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1210.5338
Cyril Furtlehner
Cyril Furtlehner, Yufei Han, Jean-Marc Lasgouttes and Victorin Martin
Pairwise MRF Calibration by Perturbation of the Bethe Reference Point
54 pages, 8 figure. section 5 and refs added in V2
null
null
Inria RR-8059
cond-mat.dis-nn cond-mat.stat-mech cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We investigate different ways of generating approximate solutions to the pairwise Markov random field (MRF) selection problem. We focus mainly on the inverse Ising problem, but discuss also the somewhat related inverse Gaussian problem because both types of MRF are suitable for inference tasks with the belief propaga...
[ { "version": "v1", "created": "Fri, 19 Oct 2012 08:08:55 GMT" }, { "version": "v2", "created": "Fri, 1 Feb 2013 17:32:44 GMT" } ]
2013-02-04T00:00:00
[ [ "Furtlehner", "Cyril", "" ], [ "Han", "Yufei", "" ], [ "Lasgouttes", "Jean-Marc", "" ], [ "Martin", "Victorin", "" ] ]
TITLE: Pairwise MRF Calibration by Perturbation of the Bethe Reference Point ABSTRACT: We investigate different ways of generating approximate solutions to the pairwise Markov random field (MRF) selection problem. We focus mainly on the inverse Ising problem, but discuss also the somewhat related inverse Gaussian p...
1111.5534
Lazaros Gallos
Lazaros K. Gallos, Diego Rybski, Fredrik Liljeros, Shlomo Havlin, Hernan A. Makse
How people interact in evolving online affiliation networks
10 pages, 8 figures
Phys. Rev. X 2, 031014 (2012)
null
null
physics.soc-ph cs.SI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The study of human interactions is of central importance for understanding the behavior of individuals, groups and societies. Here, we observe the formation and evolution of networks by monitoring the addition of all new links and we analyze quantitatively the tendencies used to create ties in these evolving online a...
[ { "version": "v1", "created": "Wed, 23 Nov 2011 16:04:06 GMT" } ]
2013-02-01T00:00:00
[ [ "Gallos", "Lazaros K.", "" ], [ "Rybski", "Diego", "" ], [ "Liljeros", "Fredrik", "" ], [ "Havlin", "Shlomo", "" ], [ "Makse", "Hernan A.", "" ] ]
TITLE: How people interact in evolving online affiliation networks ABSTRACT: The study of human interactions is of central importance for understanding the behavior of individuals, groups and societies. Here, we observe the formation and evolution of networks by monitoring the addition of all new links and we analy...
1301.7363
John S. Breese
John S. Breese, David Heckerman, Carl Kadie
Empirical Analysis of Predictive Algorithms for Collaborative Filtering
Appears in Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence (UAI1998)
null
null
UAI-P-1998-PG-43-52
cs.IR cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Collaborative filtering or recommender systems use a database about user preferences to predict additional topics or products a new user might like. In this paper we describe several algorithms designed for this task, including techniques based on correlation coefficients, vector-based similarity calculations, and st...
[ { "version": "v1", "created": "Wed, 30 Jan 2013 15:02:44 GMT" } ]
2013-02-01T00:00:00
[ [ "Breese", "John S.", "" ], [ "Heckerman", "David", "" ], [ "Kadie", "Carl", "" ] ]
TITLE: Empirical Analysis of Predictive Algorithms for Collaborative Filtering ABSTRACT: Collaborative filtering or recommender systems use a database about user preferences to predict additional topics or products a new user might like. In this paper we describe several algorithms designed for this task, including...
0903.4960
Michael Schreiber
Michael Schreiber
A Case Study of the Modified Hirsch Index hm Accounting for Multiple Co-authors
29 pages, including 2 tables, 3 figures with 7 plots altogether, accepted for publication in J. Am. Soc. Inf. Sci. Techn. vol. 60 (5) 2009
J. Am. Soc. Inf. Sci. Techn. 60, 1274-1282 (2009)
10.1002/asi.21057
null
physics.soc-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
J. E. Hirsch (2005) introduced the h-index to quantify an individual's scientific research output by the largest number h of a scientist's papers, that received at least h citations. This so-called Hirsch index can be easily modified to take multiple co-authorship into account by counting the papers fractionally acco...
[ { "version": "v1", "created": "Sat, 28 Mar 2009 10:01:42 GMT" } ]
2013-01-31T00:00:00
[ [ "Schreiber", "Michael", "" ] ]
TITLE: A Case Study of the Modified Hirsch Index hm Accounting for Multiple Co-authors ABSTRACT: J. E. Hirsch (2005) introduced the h-index to quantify an individual's scientific research output by the largest number h of a scientist's papers, that received at least h citations. This so-called Hirsch index can be...
1202.3861
Michael Schreiber
Michael Schreiber
Inconsistencies of Recently Proposed Citation Impact Indicators and how to Avoid Them
14 pages, 9 figures, accepted by Journal of the American Society for Information Science and Technology Final version with slightly changed figures, new scoring rule, extended discussion
J. Am. Soc. Inf. Sci. Techn. 63(10), 2062-2073, (2012)
null
null
stat.AP cs.DL physics.soc-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
It is shown that under certain circumstances in particular for small datasets the recently proposed citation impact indicators I3(6PR) and R(6,k) behave inconsistently when additional papers or citations are taken into consideration. Three simple examples are presented, in which the indicators fluctuate strongly and ...
[ { "version": "v1", "created": "Fri, 17 Feb 2012 10:05:04 GMT" }, { "version": "v2", "created": "Wed, 4 Apr 2012 08:33:52 GMT" } ]
2013-01-31T00:00:00
[ [ "Schreiber", "Michael", "" ] ]
TITLE: Inconsistencies of Recently Proposed Citation Impact Indicators and how to Avoid Them ABSTRACT: It is shown that under certain circumstances in particular for small datasets the recently proposed citation impact indicators I3(6PR) and R(6,k) behave inconsistently when additional papers or citations are tak...
1202.4605
Andreas Raue
Andreas Raue, Clemens Kreutz, Fabian Joachim Theis, Jens Timmer
Joining Forces of Bayesian and Frequentist Methodology: A Study for Inference in the Presence of Non-Identifiability
Article to appear in Phil. Trans. Roy. Soc. A
Phil. Trans. R. Soc. A. 371, 20110544, 2013
10.1098/rsta.2011.0544
null
physics.data-an
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Increasingly complex applications involve large datasets in combination with non-linear and high dimensional mathematical models. In this context, statistical inference is a challenging issue that calls for pragmatic approaches that take advantage of both Bayesian and frequentist methods. The elegance of Bayesian met...
[ { "version": "v1", "created": "Tue, 21 Feb 2012 11:44:06 GMT" } ]
2013-01-31T00:00:00
[ [ "Raue", "Andreas", "" ], [ "Kreutz", "Clemens", "" ], [ "Theis", "Fabian Joachim", "" ], [ "Timmer", "Jens", "" ] ]
TITLE: Joining Forces of Bayesian and Frequentist Methodology: A Study for Inference in the Presence of Non-Identifiability ABSTRACT: Increasingly complex applications involve large datasets in combination with non-linear and high dimensional mathematical models. In this context, statistical inference is a challe...
1211.2756
Anton Korobeynikov
Sergey I. Nikolenko, Anton I. Korobeynikov and Max A. Alekseyev
BayesHammer: Bayesian clustering for error correction in single-cell sequencing
null
BMC Genomics 14(Suppl 1) (2013), pp. S7
10.1186/1471-2164-14-S1-S7
null
q-bio.QM cs.CE cs.DS q-bio.GN
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Error correction of sequenced reads remains a difficult task, especially in single-cell sequencing projects with extremely non-uniform coverage. While existing error correction tools designed for standard (multi-cell) sequencing data usually come up short in single-cell sequencing projects, algorithms actually used f...
[ { "version": "v1", "created": "Mon, 12 Nov 2012 19:52:34 GMT" } ]
2013-01-31T00:00:00
[ [ "Nikolenko", "Sergey I.", "" ], [ "Korobeynikov", "Anton I.", "" ], [ "Alekseyev", "Max A.", "" ] ]
TITLE: BayesHammer: Bayesian clustering for error correction in single-cell sequencing ABSTRACT: Error correction of sequenced reads remains a difficult task, especially in single-cell sequencing projects with extremely non-uniform coverage. While existing error correction tools designed for standard (multi-cell)...
0910.5260
Sewoong Oh
Raghunandan H. Keshavan, Sewoong Oh
A Gradient Descent Algorithm on the Grassman Manifold for Matrix Completion
26 pages, 15 figures
null
10.1016/j.trc.2012.12.007
null
cs.NA cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We consider the problem of reconstructing a low-rank matrix from a small subset of its entries. In this paper, we describe the implementation of an efficient algorithm called OptSpace, based on singular value decomposition followed by local manifold optimization, for solving the low-rank matrix completion problem. It...
[ { "version": "v1", "created": "Tue, 27 Oct 2009 22:19:31 GMT" }, { "version": "v2", "created": "Tue, 3 Nov 2009 23:35:13 GMT" } ]
2013-01-30T00:00:00
[ [ "Keshavan", "Raghunandan H.", "" ], [ "Oh", "Sewoong", "" ] ]
TITLE: A Gradient Descent Algorithm on the Grassman Manifold for Matrix Completion ABSTRACT: We consider the problem of reconstructing a low-rank matrix from a small subset of its entries. In this paper, we describe the implementation of an efficient algorithm called OptSpace, based on singular value decompositio...
1205.4377
Kirill Trapeznikov
Kirill Trapeznikov, Venkatesh Saligrama, David Castanon
Multi-Stage Classifier Design
null
null
null
null
cs.CV stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In many classification systems, sensing modalities have different acquisition costs. It is often {\it unnecessary} to use every modality to classify a majority of examples. We study a multi-stage system in a prediction time cost reduction setting, where the full data is available for training, but for a test example,...
[ { "version": "v1", "created": "Sun, 20 May 2012 03:15:13 GMT" }, { "version": "v2", "created": "Tue, 29 Jan 2013 16:54:30 GMT" } ]
2013-01-30T00:00:00
[ [ "Trapeznikov", "Kirill", "" ], [ "Saligrama", "Venkatesh", "" ], [ "Castanon", "David", "" ] ]
TITLE: Multi-Stage Classifier Design ABSTRACT: In many classification systems, sensing modalities have different acquisition costs. It is often {\it unnecessary} to use every modality to classify a majority of examples. We study a multi-stage system in a prediction time cost reduction setting, where the full data i...
1301.6686
Gregory F. Cooper
Gregory F. Cooper, Changwon Yoo
Causal Discovery from a Mixture of Experimental and Observational Data
Appears in Proceedings of the Fifteenth Conference on Uncertainty in Artificial Intelligence (UAI1999)
null
null
UAI-P-1999-PG-116-125
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper describes a Bayesian method for combining an arbitrary mixture of observational and experimental data in order to learn causal Bayesian networks. Observational data are passively observed. Experimental data, such as that produced by randomized controlled trials, result from the experimenter manipulating on...
[ { "version": "v1", "created": "Wed, 23 Jan 2013 15:57:22 GMT" } ]
2013-01-30T00:00:00
[ [ "Cooper", "Gregory F.", "" ], [ "Yoo", "Changwon", "" ] ]
TITLE: Causal Discovery from a Mixture of Experimental and Observational Data ABSTRACT: This paper describes a Bayesian method for combining an arbitrary mixture of observational and experimental data in order to learn causal Bayesian networks. Observational data are passively observed. Experimental data, such as t...
1301.6723
Stefano Monti
Stefano Monti, Gregory F. Cooper
A Bayesian Network Classifier that Combines a Finite Mixture Model and a Naive Bayes Model
Appears in Proceedings of the Fifteenth Conference on Uncertainty in Artificial Intelligence (UAI1999)
null
null
UAI-P-1999-PG-447-456
cs.LG cs.AI stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper we present a new Bayesian network model for classification that combines the naive-Bayes (NB) classifier and the finite-mixture (FM) classifier. The resulting classifier aims at relaxing the strong assumptions on which the two component models are based, in an attempt to improve on their classification ...
[ { "version": "v1", "created": "Wed, 23 Jan 2013 15:59:54 GMT" } ]
2013-01-30T00:00:00
[ [ "Monti", "Stefano", "" ], [ "Cooper", "Gregory F.", "" ] ]
TITLE: A Bayesian Network Classifier that Combines a Finite Mixture Model and a Naive Bayes Model ABSTRACT: In this paper we present a new Bayesian network model for classification that combines the naive-Bayes (NB) classifier and the finite-mixture (FM) classifier. The resulting classifier aims at relaxing the s...
