper (arXiv:cs/0703125). The main features of our approach are that a high intrinsic dimension of a dataset reflects the presence of the curse of dimensionality (in a certain mathem...
[ { "version": "v1", "created": "Wed, 12 Dec 2007 23:39:21 GMT" } ]
2009-11-17T00:00:00
[ [ "Pestov", "Vladimir", "" ] ]
TITLE: An axiomatic approach to intrinsic dimension of a dataset ABSTRACT: We perform a deeper analysis of an axiomatic approach to the concept of intrinsic dimension of a dataset proposed by us in the IJCNN'07 paper (arXiv:cs/0703125). The main features of our approach are that a high intrinsic dimension of a data...
cs/9901004
Vladimir Pestov
Vladimir Pestov
On the geometry of similarity search: dimensionality curse and concentration of measure
7 pages, LaTeX 2e
Information Processing Letters 73 (2000), 47-51.
null
RP-99-01, Victoria University of Wellington, NZ
cs.IR cs.CG cs.DB cs.DS
null
We suggest that the curse of dimensionality affecting the similarity-based search in large datasets is a manifestation of the phenomenon of concentration of measure on high-dimensional structures. We prove that, under certain geometric assumptions on the query domain $\Omega$ and the dataset $X$, if $\Omega$ satisfie...
[ { "version": "v1", "created": "Tue, 12 Jan 1999 21:56:39 GMT" } ]
2009-11-17T00:00:00
[ [ "Pestov", "Vladimir", "" ] ]
TITLE: On the geometry of similarity search: dimensionality curse and concentration of measure ABSTRACT: We suggest that the curse of dimensionality affecting the similarity-based search in large datasets is a manifestation of the phenomenon of concentration of measure on high-dimensional structures. We prove tha...