1301.6770
Zhixiang Eddie Xu
Zhixiang (Eddie) Xu, Minmin Chen, Kilian Q. Weinberger, Fei Sha
An alternative text representation to TF-IDF and Bag-of-Words
null
null
null
null
cs.IR cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In text mining, information retrieval, and machine learning, text documents are commonly represented through variants of sparse Bag of Words (sBoW) vectors (e.g. TF-IDF). Although simple and intuitive, sBoW style representations suffer from their inherent over-sparsity and fail to capture word-level synonymy and poly...
[ { "version": "v1", "created": "Mon, 28 Jan 2013 21:04:45 GMT" } ]
2013-01-30T00:00:00
[ [ "Zhixiang", "", "", "Eddie" ], [ "Xu", "", "" ], [ "Chen", "Minmin", "" ], [ "Weinberger", "Kilian Q.", "" ], [ "Sha", "Fei", "" ] ]
TITLE: An alternative text representation to TF-IDF and Bag-of-Words ABSTRACT: In text mining, information retrieval, and machine learning, text documents are commonly represented through variants of sparse Bag of Words (sBoW) vectors (e.g. TF-IDF). Although simple and intuitive, sBoW style representations suffer f...
1301.6800
Mokhov, Nikolai
C. Yoshikawa (Muons, Inc.), A. Leveling, N.V. Mokhov, J. Morgan, D. Neuffer, S. Striganov (Fermilab)
Optimization of the Target Subsystem for the New g-2 Experiment
4 pp. 3rd International Particle Accelerator Conference (IPAC 2012) 20-25 May 2012, New Orleans, Louisiana
null
null
FERMILAB-CONF-12-202-AD-APC
physics.acc-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A precision measurement of the muon anomalous magnetic moment, $a_{\mu} = (g-2)/2$, was previously performed at BNL with a result of 2.2 - 2.7 standard deviations above the Standard Model (SM) theoretical calculations. The same experimental apparatus is being planned to run in the new Muon Campus at Fermilab, where t...
[ { "version": "v1", "created": "Mon, 28 Jan 2013 22:30:19 GMT" } ]
2013-01-30T00:00:00
[ [ "Yoshikawa", "C.", "", "Muons, Inc." ], [ "Leveling", "A.", "", "Fermilab" ], [ "Mokhov", "N. V.", "", "Fermilab" ], [ "Morgan", "J.", "", "Fermilab" ], [ "Neuffer", "D.", "", "Fermilab" ], [ "Striganov", "...
TITLE: Optimization of the Target Subsystem for the New g-2 Experiment ABSTRACT: A precision measurement of the muon anomalous magnetic moment, $a_{\mu} = (g-2)/2$, was previously performed at BNL with a result of 2.2 - 2.7 standard deviations above the Standard Model (SM) theoretical calculations. The same experim...
1301.6870
Paridhi Jain
Anshu Malhotra, Luam Totti, Wagner Meira Jr., Ponnurangam Kumaraguru, Virgilio Almeida
Studying User Footprints in Different Online Social Networks
The paper is already published in ASONAM 2012
null
null
null
cs.SI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
With the growing popularity and usage of online social media services, people now have accounts (some times several) on multiple and diverse services like Facebook, LinkedIn, Twitter and YouTube. Publicly available information can be used to create a digital footprint of any user using these social media services. Ge...
[ { "version": "v1", "created": "Tue, 29 Jan 2013 09:29:54 GMT" } ]
2013-01-30T00:00:00
[ [ "Malhotra", "Anshu", "" ], [ "Totti", "Luam", "" ], [ "Meira", "Wagner", "Jr." ], [ "Kumaraguru", "Ponnurangam", "" ], [ "Almeida", "Virgilio", "" ] ]
TITLE: Studying User Footprints in Different Online Social Networks ABSTRACT: With the growing popularity and usage of online social media services, people now have accounts (some times several) on multiple and diverse services like Facebook, LinkedIn, Twitter and YouTube. Publicly available information can be used...
1210.0137
Pierre Deville Pierre
Vincent D. Blondel, Markus Esch, Connie Chan, Fabrice Clerot, Pierre Deville, Etienne Huens, Fr\'ed\'eric Morlot, Zbigniew Smoreda and Cezary Ziemlicki
Data for Development: the D4D Challenge on Mobile Phone Data
10 pages, 3 figures
null
null
null
cs.CY cs.SI physics.soc-ph stat.CO
http://creativecommons.org/licenses/by-nc-sa/3.0/
The Orange "Data for Development" (D4D) challenge is an open data challenge on anonymous call patterns of Orange's mobile phone users in Ivory Coast. The goal of the challenge is to help address society development questions in novel ways by contributing to the socio-economic development and well-being of the Ivory C...
[ { "version": "v1", "created": "Sat, 29 Sep 2012 17:39:16 GMT" }, { "version": "v2", "created": "Mon, 28 Jan 2013 12:56:55 GMT" } ]
2013-01-29T00:00:00
[ [ "Blondel", "Vincent D.", "" ], [ "Esch", "Markus", "" ], [ "Chan", "Connie", "" ], [ "Clerot", "Fabrice", "" ], [ "Deville", "Pierre", "" ], [ "Huens", "Etienne", "" ], [ "Morlot", "Frédéric", "" ], [ ...
TITLE: Data for Development: the D4D Challenge on Mobile Phone Data ABSTRACT: The Orange "Data for Development" (D4D) challenge is an open data challenge on anonymous call patterns of Orange's mobile phone users in Ivory Coast. The goal of the challenge is to help address society development questions in novel ways...
1301.4293
Limin Yao
Sebastian Riedel, Limin Yao, Andrew McCallum
Latent Relation Representations for Universal Schemas
4 pages, ICLR workshop
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Traditional relation extraction predicts relations within some fixed and finite target schema. Machine learning approaches to this task require either manual annotation or, in the case of distant supervision, existing structured sources of the same schema. The need for existing datasets can be avoided by using a univ...
[ { "version": "v1", "created": "Fri, 18 Jan 2013 04:37:30 GMT" }, { "version": "v2", "created": "Mon, 28 Jan 2013 20:10:21 GMT" } ]
2013-01-29T00:00:00
[ [ "Riedel", "Sebastian", "" ], [ "Yao", "Limin", "" ], [ "McCallum", "Andrew", "" ] ]
TITLE: Latent Relation Representations for Universal Schemas ABSTRACT: Traditional relation extraction predicts relations within some fixed and finite target schema. Machine learning approaches to this task require either manual annotation or, in the case of distant supervision, existing structured sources of the s...
1301.5686
Jeon-Hyung Kang
Jeon-Hyung Kang, Jun Ma, Yan Liu
Transfer Topic Modeling with Ease and Scalability
2012 SIAM International Conference on Data Mining (SDM12) Pages: {564-575}
null
null
null
cs.CL cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The increasing volume of short texts generated on social media sites, such as Twitter or Facebook, creates a great demand for effective and efficient topic modeling approaches. While latent Dirichlet allocation (LDA) can be applied, it is not optimal due to its weakness in handling short texts with fast-changing topi...
[ { "version": "v1", "created": "Thu, 24 Jan 2013 02:02:13 GMT" }, { "version": "v2", "created": "Sat, 26 Jan 2013 18:00:19 GMT" } ]
2013-01-29T00:00:00
[ [ "Kang", "Jeon-Hyung", "" ], [ "Ma", "Jun", "" ], [ "Liu", "Yan", "" ] ]
TITLE: Transfer Topic Modeling with Ease and Scalability ABSTRACT: The increasing volume of short texts generated on social media sites, such as Twitter or Facebook, creates a great demand for effective and efficient topic modeling approaches. While latent Dirichlet allocation (LDA) can be applied, it is not optima...
1301.6553
Thomas Couronne
Thomas Couronne, Zbigniew Smoreda, Ana-Maria Olteanu
Chatty Mobiles:Individual mobility and communication patterns
NetMob 2011, Boston
null
null
null
cs.CY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Human mobility analysis is an important issue in social sciences, and mobility data are among the most sought-after sources of information in ur- Data ban studies, geography, transportation and territory management. In network sciences mobility studies have become popular in the past few years, especially using mobil...
[ { "version": "v1", "created": "Mon, 28 Jan 2013 14:19:48 GMT" } ]
2013-01-29T00:00:00
[ [ "Couronne", "Thomas", "" ], [ "Smoreda", "Zbigniew", "" ], [ "Olteanu", "Ana-Maria", "" ] ]
TITLE: Chatty Mobiles:Individual mobility and communication patterns ABSTRACT: Human mobility analysis is an important issue in social sciences, and mobility data are among the most sought-after sources of information in ur- Data ban studies, geography, transportation and territory management. In network sciences m...
1301.5943
Lu\'is Filipe Te\'ofilo
Lu\'is Filipe Te\'ofilo, Luis Paulo Reis
Identifying Player\'s Strategies in No Limit Texas Hold\'em Poker through the Analysis of Individual Moves
null
null
null
null
cs.AI cs.GT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The development of competitive artificial Poker playing agents has proven to be a challenge, because agents must deal with unreliable information and deception which make it essential to model the opponents in order to achieve good results. This paper presents a methodology to develop opponent modeling techniques for...
[ { "version": "v1", "created": "Fri, 25 Jan 2013 01:49:15 GMT" } ]
2013-01-28T00:00:00
[ [ "Teófilo", "Luís Filipe", "" ], [ "Reis", "Luis Paulo", "" ] ]
TITLE: Identifying Player\'s Strategies in No Limit Texas Hold\'em Poker through the Analysis of Individual Moves ABSTRACT: The development of competitive artificial Poker playing agents has proven to be a challenge, because agents must deal with unreliable information and deception which make it essential to mod...
1212.2142
Arnab Chatterjee
Arnab Chatterjee, Marija Mitrovi\'c and Santo Fortunato
Universality in voting behavior: an empirical analysis
19 pages, 10 figures, 8 tables. The elections data-sets can be downloaded from http://becs.aalto.fi/en/research/complex_systems/elections/
Scientific Reports 3, 1049 (2013)
null
null
physics.soc-ph cs.SI physics.data-an
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Election data represent a precious source of information to study human behavior at a large scale. In proportional elections with open lists, the number of votes received by a candidate, rescaled by the average performance of all competitors in the same party list, has the same distribution regardless of the country ...
[ { "version": "v1", "created": "Mon, 10 Dec 2012 17:26:06 GMT" }, { "version": "v2", "created": "Thu, 24 Jan 2013 12:41:20 GMT" } ]
2013-01-25T00:00:00
[ [ "Chatterjee", "Arnab", "" ], [ "Mitrović", "Marija", "" ], [ "Fortunato", "Santo", "" ] ]
TITLE: Universality in voting behavior: an empirical analysis ABSTRACT: Election data represent a precious source of information to study human behavior at a large scale. In proportional elections with open lists, the number of votes received by a candidate, rescaled by the average performance of all competitors in...
1301.5399
Hoda Sadat Ayatollahi Tabatabaii
Hoda S. Ayatollahi Tabatabaii, Hamid R. Rabiee, Mohammad Hossein Rohban, Mostafa Salehi
Incorporating Betweenness Centrality in Compressive Sensing for Congestion Detection
null
null
null
null
cs.NI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper presents a new Compressive Sensing (CS) scheme for detecting network congested links. We focus on decreasing the required number of measurements to detect all congested links in the context of network tomography. We have expanded the LASSO objective function by adding a new term corresponding to the prior ...
[ { "version": "v1", "created": "Wed, 23 Jan 2013 04:12:08 GMT" } ]
2013-01-24T00:00:00
[ [ "Tabatabaii", "Hoda S. Ayatollahi", "" ], [ "Rabiee", "Hamid R.", "" ], [ "Rohban", "Mohammad Hossein", "" ], [ "Salehi", "Mostafa", "" ] ]
TITLE: Incorporating Betweenness Centrality in Compressive Sensing for Congestion Detection ABSTRACT: This paper presents a new Compressive Sensing (CS) scheme for detecting network congested links. We focus on decreasing the required number of measurements to detect all congested links in the context of network ...
1204.4491
Huy Nguyen
Huy Nguyen, Rong Zheng
On Budgeted Influence Maximization in Social Networks
Submitted to JSAC NS
null
null
null
cs.SI physics.soc-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Given a budget and arbitrary cost for selecting each node, the budgeted influence maximization (BIM) problem concerns selecting a set of seed nodes to disseminate some information that maximizes the total number of nodes influenced (termed as influence spread) in social networks at a total cost no more than the budge...
[ { "version": "v1", "created": "Thu, 19 Apr 2012 22:50:48 GMT" }, { "version": "v2", "created": "Thu, 2 Aug 2012 05:02:19 GMT" }, { "version": "v3", "created": "Tue, 22 Jan 2013 07:01:49 GMT" } ]
2013-01-23T00:00:00
[ [ "Nguyen", "Huy", "" ], [ "Zheng", "Rong", "" ] ]
TITLE: On Budgeted Influence Maximization in Social Networks ABSTRACT: Given a budget and arbitrary cost for selecting each node, the budgeted influence maximization (BIM) problem concerns selecting a set of seed nodes to disseminate some information that maximizes the total number of nodes influenced (termed as in...
1301.5088
Ian Goodfellow
Ian J. Goodfellow
Piecewise Linear Multilayer Perceptrons and Dropout
null
null
null
null
stat.ML cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We propose a new type of hidden layer for a multilayer perceptron, and demonstrate that it obtains the best reported performance for an MLP on the MNIST dataset.
[ { "version": "v1", "created": "Tue, 22 Jan 2013 07:10:34 GMT" } ]
2013-01-23T00:00:00
[ [ "Goodfellow", "Ian J.", "" ] ]
TITLE: Piecewise Linear Multilayer Perceptrons and Dropout ABSTRACT: We propose a new type of hidden layer for a multilayer perceptron, and demonstrate that it obtains the best reported performance for an MLP on the MNIST dataset.
1301.5121
Alex Averbuch
Alex Averbuch, Martin Neumann
Partitioning Graph Databases - A Quantitative Evaluation
null
null
null
null
cs.DB cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Electronic data is growing at increasing rates, in both size and connectivity: the increasing presence of, and interest in, relationships between data. An example is the Twitter social network graph. Due to this growth demand is increasing for technologies that can process such data. Currently relational databases ar...
[ { "version": "v1", "created": "Tue, 22 Jan 2013 09:48:34 GMT" } ]
2013-01-23T00:00:00
[ [ "Averbuch", "Alex", "" ], [ "Neumann", "Martin", "" ] ]
TITLE: Partitioning Graph Databases - A Quantitative Evaluation ABSTRACT: Electronic data is growing at increasing rates, in both size and connectivity: the increasing presence of, and interest in, relationships between data. An example is the Twitter social network graph. Due to this growth demand is increasing fo...
1012.4506
Taha Sochi
Taha Sochi
High Throughput Software for Powder Diffraction and its Application to Heterogeneous Catalysis
thesis, 202 pages, 95 figures, 6 tables
null
null
null
physics.data-an hep-ex physics.chem-ph physics.comp-ph physics.ins-det
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this thesis we investigate high throughput computational methods for processing large quantities of data collected from synchrotrons and their application to spectral analysis of powder diffraction data. We also present the main product of this PhD programme, specifically a software called 'EasyDD' developed by th...
[ { "version": "v1", "created": "Mon, 20 Dec 2010 23:35:54 GMT" } ]
2013-01-22T00:00:00
[ [ "Sochi", "Taha", "" ] ]
TITLE: High Throughput Software for Powder Diffraction and its Application to Heterogeneous Catalysis ABSTRACT: In this thesis we investigate high throughput computational methods for processing large quantities of data collected from synchrotrons and their application to spectral analysis of powder diffraction d...
1207.4417
Jingwei Liu
Jingwei Liu, Meizhi Xu
Penalty Constraints and Kernelization of M-Estimation Based Fuzzy C-Means
null
null
null
null
cs.CV stat.CO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A framework of M-estimation based fuzzy C-means clustering (MFCM) algorithm is proposed with iterative reweighted least squares (IRLS) algorithm, and penalty constraint and kernelization extensions of MFCM algorithms are also developed. Introducing penalty information to the object functions of MFCM algorithms, the s...
[ { "version": "v1", "created": "Wed, 18 Jul 2012 17:20:32 GMT" }, { "version": "v2", "created": "Sat, 19 Jan 2013 10:33:02 GMT" } ]
2013-01-22T00:00:00
[ [ "Liu", "Jingwei", "" ], [ "Xu", "Meizhi", "" ] ]
TITLE: Penalty Constraints and Kernelization of M-Estimation Based Fuzzy C-Means ABSTRACT: A framework of M-estimation based fuzzy C-means clustering (MFCM) algorithm is proposed with iterative reweighted least squares (IRLS) algorithm, and penalty constraint and kernelization extensions of MFCM algorithms are al...
1301.3753
Leif Johnson
Leif Johnson and Craig Corcoran
Switched linear encoding with rectified linear autoencoders
null
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Several recent results in machine learning have established formal connections between autoencoders---artificial neural network models that attempt to reproduce their inputs---and other coding models like sparse coding and K-means. This paper explores in depth an autoencoder model that is constructed using rectified ...
[ { "version": "v1", "created": "Wed, 16 Jan 2013 17:04:10 GMT" }, { "version": "v2", "created": "Sat, 19 Jan 2013 19:38:36 GMT" } ]
2013-01-22T00:00:00
[ [ "Johnson", "Leif", "" ], [ "Corcoran", "Craig", "" ] ]
TITLE: Switched linear encoding with rectified linear autoencoders ABSTRACT: Several recent results in machine learning have established formal connections between autoencoders---artificial neural network models that attempt to reproduce their inputs---and other coding models like sparse coding and K-means. This pa...
1301.3844
Gregory F. Cooper
Gregory F. Cooper
A Bayesian Method for Causal Modeling and Discovery Under Selection
Appears in Proceedings of the Sixteenth Conference on Uncertainty in Artificial Intelligence (UAI2000)
null
null
UAI-P-2000-PG-98-106
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper describes a Bayesian method for learning causal networks using samples that were selected in a non-random manner from a population of interest. Examples of data obtained by non-random sampling include convenience samples and case-control data in which a fixed number of samples with and without some conditi...
[ { "version": "v1", "created": "Wed, 16 Jan 2013 15:49:26 GMT" } ]
2013-01-18T00:00:00
[ [ "Cooper", "Gregory F.", "" ] ]
TITLE: A Bayesian Method for Causal Modeling and Discovery Under Selection ABSTRACT: This paper describes a Bayesian method for learning causal networks using samples that were selected in a non-random manner from a population of interest. Examples of data obtained by non-random sampling include convenience samples...
1301.3856
Nir Friedman
Nir Friedman, Daphne Koller
Being Bayesian about Network Structure
Appears in Proceedings of the Sixteenth Conference on Uncertainty in Artificial Intelligence (UAI2000)
null
null
UAI-P-2000-PG-201-210
cs.LG cs.AI stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In many domains, we are interested in analyzing the structure of the underlying distribution, e.g., whether one variable is a direct parent of the other. Bayesian model-selection attempts to find the MAP model and use its structure to answer these questions. However, when the amount of available data is modest, there...
[ { "version": "v1", "created": "Wed, 16 Jan 2013 15:50:14 GMT" } ]
2013-01-18T00:00:00
[ [ "Friedman", "Nir", "" ], [ "Koller", "Daphne", "" ] ]
TITLE: Being Bayesian about Network Structure ABSTRACT: In many domains, we are interested in analyzing the structure of the underlying distribution, e.g., whether one variable is a direct parent of the other. Bayesian model-selection attempts to find the MAP model and use its structure to answer these questions. H...
1301.3884
Dmitry Y. Pavlov
Dmitry Y. Pavlov, Heikki Mannila, Padhraic Smyth
Probabilistic Models for Query Approximation with Large Sparse Binary Datasets
Appears in Proceedings of the Sixteenth Conference on Uncertainty in Artificial Intelligence (UAI2000)
null
null
UAI-P-2000-PG-465-472
cs.AI cs.DB
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Large sparse sets of binary transaction data with millions of records and thousands of attributes occur in various domains: customers purchasing products, users visiting web pages, and documents containing words are just three typical examples. Real-time query selectivity estimation (the problem of estimating the num...
[ { "version": "v1", "created": "Wed, 16 Jan 2013 15:52:06 GMT" } ]
2013-01-18T00:00:00
[ [ "Pavlov", "Dmitry Y.", "" ], [ "Mannila", "Heikki", "" ], [ "Smyth", "Padhraic", "" ] ]
TITLE: Probabilistic Models for Query Approximation with Large Sparse Binary Datasets ABSTRACT: Large sparse sets of binary transaction data with millions of records and thousands of attributes occur in various domains: customers purchasing products, users visiting web pages, and documents containing words are ju...
1301.3891
Marc Sebban
Marc Sebban, Richard Nock
Combining Feature and Prototype Pruning by Uncertainty Minimization
Appears in Proceedings of the Sixteenth Conference on Uncertainty in Artificial Intelligence (UAI2000)
null
null
UAI-P-2000-PG-533-540
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We focus in this paper on dataset reduction techniques for use in k-nearest neighbor classification. In such a context, feature and prototype selections have always been independently treated by the standard storage reduction algorithms. While this certifying is theoretically justified by the fact that each subproble...
[ { "version": "v1", "created": "Wed, 16 Jan 2013 15:52:33 GMT" } ]
2013-01-18T00:00:00
[ [ "Sebban", "Marc", "" ], [ "Nock", "Richard", "" ] ]
TITLE: Combining Feature and Prototype Pruning by Uncertainty Minimization ABSTRACT: We focus in this paper on dataset reduction techniques for use in k-nearest neighbor classification. In such a context, feature and prototype selections have always been independently treated by the standard storage reduction algor...
1301.4028
Michael Schreiber
Michael Schreiber
Do we need the g-index?
7 pages, 3 figures accepted for publication in Journal of the American Society for Information Science and Technology
null
null
null
physics.soc-ph cs.DL
http://creativecommons.org/licenses/by-nc-sa/3.0/
Using a very small sample of 8 datasets it was recently shown by De Visscher (2011) that the g-index is very close to the square root of the total number of citations. It was argued that there is no bibliometrically meaningful difference. Using another somewhat larger empirical sample of 26 datasets I show that the d...
[ { "version": "v1", "created": "Thu, 17 Jan 2013 09:45:27 GMT" } ]
2013-01-18T00:00:00
[ [ "Schreiber", "Michael", "" ] ]
TITLE: Do we need the g-index? ABSTRACT: Using a very small sample of 8 datasets it was recently shown by De Visscher (2011) that the g-index is very close to the square root of the total number of citations. It was argued that there is no bibliometrically meaningful difference. Using another somewhat larger empiri...
1301.4171
Jason Weston
Jason Weston, Ron Weiss, Hector Yee
Affinity Weighted Embedding
null
null
null
null
cs.IR cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Supervised (linear) embedding models like Wsabie and PSI have proven successful at ranking, recommendation and annotation tasks. However, despite being scalable to large datasets they do not take full advantage of the extra data due to their linear nature, and typically underfit. We propose a new class of models whic...
[ { "version": "v1", "created": "Thu, 17 Jan 2013 17:46:27 GMT" } ]
2013-01-18T00:00:00
[ [ "Weston", "Jason", "" ], [ "Weiss", "Ron", "" ], [ "Yee", "Hector", "" ] ]
TITLE: Affinity Weighted Embedding ABSTRACT: Supervised (linear) embedding models like Wsabie and PSI have proven successful at ranking, recommendation and annotation tasks. However, despite being scalable to large datasets they do not take full advantage of the extra data due to their linear nature, and typically ...
1207.0166
Claudio Gentile
Claudio Gentile and Francesco Orabona
On Multilabel Classification and Ranking with Partial Feedback
null
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present a novel multilabel/ranking algorithm working in partial information settings. The algorithm is based on 2nd-order descent methods, and relies on upper-confidence bounds to trade-off exploration and exploitation. We analyze this algorithm in a partial adversarial setting, where covariates can be adversarial...
[ { "version": "v1", "created": "Sat, 30 Jun 2012 23:07:03 GMT" }, { "version": "v2", "created": "Tue, 20 Nov 2012 16:48:22 GMT" }, { "version": "v3", "created": "Wed, 16 Jan 2013 19:19:34 GMT" } ]
2013-01-17T00:00:00
[ [ "Gentile", "Claudio", "" ], [ "Orabona", "Francesco", "" ] ]
TITLE: On Multilabel Classification and Ranking with Partial Feedback ABSTRACT: We present a novel multilabel/ranking algorithm working in partial information settings. The algorithm is based on 2nd-order descent methods, and relies on upper-confidence bounds to trade-off exploration and exploitation. We analyze th...
1301.3528
Momiao Xiong
Momiao Xiong and Long Ma
An Efficient Sufficient Dimension Reduction Method for Identifying Genetic Variants of Clinical Significance
null
null
null
null
q-bio.GN cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Fast and cheaper next generation sequencing technologies will generate unprecedentedly massive and highly-dimensional genomic and epigenomic variation data. In the near future, a routine part of medical record will include the sequenced genomes. A fundamental question is how to efficiently extract genomic and epigeno...
[ { "version": "v1", "created": "Tue, 15 Jan 2013 23:19:14 GMT" } ]
2013-01-17T00:00:00
[ [ "Xiong", "Momiao", "" ], [ "Ma", "Long", "" ] ]
TITLE: An Efficient Sufficient Dimension Reduction Method for Identifying Genetic Variants of Clinical Significance ABSTRACT: Fast and cheaper next generation sequencing technologies will generate unprecedentedly massive and highly-dimensional genomic and epigenomic variation data. In the near future, a routine p...
1301.3539
Yoonseop Kang
Yoonseop Kang and Seungjin Choi
Learning Features with Structure-Adapting Multi-view Exponential Family Harmoniums
3 pages, 2 figures, ICLR2013 workshop track submission
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We proposea graphical model for multi-view feature extraction that automatically adapts its structure to achieve better representation of data distribution. The proposed model, structure-adapting multi-view harmonium (SA-MVH) has switch parameters that control the connection between hidden nodes and input views, and ...
[ { "version": "v1", "created": "Wed, 16 Jan 2013 01:07:38 GMT" } ]
2013-01-17T00:00:00
[ [ "Kang", "Yoonseop", "" ], [ "Choi", "Seungjin", "" ] ]
TITLE: Learning Features with Structure-Adapting Multi-view Exponential Family Harmoniums ABSTRACT: We proposea graphical model for multi-view feature extraction that automatically adapts its structure to achieve better representation of data distribution. The proposed model, structure-adapting multi-view harmoni...
1301.3557
Matthew Zeiler
Matthew D. Zeiler and Rob Fergus
Stochastic Pooling for Regularization of Deep Convolutional Neural Networks
9 pages
null
null
null
cs.LG cs.NE stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We introduce a simple and effective method for regularizing large convolutional neural networks. We replace the conventional deterministic pooling operations with a stochastic procedure, randomly picking the activation within each pooling region according to a multinomial distribution, given by the activities within ...
[ { "version": "v1", "created": "Wed, 16 Jan 2013 02:12:07 GMT" } ]
2013-01-17T00:00:00
[ [ "Zeiler", "Matthew D.", "" ], [ "Fergus", "Rob", "" ] ]
TITLE: Stochastic Pooling for Regularization of Deep Convolutional Neural Networks ABSTRACT: We introduce a simple and effective method for regularizing large convolutional neural networks. We replace the conventional deterministic pooling operations with a stochastic procedure, randomly picking the activation wi...
1301.3744
Tim Vines
Timothy H. Vines, Rose L. Andrew, Dan G. Bock, Michelle T. Franklin, Kimberly J. Gilbert, Nolan C. Kane, Jean-S\'ebastien Moore, Brook T. Moyers, S\'ebastien Renaut, Diana J. Rennison, Thor Veen, Sam Yeaman
Mandated data archiving greatly improves access to research data
null
null
10.1096/fj.12-218164
null
cs.DL physics.soc-ph q-bio.QM
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The data underlying scientific papers should be accessible to researchers both now and in the future, but how best can we ensure that these data are available? Here we examine the effectiveness of four approaches to data archiving: no stated archiving policy, recommending (but not requiring) archiving, and two versio...
[ { "version": "v1", "created": "Wed, 16 Jan 2013 16:22:26 GMT" } ]
2013-01-17T00:00:00
[ [ "Vines", "Timothy H.", "" ], [ "Andrew", "Rose L.", "" ], [ "Bock", "Dan G.", "" ], [ "Franklin", "Michelle T.", "" ], [ "Gilbert", "Kimberly J.", "" ], [ "Kane", "Nolan C.", "" ], [ "Moore", "Jean-Sébastien", ...
TITLE: Mandated data archiving greatly improves access to research data ABSTRACT: The data underlying scientific papers should be accessible to researchers both now and in the future, but how best can we ensure that these data are available? Here we examine the effectiveness of four approaches to data archiving: no...
1301.2659
Fabrice Rossi
Romain Guigour\`es, Marc Boull\'e, Fabrice Rossi (SAMM)
A Triclustering Approach for Time Evolving Graphs
null
Co-clustering and Applications International Conference on Data Mining Workshop, Brussels : Belgium (2012)
10.1109/ICDMW.2012.61
null
cs.LG cs.SI stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper introduces a novel technique to track structures in time evolving graphs. The method is based on a parameter free approach for three-dimensional co-clustering of the source vertices, the target vertices and the time. All these features are simultaneously segmented in order to build time segments and cluste...
[ { "version": "v1", "created": "Sat, 12 Jan 2013 07:51:14 GMT" } ]
2013-01-15T00:00:00
[ [ "Guigourès", "Romain", "", "SAMM" ], [ "Boullé", "Marc", "", "SAMM" ], [ "Rossi", "Fabrice", "", "SAMM" ] ]
TITLE: A Triclustering Approach for Time Evolving Graphs ABSTRACT: This paper introduces a novel technique to track structures in time evolving graphs. The method is based on a parameter free approach for three-dimensional co-clustering of the source vertices, the target vertices and the time. All these features ar...
1301.2785
Rafi Muhammad
Muhammad Rafi, Mohammad Shahid Shaikh
A comparison of SVM and RVM for Document Classification
ICoCSIM 2012, Medan Indonesia
null
null
null
cs.IR cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Document classification is a task of assigning a new unclassified document to one of the predefined set of classes. The content based document classification uses the content of the document with some weighting criteria to assign it to one of the predefined classes. It is a major task in library science, electronic d...
[ { "version": "v1", "created": "Sun, 13 Jan 2013 15:58:09 GMT" } ]
2013-01-15T00:00:00
[ [ "Rafi", "Muhammad", "" ], [ "Shaikh", "Mohammad Shahid", "" ] ]
TITLE: A comparison of SVM and RVM for Document Classification ABSTRACT: Document classification is a task of assigning a new unclassified document to one of the predefined set of classes. The content based document classification uses the content of the document with some weighting criteria to assign it to one of ...
1301.2283
Tomas Kocka
Tomas Kocka, Robert Castelo
Improved learning of Bayesian networks
Appears in Proceedings of the Seventeenth Conference on Uncertainty in Artificial Intelligence (UAI2001)
null
null
UAI-P-2001-PG-269-276
cs.LG cs.AI stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The search space of Bayesian Network structures is usually defined as Acyclic Directed Graphs (DAGs) and the search is done by local transformations of DAGs. But the space of Bayesian Networks is ordered by DAG Markov model inclusion and it is natural to consider that a good search policy should take this into accoun...
[ { "version": "v1", "created": "Thu, 10 Jan 2013 16:24:32 GMT" } ]
2013-01-14T00:00:00
[ [ "Kocka", "Tomas", "" ], [ "Castelo", "Robert", "" ] ]
TITLE: Improved learning of Bayesian networks ABSTRACT: The search space of Bayesian Network structures is usually defined as Acyclic Directed Graphs (DAGs) and the search is done by local transformations of DAGs. But the space of Bayesian Networks is ordered by DAG Markov model inclusion and it is natural to consi...
1301.2375
Jianxin Li
Jianxin Li, Chengfei Liu, Liang Yao and Jeffrey Xu Yu
Context-based Diversification for Keyword Queries over XML Data
null
null
null
null
cs.DB
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
While keyword query empowers ordinary users to search vast amount of data, the ambiguity of keyword query makes it difficult to effectively answer keyword queries, especially for short and vague keyword queries. To address this challenging problem, in this paper we propose an approach that automatically diversifies X...
[ { "version": "v1", "created": "Fri, 11 Jan 2013 01:33:50 GMT" } ]
2013-01-14T00:00:00
[ [ "Li", "Jianxin", "" ], [ "Liu", "Chengfei", "" ], [ "Yao", "Liang", "" ], [ "Yu", "Jeffrey Xu", "" ] ]
TITLE: Context-based Diversification for Keyword Queries over XML Data ABSTRACT: While keyword query empowers ordinary users to search vast amount of data, the ambiguity of keyword query makes it difficult to effectively answer keyword queries, especially for short and vague keyword queries. To address this challen...
1301.2378
Jianxin Li
Jianxin Li, Chengfei Liu, Liang Yao, Jeffrey Xu Yu and Rui Zhou
Query-driven Frequent Co-occurring Term Extraction over Relational Data using MapReduce
null
null
null
null
cs.DB
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper we study how to efficiently compute \textit{frequent co-occurring terms} (FCT) in the results of a keyword query in parallel using the popular MapReduce framework. Taking as input a keyword query q and an integer k, an FCT query reports the k terms that are not in q, but appear most frequently in the re...
[ { "version": "v1", "created": "Fri, 11 Jan 2013 01:55:10 GMT" } ]
2013-01-14T00:00:00
[ [ "Li", "Jianxin", "" ], [ "Liu", "Chengfei", "" ], [ "Yao", "Liang", "" ], [ "Yu", "Jeffrey Xu", "" ], [ "Zhou", "Rui", "" ] ]
TITLE: Query-driven Frequent Co-occurring Term Extraction over Relational Data using MapReduce ABSTRACT: In this paper we study how to efficiently compute \textit{frequent co-occurring terms} (FCT) in the results of a keyword query in parallel using the popular MapReduce framework. Taking as input a keyword query...
1301.2115
Krikamol Muandet
Krikamol Muandet, David Balduzzi, Bernhard Sch\"olkopf
Domain Generalization via Invariant Feature Representation
The 30th International Conference on Machine Learning (ICML 2013)
null
null
null
stat.ML cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper investigates domain generalization: How to take knowledge acquired from an arbitrary number of related domains and apply it to previously unseen domains? We propose Domain-Invariant Component Analysis (DICA), a kernel-based optimization algorithm that learns an invariant transformation by minimizing the di...
[ { "version": "v1", "created": "Thu, 10 Jan 2013 13:29:17 GMT" } ]
2013-01-11T00:00:00
[ [ "Muandet", "Krikamol", "" ], [ "Balduzzi", "David", "" ], [ "Schölkopf", "Bernhard", "" ] ]
TITLE: Domain Generalization via Invariant Feature Representation ABSTRACT: This paper investigates domain generalization: How to take knowledge acquired from an arbitrary number of related domains and apply it to previously unseen domains? We propose Domain-Invariant Component Analysis (DICA), a kernel-based optim...
1301.1722
Andrea Montanari
Yash Deshpande and Andrea Montanari
Linear Bandits in High Dimension and Recommendation Systems
21 pages, 4 figures
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A large number of online services provide automated recommendations to help users to navigate through a large collection of items. New items (products, videos, songs, advertisements) are suggested on the basis of the user's past history and --when available-- her demographic profile. Recommendations have to satisfy t...
[ { "version": "v1", "created": "Tue, 8 Jan 2013 23:45:06 GMT" } ]
2013-01-10T00:00:00
[ [ "Deshpande", "Yash", "" ], [ "Montanari", "Andrea", "" ] ]
TITLE: Linear Bandits in High Dimension and Recommendation Systems ABSTRACT: A large number of online services provide automated recommendations to help users to navigate through a large collection of items. New items (products, videos, songs, advertisements) are suggested on the basis of the user's past history an...
1301.1502
Hannah Inbarani
N. Kalaiselvi, H. Hannah Inbarani
Fuzzy Soft Set Based Classification for Gene Expression Data
7 pages, IJSER Vol.3 Issue: 10 Oct 2012
null
null
null
cs.AI cs.CE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Classification is one of the major issues in Data Mining Research fields. The classification problems in medical area often classify medical dataset based on the result of medical diagnosis or description of medical treatment by the medical practitioner. This research work discusses the classification process of Gene...
[ { "version": "v1", "created": "Tue, 8 Jan 2013 11:48:49 GMT" } ]
2013-01-09T00:00:00
[ [ "Kalaiselvi", "N.", "" ], [ "Inbarani", "H. Hannah", "" ] ]
TITLE: Fuzzy Soft Set Based Classification for Gene Expression Data ABSTRACT: Classification is one of the major issues in Data Mining Research fields. The classification problems in medical area often classify medical dataset based on the result of medical diagnosis or description of medical treatment by the medic...
1212.4775
Mario Frank
Mario Frank, Joachim M. Buhmann, David Basin
Role Mining with Probabilistic Models
accepted for publication at ACM Transactions on Information and System Security (TISSEC)
null
null
null
cs.CR cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Role mining tackles the problem of finding a role-based access control (RBAC) configuration, given an access-control matrix assigning users to access permissions as input. Most role mining approaches work by constructing a large set of candidate roles and use a greedy selection strategy to iteratively pick a small su...
[ { "version": "v1", "created": "Wed, 19 Dec 2012 18:12:34 GMT" }, { "version": "v2", "created": "Thu, 3 Jan 2013 17:27:55 GMT" }, { "version": "v3", "created": "Fri, 4 Jan 2013 22:24:15 GMT" } ]
2013-01-08T00:00:00
[ [ "Frank", "Mario", "" ], [ "Buhmann", "Joachim M.", "" ], [ "Basin", "David", "" ] ]
TITLE: Role Mining with Probabilistic Models ABSTRACT: Role mining tackles the problem of finding a role-based access control (RBAC) configuration, given an access-control matrix assigning users to access permissions as input. Most role mining approaches work by constructing a large set of candidate roles and use a...
1301.0561
David Maxwell Chickering
David Maxwell Chickering, Christopher Meek
Finding Optimal Bayesian Networks
Appears in Proceedings of the Eighteenth Conference on Uncertainty in Artificial Intelligence (UAI2002)
null
null
UAI-P-2002-PG-94-102
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we derive optimality results for greedy Bayesian-network search algorithms that perform single-edge modifications at each step and use asymptotically consistent scoring criteria. Our results extend those of Meek (1997) and Chickering (2002), who demonstrate that in the limit of large datasets, if the g...
[ { "version": "v1", "created": "Wed, 12 Dec 2012 15:55:46 GMT" } ]
2013-01-07T00:00:00
[ [ "Chickering", "David Maxwell", "" ], [ "Meek", "Christopher", "" ] ]
TITLE: Finding Optimal Bayesian Networks ABSTRACT: In this paper, we derive optimality results for greedy Bayesian-network search algorithms that perform single-edge modifications at each step and use asymptotically consistent scoring criteria. Our results extend those of Meek (1997) and Chickering (2002), who demo...
1301.0432
Fahad Mahmood Mr
F. Mahmood, F. Kunwar
A Self-Organizing Neural Scheme for Door Detection in Different Environments
Page No 13-18, 7 figures, Published with International Journal of Computer Applications (IJCA)
International Journal of Computer Applications 60(9):13-18, 2012
10.5120/9719-3679
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Doors are important landmarks for indoor mobile robot navigation and also assist blind people to independently access unfamiliar buildings. Most existing algorithms of door detection are limited to work for familiar environments because of restricted assumptions about color, texture and shape. In this paper we propos...
[ { "version": "v1", "created": "Thu, 3 Jan 2013 12:04:28 GMT" } ]
2013-01-04T00:00:00
[ [ "Mahmood", "F.", "" ], [ "Kunwar", "F.", "" ] ]
TITLE: A Self-Organizing Neural Scheme for Door Detection in Different Environments ABSTRACT: Doors are important landmarks for indoor mobile robot navigation and also assist blind people to independently access unfamiliar buildings. Most existing algorithms of door detection are limited to work for familiar envi...
0911.2942
Chris Giannella
Chris Giannella, Kun Liu, Hillol Kargupta
Breaching Euclidean Distance-Preserving Data Perturbation Using Few Known Inputs
This is a major revision accounting for journal peer-review. Changes include: removal of known sample attack, more citations added, an empirical comparison against the algorithm of Kaplan et al. added
Data & Knowledge Engineering 83, pages 93-110, 2013
null
null
cs.DB cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We examine Euclidean distance-preserving data perturbation as a tool for privacy-preserving data mining. Such perturbations allow many important data mining algorithms e.g. hierarchical and k-means clustering), with only minor modification, to be applied to the perturbed data and produce exactly the same results as i...
[ { "version": "v1", "created": "Mon, 16 Nov 2009 02:51:37 GMT" }, { "version": "v2", "created": "Wed, 2 Jan 2013 15:49:10 GMT" } ]
2013-01-03T00:00:00
[ [ "Giannella", "Chris", "" ], [ "Liu", "Kun", "" ], [ "Kargupta", "Hillol", "" ] ]
TITLE: Breaching Euclidean Distance-Preserving Data Perturbation Using Few Known Inputs ABSTRACT: We examine Euclidean distance-preserving data perturbation as a tool for privacy-preserving data mining. Such perturbations allow many important data mining algorithms e.g. hierarchical and k-means clustering), with ...
1212.5841
Andrei Zinovyev Dr.
Andrei Zinovyev and Evgeny Mirkes
Data complexity measured by principal graphs
Computers and Mathematics with Applications, in press
null
10.1016/j.camwa.2012.12.009
null
cs.LG cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
How to measure the complexity of a finite set of vectors embedded in a multidimensional space? This is a non-trivial question which can be approached in many different ways. Here we suggest a set of data complexity measures using universal approximators, principal cubic complexes. Principal cubic complexes generalise...
[ { "version": "v1", "created": "Sun, 23 Dec 2012 23:20:14 GMT" }, { "version": "v2", "created": "Wed, 2 Jan 2013 00:00:40 GMT" } ]
2013-01-03T00:00:00
[ [ "Zinovyev", "Andrei", "" ], [ "Mirkes", "Evgeny", "" ] ]
TITLE: Data complexity measured by principal graphs ABSTRACT: How to measure the complexity of a finite set of vectors embedded in a multidimensional space? This is a non-trivial question which can be approached in many different ways. Here we suggest a set of data complexity measures using universal approximators,...
1212.6316
Nathalie Villa-Vialaneix
Madalina Olteanu (SAMM), Nathalie Villa-Vialaneix (SAMM), Marie Cottrell (SAMM)
On-line relational SOM for dissimilarity data
WSOM 2012, Santiago : Chile (2012)
null
null
null
stat.ML cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In some applications and in order to address real world situations better, data may be more complex than simple vectors. In some examples, they can be known through their pairwise dissimilarities only. Several variants of the Self Organizing Map algorithm were introduced to generalize the original algorithm to this f...
[ { "version": "v1", "created": "Thu, 27 Dec 2012 07:07:06 GMT" } ]
2013-01-03T00:00:00
[ [ "Olteanu", "Madalina", "", "SAMM" ], [ "Villa-Vialaneix", "Nathalie", "", "SAMM" ], [ "Cottrell", "Marie", "", "SAMM" ] ]
TITLE: On-line relational SOM for dissimilarity data ABSTRACT: In some applications and in order to address real world situations better, data may be more complex than simple vectors. In some examples, they can be known through their pairwise dissimilarities only. Several variants of the Self Organizing Map algorit...
1301.0082
F. Ozgur Catak
F. Ozgur Catak and M. Erdal Balaban
CloudSVM : Training an SVM Classifier in Cloud Computing Systems
13 pages
null
null
null
cs.LG cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In conventional method, distributed support vector machines (SVM) algorithms are trained over pre-configured intranet/internet environments to find out an optimal classifier. These methods are very complicated and costly for large datasets. Hence, we propose a method that is referred as the Cloud SVM training mechani...
[ { "version": "v1", "created": "Tue, 1 Jan 2013 13:20:27 GMT" } ]
2013-01-03T00:00:00
[ [ "Catak", "F. Ozgur", "" ], [ "Balaban", "M. Erdal", "" ] ]
TITLE: CloudSVM : Training an SVM Classifier in Cloud Computing Systems ABSTRACT: In conventional method, distributed support vector machines (SVM) algorithms are trained over pre-configured intranet/internet environments to find out an optimal classifier. These methods are very complicated and costly for large dat...
1301.0289
Aaditya Prakash
Aaditya Prakash
Reconstructing Self Organizing Maps as Spider Graphs for better visual interpretation of large unstructured datasets
9 pages, 8 figures
null
null
null
cs.GR stat.ML
http://creativecommons.org/licenses/by/3.0/
Self-Organizing Maps (SOM) are popular unsupervised artificial neural network used to reduce dimensions and visualize data. Visual interpretation from Self-Organizing Maps (SOM) has been limited due to grid approach of data representation, which makes inter-scenario analysis impossible. The paper proposes a new way t...
[ { "version": "v1", "created": "Mon, 24 Dec 2012 17:10:28 GMT" } ]
2013-01-03T00:00:00
[ [ "Prakash", "Aaditya", "" ] ]
TITLE: Reconstructing Self Organizing Maps as Spider Graphs for better visual interpretation of large unstructured datasets ABSTRACT: Self-Organizing Maps (SOM) are popular unsupervised artificial neural network used to reduce dimensions and visualize data. Visual interpretation from Self-Organizing Maps (SOM) ha...
1205.4463
Salah A. Aly
Salah A. Aly
Pilgrims Face Recognition Dataset -- HUFRD
5 pages, 13 images, 1 table of a new HUFRD work
null
null
null
cs.CV cs.CY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this work, we define a new pilgrims face recognition dataset, called HUFRD dataset. The new developed dataset presents various pilgrims' images taken from outside the Holy Masjid El-Harram in Makkah during the 2011-2012 Hajj and Umrah seasons. Such dataset will be used to test our developed facial recognition and ...
[ { "version": "v1", "created": "Sun, 20 May 2012 22:07:27 GMT" }, { "version": "v2", "created": "Sun, 30 Dec 2012 00:58:09 GMT" } ]
2013-01-01T00:00:00
[ [ "Aly", "Salah A.", "" ] ]
TITLE: Pilgrims Face Recognition Dataset -- HUFRD ABSTRACT: In this work, we define a new pilgrims face recognition dataset, called HUFRD dataset. The new developed dataset presents various pilgrims' images taken from outside the Holy Masjid El-Harram in Makkah during the 2011-2012 Hajj and Umrah seasons. Such data...
1212.6659
Raphael Pelossof
Raphael Pelossof and Zhiliang Ying
Focus of Attention for Linear Predictors
9 pages, 4 figures. arXiv admin note: substantial text overlap with arXiv:1105.0382
null
null
null
stat.ML cs.AI cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present a method to stop the evaluation of a prediction process when the result of the full evaluation is obvious. This trait is highly desirable in prediction tasks where a predictor evaluates all its features for every example in large datasets. We observe that some examples are easier to classify than others, a...
[ { "version": "v1", "created": "Sat, 29 Dec 2012 20:23:48 GMT" } ]
2013-01-01T00:00:00
[ [ "Pelossof", "Raphael", "" ], [ "Ying", "Zhiliang", "" ] ]
TITLE: Focus of Attention for Linear Predictors ABSTRACT: We present a method to stop the evaluation of a prediction process when the result of the full evaluation is obvious. This trait is highly desirable in prediction tasks where a predictor evaluates all its features for every example in large datasets. We obse...
1212.5637
Claudio Gentile
Nicolo' Cesa-Bianchi, Claudio Gentile, Fabio Vitale, Giovanni Zappella
Random Spanning Trees and the Prediction of Weighted Graphs
Appeared in ICML 2010
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We investigate the problem of sequentially predicting the binary labels on the nodes of an arbitrary weighted graph. We show that, under a suitable parametrization of the problem, the optimal number of prediction mistakes can be characterized (up to logarithmic factors) by the cutsize of a random spanning tree of the...
[ { "version": "v1", "created": "Fri, 21 Dec 2012 23:51:21 GMT" } ]
2012-12-27T00:00:00
[ [ "Cesa-Bianchi", "Nicolo'", "" ], [ "Gentile", "Claudio", "" ], [ "Vitale", "Fabio", "" ], [ "Zappella", "Giovanni", "" ] ]
TITLE: Random Spanning Trees and the Prediction of Weighted Graphs ABSTRACT: We investigate the problem of sequentially predicting the binary labels on the nodes of an arbitrary weighted graph. We show that, under a suitable parametrization of the problem, the optimal number of prediction mistakes can be characteri...
1212.5701
Matthew Zeiler
Matthew D. Zeiler
ADADELTA: An Adaptive Learning Rate Method
6 pages
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present a novel per-dimension learning rate method for gradient descent called ADADELTA. The method dynamically adapts over time using only first order information and has minimal computational overhead beyond vanilla stochastic gradient descent. The method requires no manual tuning of a learning rate and appears ...
[ { "version": "v1", "created": "Sat, 22 Dec 2012 15:46:49 GMT" } ]
2012-12-27T00:00:00
[ [ "Zeiler", "Matthew D.", "" ] ]
TITLE: ADADELTA: An Adaptive Learning Rate Method ABSTRACT: We present a novel per-dimension learning rate method for gradient descent called ADADELTA. The method dynamically adapts over time using only first order information and has minimal computational overhead beyond vanilla stochastic gradient descent. The me...
1212.6246
Radford M. Neal
Chunyi Wang and Radford M. Neal
Gaussian Process Regression with Heteroscedastic or Non-Gaussian Residuals
null
null
null
null
stat.ML cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Gaussian Process (GP) regression models typically assume that residuals are Gaussian and have the same variance for all observations. However, applications with input-dependent noise (heteroscedastic residuals) frequently arise in practice, as do applications in which the residuals do not have a Gaussian distribution...
[ { "version": "v1", "created": "Wed, 26 Dec 2012 20:45:48 GMT" } ]
2012-12-27T00:00:00
[ [ "Wang", "Chunyi", "" ], [ "Neal", "Radford M.", "" ] ]
TITLE: Gaussian Process Regression with Heteroscedastic or Non-Gaussian Residuals ABSTRACT: Gaussian Process (GP) regression models typically assume that residuals are Gaussian and have the same variance for all observations. However, applications with input-dependent noise (heteroscedastic residuals) frequently ...
1211.3089
Yuheng Hu
Yuheng Hu, Ajita John, Fei Wang, Subbarao Kambhampati
ET-LDA: Joint Topic Modeling for Aligning Events and their Twitter Feedback
reference error, delete for now
null
null
null
cs.SI cs.AI cs.CY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
During broadcast events such as the Superbowl, the U.S. Presidential and Primary debates, etc., Twitter has become the de facto platform for crowds to share perspectives and commentaries about them. Given an event and an associated large-scale collection of tweets, there are two fundamental research problems that hav...
[ { "version": "v1", "created": "Tue, 13 Nov 2012 19:46:51 GMT" }, { "version": "v2", "created": "Fri, 21 Dec 2012 05:50:15 GMT" } ]
2012-12-24T00:00:00
[ [ "Hu", "Yuheng", "" ], [ "John", "Ajita", "" ], [ "Wang", "Fei", "" ], [ "Kambhampati", "Subbarao", "" ] ]
TITLE: ET-LDA: Joint Topic Modeling for Aligning Events and their Twitter Feedback ABSTRACT: During broadcast events such as the Superbowl, the U.S. Presidential and Primary debates, etc., Twitter has become the de facto platform for crowds to share perspectives and commentaries about them. Given an event and an ...
1212.5265
Tamal Ghosh Tamal Ghosh
Tamal Ghosh, Pranab K Dan
An Effective Machine-Part Grouping Algorithm to Construct Manufacturing Cells
null
Proceedings of Conference on Industrial Engineering (NCIE 2011)
null
null
cs.CE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The machine-part cell formation problem consists of creating machine cells and their corresponding part families with the objective of minimizing the inter-cell and intra-cell movement while maximizing the machine utilization. This article demonstrates a hybrid clustering approach for the cell formation problem in ce...
[ { "version": "v1", "created": "Thu, 20 Dec 2012 15:51:13 GMT" } ]
2012-12-24T00:00:00
[ [ "Ghosh", "Tamal", "" ], [ "Dan", "Pranab K", "" ] ]
TITLE: An Effective Machine-Part Grouping Algorithm to Construct Manufacturing Cells ABSTRACT: The machine-part cell formation problem consists of creating machine cells and their corresponding part families with the objective of minimizing the inter-cell and intra-cell movement while maximizing the machine utili...
1212.4458
Dan Burger
Dan Burger, Keivan G. Stassun, Joshua Pepper, Robert J. Siverd, Martin A. Paegert, Nathan M. De Lee
Filtergraph: A Flexible Web Application for Instant Data Visualization of Astronomy Datasets
4 pages, 1 figure. Originally presented at the ADASS XXII Conference in Champaign, IL on November 6, 2012. Published in the conference proceedings by ASP Conference Series (revised to include URL of web application)
null
null
null
astro-ph.IM cs.SE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Filtergraph is a web application being developed by the Vanderbilt Initiative in Data-intensive Astrophysics (VIDA) to flexibly handle a large variety of astronomy datasets. While current datasets at Vanderbilt are being used to search for eclipsing binaries and extrasolar planets, this system can be easily reconfigu...
[ { "version": "v1", "created": "Tue, 18 Dec 2012 19:00:06 GMT" }, { "version": "v2", "created": "Wed, 19 Dec 2012 17:04:02 GMT" }, { "version": "v3", "created": "Thu, 20 Dec 2012 17:17:00 GMT" } ]
2012-12-21T00:00:00
[ [ "Burger", "Dan", "" ], [ "Stassun", "Keivan G.", "" ], [ "Pepper", "Joshua", "" ], [ "Siverd", "Robert J.", "" ], [ "Paegert", "Martin A.", "" ], [ "De Lee", "Nathan M.", "" ] ]
TITLE: Filtergraph: A Flexible Web Application for Instant Data Visualization of Astronomy Datasets ABSTRACT: Filtergraph is a web application being developed by the Vanderbilt Initiative in Data-intensive Astrophysics (VIDA) to flexibly handle a large variety of astronomy datasets. While current datasets at Vand...
1212.4871
Ramin Norousi
Ramin Norousi, Stephan Wickles, Christoph Leidig, Thomas Becker, Volker J. Schmid, Roland Beckmann, Achim Tresch
Automatic post-picking using MAPPOS improves particle image detection from Cryo-EM micrographs
null
null
null
null
stat.ML cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Cryo-electron microscopy (cryo-EM) studies using single particle reconstruction are extensively used to reveal structural information on macromolecular complexes. Aiming at the highest achievable resolution, state of the art electron microscopes automatically acquire thousands of high-quality micrographs. Particles a...
[ { "version": "v1", "created": "Wed, 19 Dec 2012 22:17:18 GMT" } ]
2012-12-21T00:00:00
[ [ "Norousi", "Ramin", "" ], [ "Wickles", "Stephan", "" ], [ "Leidig", "Christoph", "" ], [ "Becker", "Thomas", "" ], [ "Schmid", "Volker J.", "" ], [ "Beckmann", "Roland", "" ], [ "Tresch", "Achim", "" ] ]
TITLE: Automatic post-picking using MAPPOS improves particle image detection from Cryo-EM micrographs ABSTRACT: Cryo-electron microscopy (cryo-EM) studies using single particle reconstruction are extensively used to reveal structural information on macromolecular complexes. Aiming at the highest achievable resolu...
1212.4788
Dominik Grimm dg
Dominik Grimm, Bastian Greshake, Stefan Kleeberger, Christoph Lippert, Oliver Stegle, Bernhard Sch\"olkopf, Detlef Weigel and Karsten Borgwardt
easyGWAS: An integrated interspecies platform for performing genome-wide association studies
null
null
null
null
q-bio.GN cs.CE cs.DL stat.AP
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Motivation: The rapid growth in genome-wide association studies (GWAS) in plants and animals has brought about the need for a central resource that facilitates i) performing GWAS, ii) accessing data and results of other GWAS, and iii) enabling all users regardless of their background to exploit the latest statistical...
[ { "version": "v1", "created": "Wed, 19 Dec 2012 18:39:06 GMT" } ]
2012-12-20T00:00:00
[ [ "Grimm", "Dominik", "" ], [ "Greshake", "Bastian", "" ], [ "Kleeberger", "Stefan", "" ], [ "Lippert", "Christoph", "" ], [ "Stegle", "Oliver", "" ], [ "Schölkopf", "Bernhard", "" ], [ "Weigel", "Detlef", ""...
TITLE: easyGWAS: An integrated interspecies platform for performing genome-wide association studies ABSTRACT: Motivation: The rapid growth in genome-wide association studies (GWAS) in plants and animals has brought about the need for a central resource that facilitates i) performing GWAS, ii) accessing data and r...
1212.4347
Bonggun Shin
Bonggun Shin, Alice Oh
Bayesian Group Nonnegative Matrix Factorization for EEG Analysis
null
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We propose a generative model of a group EEG analysis, based on appropriate kernel assumptions on EEG data. We derive the variational inference update rule using various approximation techniques. The proposed model outperforms the current state-of-the-art algorithms in terms of common pattern extraction. The validity...
[ { "version": "v1", "created": "Tue, 18 Dec 2012 13:35:38 GMT" } ]
2012-12-19T00:00:00
[ [ "Shin", "Bonggun", "" ], [ "Oh", "Alice", "" ] ]
TITLE: Bayesian Group Nonnegative Matrix Factorization for EEG Analysis ABSTRACT: We propose a generative model of a group EEG analysis, based on appropriate kernel assumptions on EEG data. We derive the variational inference update rule using various approximation techniques. The proposed model outperforms the cur...
1212.3938
Aurore Laurendeau
Aurore Laurendeau (ISTerre), Fabrice Cotton (ISTerre), Luis Fabian Bonilla
Nonstationary Stochastic Simulation of Strong Ground-Motion Time Histories : Application to the Japanese Database
10 pages; 15th World Conference on Earthquake Engineering, Lisbon : Portugal (2012)
null
null
null
stat.AP physics.geo-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
For earthquake-resistant design, engineering seismologists employ time-history analysis for nonlinear simulations. The nonstationary stochastic method previously developed by Pousse et al. (2006) has been updated. This method has the advantage of being both simple, fast and taking into account the basic concepts of s...
[ { "version": "v1", "created": "Mon, 17 Dec 2012 08:47:29 GMT" } ]
2012-12-18T00:00:00
[ [ "Laurendeau", "Aurore", "", "ISTerre" ], [ "Cotton", "Fabrice", "", "ISTerre" ], [ "Bonilla", "Luis Fabian", "" ] ]
TITLE: Nonstationary Stochastic Simulation of Strong Ground-Motion Time Histories : Application to the Japanese Database ABSTRACT: For earthquake-resistant design, engineering seismologists employ time-history analysis for nonlinear simulations. The nonstationary stochastic method previously developed by Pousse e...
1212.3964
Sourav Dutta
Suman K. Bera, Sourav Dutta, Ankur Narang and Souvik Bhattacherjee
Advanced Bloom Filter Based Algorithms for Efficient Approximate Data De-Duplication in Streams
41 pages
null
null
null
cs.IR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Applications involving telecommunication call data records, web pages, online transactions, medical records, stock markets, climate warning systems, etc., necessitate efficient management and processing of such massively exponential amount of data from diverse sources. De-duplication or Intelligent Compression in str...
[ { "version": "v1", "created": "Mon, 17 Dec 2012 11:47:09 GMT" } ]
2012-12-18T00:00:00
[ [ "Bera", "Suman K.", "" ], [ "Dutta", "Sourav", "" ], [ "Narang", "Ankur", "" ], [ "Bhattacherjee", "Souvik", "" ] ]
TITLE: Advanced Bloom Filter Based Algorithms for Efficient Approximate Data De-Duplication in Streams ABSTRACT: Applications involving telecommunication call data records, web pages, online transactions, medical records, stock markets, climate warning systems, etc., necessitate efficient management and processin...
1212.3390
A Majumder
Anirban Majumder and Nisheeth Shrivastava
Know Your Personalization: Learning Topic level Personalization in Online Services
privacy, personalization
null
null
null
cs.LG cs.IR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Online service platforms (OSPs), such as search engines, news-websites, ad-providers, etc., serve highly pe rsonalized content to the user, based on the profile extracted from his history with the OSP. Although personalization (generally) leads to a better user experience, it also raises privacy concerns for the user...
[ { "version": "v1", "created": "Fri, 14 Dec 2012 04:12:21 GMT" } ]
2012-12-17T00:00:00
[ [ "Majumder", "Anirban", "" ], [ "Shrivastava", "Nisheeth", "" ] ]
TITLE: Know Your Personalization: Learning Topic level Personalization in Online Services ABSTRACT: Online service platforms (OSPs), such as search engines, news-websites, ad-providers, etc., serve highly pe rsonalized content to the user, based on the profile extracted from his history with the OSP. Although per...
1212.2981
Celine Beauval
C\'eline Beauval (ISTerre), Hilal Tasan (ISTerre), Aurore Laurendeau (ISTerre), Elise Delavaud, Fabrice Cotton (ISTerre), Philippe Gu\'eguen (ISTerre), Nicolas Kuehn
On the Testing of Ground--Motion Prediction Equations against Small--Magnitude Data
null
Bulletin of the Seismological Society of America 102, 5 (2012) 1994-2007
10.1785/0120110271
null
physics.geo-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Ground-motion prediction equations (GMPE) are essential in probabilistic seismic hazard studies for estimating the ground motions generated by the seismic sources. In low seismicity regions, only weak motions are available in the lifetime of accelerometric networks, and the equations selected for the probabilistic st...
[ { "version": "v1", "created": "Wed, 12 Dec 2012 21:01:39 GMT" } ]
2012-12-14T00:00:00
[ [ "Beauval", "Céline", "", "ISTerre" ], [ "Tasan", "Hilal", "", "ISTerre" ], [ "Laurendeau", "Aurore", "", "ISTerre" ], [ "Delavaud", "Elise", "", "ISTerre" ], [ "Cotton", "Fabrice", "", "ISTerre" ], [ "Guéguen",...
TITLE: On the Testing of Ground--Motion Prediction Equations against Small--Magnitude Data ABSTRACT: Ground-motion prediction equations (GMPE) are essential in probabilistic seismic hazard studies for estimating the ground motions generated by the seismic sources. In low seismicity regions, only weak motions are ...
1212.3013
Gabriele Modena
K. Massoudi, G. Modena
Product/Brand extraction from WikiPedia
17 pages. Manuscript first creation date: November 27, 2009. At the time of first creation both authors were affiliated with the University of Amsterdam (The Netherlands)
null
null
null
cs.IR cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper we describe the task of extracting product and brand pages from wikipedia. We present an experimental environment and setup built on top of a dataset of wikipedia pages we collected. We introduce a method for recognition of product pages modelled as a boolean probabilistic classification task. We show t...
[ { "version": "v1", "created": "Wed, 12 Dec 2012 23:25:46 GMT" } ]
2012-12-14T00:00:00
[ [ "Massoudi", "K.", "" ], [ "Modena", "G.", "" ] ]
TITLE: Product/Brand extraction from WikiPedia ABSTRACT: In this paper we describe the task of extracting product and brand pages from wikipedia. We present an experimental environment and setup built on top of a dataset of wikipedia pages we collected. We introduce a method for recognition of product pages modelle...
1212.3152
Benjamin Laken
Benjamin A. Laken, Jasa \v{C}alogovi\'c, Tariq Shahbaz and Enric Pall\'e
Examining a solar climate link in diurnal temperature ranges
18 pages, 7 figures, 1 table
Laken B.A., J. Calogovic, T. Shahbaz, & E. Palle (2012) Examining a solar-climate link in diurnal temperature ranges. Journal of Geophysical Research, 117, D18112, 9PP
10.1029/2012JD17683
null
physics.ao-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A recent study has suggested a link between the surface level diurnal temperature range (DTR) and variations in the cosmic ray (CR) flux. As the DTR is an effective proxy for cloud cover, this result supports the notion that widespread cloud changes may be induced by the CR flux. If confirmed, this would have signifi...
[ { "version": "v1", "created": "Thu, 13 Dec 2012 12:42:43 GMT" } ]
2012-12-14T00:00:00
[ [ "Laken", "Benjamin A.", "" ], [ "Čalogović", "Jasa", "" ], [ "Shahbaz", "Tariq", "" ], [ "Pallé", "Enric", "" ] ]
TITLE: Examining a solar climate link in diurnal temperature ranges ABSTRACT: A recent study has suggested a link between the surface level diurnal temperature range (DTR) and variations in the cosmic ray (CR) flux. As the DTR is an effective proxy for cloud cover, this result supports the notion that widespread cl...
1212.3287
Celine Beauval
C\'eline Beauval (ISTerre), F. Cotton (ISTerre), N. Abrahamson, N. Theodulidis (ITSAK), E. Delavaud (ISTerre), L. Rodriguez (ISTerre), F. Scherbaum, A. Haendel
Regional differences in subduction ground motions
10 pages
World Conference on Earthquake Engineering, Lisbonne : Portugal (2012)
null
null
physics.geo-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A few ground-motion prediction models have been published in the last years, for predicting ground motions produced by interface and intraslab earthquakes. When one must carry out a probabilistic seismic hazard analysis in a region including a subduction zone, GMPEs must be selected to feed a logic tree. In the prese...
[ { "version": "v1", "created": "Thu, 13 Dec 2012 19:41:24 GMT" } ]
2012-12-14T00:00:00
[ [ "Beauval", "Céline", "", "ISTerre" ], [ "Cotton", "F.", "", "ISTerre" ], [ "Abrahamson", "N.", "", "ITSAK" ], [ "Theodulidis", "N.", "", "ITSAK" ], [ "Delavaud", "E.", "", "ISTerre" ], [ "Rodriguez", "L.", ...
TITLE: Regional differences in subduction ground motions ABSTRACT: A few ground-motion prediction models have been published in the last years, for predicting ground motions produced by interface and intraslab earthquakes. When one must carry out a probabilistic seismic hazard analysis in a region including a subdu...
1212.2692
Ghazali Osman
Ghazali Osman, Muhammad Suzuri Hitam and Mohd Nasir Ismail
Enhanced skin colour classifier using RGB Ratio model
14 pages; International Journal on Soft Computing (IJSC) Vol.3, No.4, November 2012
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Skin colour detection is frequently been used for searching people, face detection, pornographic filtering and hand tracking. The presence of skin or non-skin in digital image can be determined by manipulating pixels colour or pixels texture. The main problem in skin colour detection is to represent the skin colour d...
[ { "version": "v1", "created": "Wed, 12 Dec 2012 03:01:00 GMT" } ]
2012-12-13T00:00:00
[ [ "Osman", "Ghazali", "" ], [ "Hitam", "Muhammad Suzuri", "" ], [ "Ismail", "Mohd Nasir", "" ] ]
TITLE: Enhanced skin colour classifier using RGB Ratio model ABSTRACT: Skin colour detection is frequently been used for searching people, face detection, pornographic filtering and hand tracking. The presence of skin or non-skin in digital image can be determined by manipulating pixels colour or pixels texture. Th...
1212.2823
Shuran Song
Shuran Song, Jianxiong Xiao
Tracking Revisited using RGBD Camera: Baseline and Benchmark
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Although there has been significant progress in the past decade,tracking is still a very challenging computer vision task, due to problems such as occlusion and model drift.Recently, the increased popularity of depth sensors e.g. Microsoft Kinect has made it easy to obtain depth data at low cost.This may be a game ch...
[ { "version": "v1", "created": "Wed, 12 Dec 2012 14:02:41 GMT" } ]
2012-12-13T00:00:00
[ [ "Song", "Shuran", "" ], [ "Xiao", "Jianxiong", "" ] ]
TITLE: Tracking Revisited using RGBD Camera: Baseline and Benchmark ABSTRACT: Although there has been significant progress in the past decade,tracking is still a very challenging computer vision task, due to problems such as occlusion and model drift.Recently, the increased popularity of depth sensors e.g. Microsof...
1212.2468
David Maxwell Chickering
David Maxwell Chickering, Christopher Meek, David Heckerman
Large-Sample Learning of Bayesian Networks is NP-Hard
Appears in Proceedings of the Nineteenth Conference on Uncertainty in Artificial Intelligence (UAI2003)
null
null
UAI-P-2003-PG-124-133
cs.LG cs.AI stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we provide new complexity results for algorithms that learn discrete-variable Bayesian networks from data. Our results apply whenever the learning algorithm uses a scoring criterion that favors the simplest model able to represent the generative distribution exactly. Our results therefore hold whenever...
[ { "version": "v1", "created": "Fri, 19 Oct 2012 15:04:28 GMT" } ]
2012-12-12T00:00:00
[ [ "Chickering", "David Maxwell", "" ], [ "Meek", "Christopher", "" ], [ "Heckerman", "David", "" ] ]
TITLE: Large-Sample Learning of Bayesian Networks is NP-Hard ABSTRACT: In this paper, we provide new complexity results for algorithms that learn discrete-variable Bayesian networks from data. Our results apply whenever the learning algorithm uses a scoring criterion that favors the simplest model able to represent...
1212.2478
Rong Jin
Rong Jin, Luo Si, ChengXiang Zhai
Preference-based Graphic Models for Collaborative Filtering
Appears in Proceedings of the Nineteenth Conference on Uncertainty in Artificial Intelligence (UAI2003)
null
null
UAI-P-2003-PG-329-336
cs.IR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Collaborative filtering is a very useful general technique for exploiting the preference patterns of a group of users to predict the utility of items to a particular user. Previous research has studied several probabilistic graphic models for collaborative filtering with promising results. However, while these models...
[ { "version": "v1", "created": "Fri, 19 Oct 2012 15:06:09 GMT" } ]
2012-12-12T00:00:00
[ [ "Jin", "Rong", "" ], [ "Si", "Luo", "" ], [ "Zhai", "ChengXiang", "" ] ]
TITLE: Preference-based Graphic Models for Collaborative Filtering ABSTRACT: Collaborative filtering is a very useful general technique for exploiting the preference patterns of a group of users to predict the utility of items to a particular user. Previous research has studied several probabilistic graphic models ...
1212.2483
Amir Globerson
Amir Globerson, Gal Chechik, Naftali Tishby
Sufficient Dimensionality Reduction with Irrelevant Statistics
Appears in Proceedings of the Nineteenth Conference on Uncertainty in Artificial Intelligence (UAI2003)
null
null
UAI-P-2003-PG-281-288
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The problem of finding a reduced dimensionality representation of categorical variables while preserving their most relevant characteristics is fundamental for the analysis of complex data. Specifically, given a co-occurrence matrix of two variables, one often seeks a compact representation of one variable which pres...
[ { "version": "v1", "created": "Fri, 19 Oct 2012 15:05:46 GMT" } ]
2012-12-12T00:00:00
[ [ "Globerson", "Amir", "" ], [ "Chechik", "Gal", "" ], [ "Tishby", "Naftali", "" ] ]
TITLE: Sufficient Dimensionality Reduction with Irrelevant Statistics ABSTRACT: The problem of finding a reduced dimensionality representation of categorical variables while preserving their most relevant characteristics is fundamental for the analysis of complex data. Specifically, given a co-occurrence matrix of ...
1212.2546
Jonathan Masci
Jonathan Masci and Jes\'us Angulo and J\"urgen Schmidhuber
A Learning Framework for Morphological Operators using Counter-Harmonic Mean
Submitted to ISMM'13
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present a novel framework for learning morphological operators using counter-harmonic mean. It combines concepts from morphology and convolutional neural networks. A thorough experimental validation analyzes basic morphological operators dilation and erosion, opening and closing, as well as the much more complex t...
[ { "version": "v1", "created": "Tue, 11 Dec 2012 17:29:04 GMT" } ]
2012-12-12T00:00:00
[ [ "Masci", "Jonathan", "" ], [ "Angulo", "Jesús", "" ], [ "Schmidhuber", "Jürgen", "" ] ]
TITLE: A Learning Framework for Morphological Operators using Counter-Harmonic Mean ABSTRACT: We present a novel framework for learning morphological operators using counter-harmonic mean. It combines concepts from morphology and convolutional neural networks. A thorough experimental validation analyzes basic mor...
1212.2573
K. S. Sesh Kumar
K. S. Sesh Kumar (LIENS, INRIA Paris - Rocquencourt), Francis Bach (LIENS, INRIA Paris - Rocquencourt)
Convex Relaxations for Learning Bounded Treewidth Decomposable Graphs
null
null
null
null
cs.LG cs.DS stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We consider the problem of learning the structure of undirected graphical models with bounded treewidth, within the maximum likelihood framework. This is an NP-hard problem and most approaches consider local search techniques. In this paper, we pose it as a combinatorial optimization problem, which is then relaxed to...
[ { "version": "v1", "created": "Tue, 11 Dec 2012 18:22:31 GMT" } ]
2012-12-12T00:00:00
[ [ "Kumar", "K. S. Sesh", "", "LIENS, INRIA Paris - Rocquencourt" ], [ "Bach", "Francis", "", "LIENS, INRIA Paris - Rocquencourt" ] ]
TITLE: Convex Relaxations for Learning Bounded Treewidth Decomposable Graphs ABSTRACT: We consider the problem of learning the structure of undirected graphical models with bounded treewidth, within the maximum likelihood framework. This is an NP-hard problem and most approaches consider local search techniques. In...
1212.1909
Luay Nakhleh
Yun Yu and Luay Nakhleh
Fast Algorithms for Reconciliation under Hybridization and Incomplete Lineage Sorting
null
null
null
null
q-bio.PE cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Reconciling a gene tree with a species tree is an important task that reveals much about the evolution of genes, genomes, and species, as well as about the molecular function of genes. A wide array of computational tools have been devised for this task under certain evolutionary events such as hybridization, gene dup...
[ { "version": "v1", "created": "Sun, 9 Dec 2012 18:12:55 GMT" } ]
2012-12-11T00:00:00
[ [ "Yu", "Yun", "" ], [ "Nakhleh", "Luay", "" ] ]
TITLE: Fast Algorithms for Reconciliation under Hybridization and Incomplete Lineage Sorting ABSTRACT: Reconciling a gene tree with a species tree is an important task that reveals much about the evolution of genes, genomes, and species, as well as about the molecular function of genes. A wide array of computatio...
1212.1936
Nicolas Boulanger-Lewandowski
Nicolas Boulanger-Lewandowski, Yoshua Bengio and Pascal Vincent
High-dimensional sequence transduction
null
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We investigate the problem of transforming an input sequence into a high-dimensional output sequence in order to transcribe polyphonic audio music into symbolic notation. We introduce a probabilistic model based on a recurrent neural network that is able to learn realistic output distributions given the input and we ...
[ { "version": "v1", "created": "Sun, 9 Dec 2012 23:28:02 GMT" } ]
2012-12-11T00:00:00
[ [ "Boulanger-Lewandowski", "Nicolas", "" ], [ "Bengio", "Yoshua", "" ], [ "Vincent", "Pascal", "" ] ]
TITLE: High-dimensional sequence transduction ABSTRACT: We investigate the problem of transforming an input sequence into a high-dimensional output sequence in order to transcribe polyphonic audio music into symbolic notation. We introduce a probabilistic model based on a recurrent neural network that is able to le...
1212.1633
Andrei Bulatov
Cong Wang and Andrei A. Bulatov
Inferring Attitude in Online Social Networks Based On Quadratic Correlation
18 pages, 3 figures
null
null
null
cs.SI physics.soc-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The structure of an online social network in most cases cannot be described just by links between its members. We study online social networks, in which members may have certain attitude, positive or negative toward each other, and so the network consists of a mixture of both positive and negative relationships. Our ...
[ { "version": "v1", "created": "Fri, 7 Dec 2012 15:45:35 GMT" } ]
2012-12-10T00:00:00
[ [ "Wang", "Cong", "" ], [ "Bulatov", "Andrei A.", "" ] ]
TITLE: Inferring Attitude in Online Social Networks Based On Quadratic Correlation ABSTRACT: The structure of an online social network in most cases cannot be described just by links between its members. We study online social networks, in which members may have certain attitude, positive or negative toward each ...
1211.6086
Kang Zhao
Kang Zhao, Greta Greer, Baojun Qiu, Prasenjit Mitra, Kenneth Portier, and John Yen
Finding influential users of an online health community: a new metric based on sentiment influence
Working paper
null
null
null
cs.SI cs.CY physics.soc-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
What characterizes influential users in online health communities (OHCs)? We hypothesize that (1) the emotional support received by OHC members can be assessed from their sentiment ex-pressed in online interactions, and (2) such assessments can help to identify influential OHC members. Through text mining and sentime...
[ { "version": "v1", "created": "Mon, 26 Nov 2012 20:37:00 GMT" }, { "version": "v2", "created": "Wed, 5 Dec 2012 23:12:05 GMT" } ]
2012-12-07T00:00:00
[ [ "Zhao", "Kang", "" ], [ "Greer", "Greta", "" ], [ "Qiu", "Baojun", "" ], [ "Mitra", "Prasenjit", "" ], [ "Portier", "Kenneth", "" ], [ "Yen", "John", "" ] ]
TITLE: Finding influential users of an online health community: a new metric based on sentiment influence ABSTRACT: What characterizes influential users in online health communities (OHCs)? We hypothesize that (1) the emotional support received by OHC members can be assessed from their sentiment ex-pressed in onl...
1212.0888
Roozbeh Rajabi
Roozbeh Rajabi, Hassan Ghassemian
Unmixing of Hyperspectral Data Using Robust Statistics-based NMF
4 pages, conference
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Mixed pixels are presented in hyperspectral images due to low spatial resolution of hyperspectral sensors. Spectral unmixing decomposes mixed pixels spectra into endmembers spectra and abundance fractions. In this paper using of robust statistics-based nonnegative matrix factorization (RNMF) for spectral unmixing of ...
[ { "version": "v1", "created": "Tue, 4 Dec 2012 21:59:35 GMT" } ]
2012-12-06T00:00:00
[ [ "Rajabi", "Roozbeh", "" ], [ "Ghassemian", "Hassan", "" ] ]
TITLE: Unmixing of Hyperspectral Data Using Robust Statistics-based NMF ABSTRACT: Mixed pixels are presented in hyperspectral images due to low spatial resolution of hyperspectral sensors. Spectral unmixing decomposes mixed pixels spectra into endmembers spectra and abundance fractions. In this paper using of robus...
1212.1037
Tushar Rao Mr.
Tushar Rao (NSIT-Delhi) and Saket Srivastava (IIIT-Delhi)
Modeling Movements in Oil, Gold, Forex and Market Indices using Search Volume Index and Twitter Sentiments
10 pages, 4 figures, 9 Tables
null
null
IIITD-TR-2012-005
cs.CE cs.SI q-fin.GN
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Study of the forecasting models using large scale microblog discussions and the search behavior data can provide a good insight for better understanding the market movements. In this work we collected a dataset of 2 million tweets and search volume index (SVI from Google) for a period of June 2010 to September 2011. ...
[ { "version": "v1", "created": "Wed, 5 Dec 2012 14:28:40 GMT" } ]
2012-12-06T00:00:00
[ [ "Rao", "Tushar", "", "NSIT-Delhi" ], [ "Srivastava", "Saket", "", "IIIT-Delhi" ] ]
TITLE: Modeling Movements in Oil, Gold, Forex and Market Indices using Search Volume Index and Twitter Sentiments ABSTRACT: Study of the forecasting models using large scale microblog discussions and the search behavior data can provide a good insight for better understanding the market movements. In this work we...
1212.1100
Jim Smith Dr
J. E. Smith, P. Caleb-Solly, M. A. Tahir, D. Sannen, H. van-Brussel
Making Early Predictions of the Accuracy of Machine Learning Applications
35 pagers, 12 figures
null
null
null
cs.LG cs.AI stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The accuracy of machine learning systems is a widely studied research topic. Established techniques such as cross-validation predict the accuracy on unseen data of the classifier produced by applying a given learning method to a given training data set. However, they do not predict whether incurring the cost of obtai...
[ { "version": "v1", "created": "Wed, 5 Dec 2012 17:07:39 GMT" } ]
2012-12-06T00:00:00
[ [ "Smith", "J. E.", "" ], [ "Caleb-Solly", "P.", "" ], [ "Tahir", "M. A.", "" ], [ "Sannen", "D.", "" ], [ "van-Brussel", "H.", "" ] ]
TITLE: Making Early Predictions of the Accuracy of Machine Learning Applications ABSTRACT: The accuracy of machine learning systems is a widely studied research topic. Established techniques such as cross-validation predict the accuracy on unseen data of the classifier produced by applying a given learning method...
1212.1131
Lior Rokach
Gilad Katz, Guy Shani, Bracha Shapira, Lior Rokach
Using Wikipedia to Boost SVD Recommender Systems
null
null
null
null
cs.LG cs.IR stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Singular Value Decomposition (SVD) has been used successfully in recent years in the area of recommender systems. In this paper we present how this model can be extended to consider both user ratings and information from Wikipedia. By mapping items to Wikipedia pages and quantifying their similarity, we are able to u...
[ { "version": "v1", "created": "Wed, 5 Dec 2012 19:03:39 GMT" } ]
2012-12-06T00:00:00
[ [ "Katz", "Gilad", "" ], [ "Shani", "Guy", "" ], [ "Shapira", "Bracha", "" ], [ "Rokach", "Lior", "" ] ]
TITLE: Using Wikipedia to Boost SVD Recommender Systems ABSTRACT: Singular Value Decomposition (SVD) has been used successfully in recent years in the area of recommender systems. In this paper we present how this model can be extended to consider both user ratings and information from Wikipedia. By mapping items t...
1212.0763
Modou Gueye M.
Modou Gueye, Talel Abdessalem, Hubert Naacke
Dynamic recommender system : using cluster-based biases to improve the accuracy of the predictions
31 pages, 7 figures
null
null
null
cs.LG cs.DB cs.IR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
It is today accepted that matrix factorization models allow a high quality of rating prediction in recommender systems. However, a major drawback of matrix factorization is its static nature that results in a progressive declining of the accuracy of the predictions after each factorization. This is due to the fact th...
[ { "version": "v1", "created": "Mon, 3 Dec 2012 13:00:27 GMT" } ]
2012-12-05T00:00:00
[ [ "Gueye", "Modou", "" ], [ "Abdessalem", "Talel", "" ], [ "Naacke", "Hubert", "" ] ]
TITLE: Dynamic recommender system : using cluster-based biases to improve the accuracy of the predictions ABSTRACT: It is today accepted that matrix factorization models allow a high quality of rating prediction in recommender systems. However, a major drawback of matrix factorization is its static nature that re...
1212.0030
Andrew Habib
Osama Khalil, Andrew Habib
Viewpoint Invariant Object Detector
null
null
null
null
cs.CV
http://creativecommons.org/licenses/by/3.0/
Object Detection is the task of identifying the existence of an object class instance and locating it within an image. Difficulties in handling high intra-class variations constitute major obstacles to achieving high performance on standard benchmark datasets (scale, viewpoint, lighting conditions and orientation var...
[ { "version": "v1", "created": "Fri, 30 Nov 2012 22:35:19 GMT" } ]
2012-12-04T00:00:00
[ [ "Khalil", "Osama", "" ], [ "Habib", "Andrew", "" ] ]
TITLE: Viewpoint Invariant Object Detector ABSTRACT: Object Detection is the task of identifying the existence of an object class instance and locating it within an image. Difficulties in handling high intra-class variations constitute major obstacles to achieving high performance on standard benchmark datasets (sc...
1212.0087
Nader Jelassi
Mohamed Nader Jelassi and Sadok Ben Yahia and Engelbert Mephu Nguifo
A scalable mining of frequent quadratic concepts in d-folksonomies
null
null
null
null
cs.SI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Folksonomy mining is grasping the interest of web 2.0 community since it represents the core data of social resource sharing systems. However, a scrutiny of the related works interested in mining folksonomies unveils that the time stamp dimension has not been considered. For example, the wealthy number of works dedic...
[ { "version": "v1", "created": "Sat, 1 Dec 2012 09:16:35 GMT" } ]
2012-12-04T00:00:00
[ [ "Jelassi", "Mohamed Nader", "" ], [ "Yahia", "Sadok Ben", "" ], [ "Nguifo", "Engelbert Mephu", "" ] ]
TITLE: A scalable mining of frequent quadratic concepts in d-folksonomies ABSTRACT: Folksonomy mining is grasping the interest of web 2.0 community since it represents the core data of social resource sharing systems. However, a scrutiny of the related works interested in mining folksonomies unveils that the time s...
1212.0141
Yiye Ruan
Hemant Purohit and Yiye Ruan and David Fuhry and Srinivasan Parthasarathy and Amit Sheth
On the Role of Social Identity and Cohesion in Characterizing Online Social Communities
null
null
null
null
cs.SI physics.soc-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Two prevailing theories for explaining social group or community structure are cohesion and identity. The social cohesion approach posits that social groups arise out of an aggregation of individuals that have mutual interpersonal attraction as they share common characteristics. These characteristics can range from c...
[ { "version": "v1", "created": "Sat, 1 Dec 2012 18:03:33 GMT" } ]
2012-12-04T00:00:00
[ [ "Purohit", "Hemant", "" ], [ "Ruan", "Yiye", "" ], [ "Fuhry", "David", "" ], [ "Parthasarathy", "Srinivasan", "" ], [ "Sheth", "Amit", "" ] ]
TITLE: On the Role of Social Identity and Cohesion in Characterizing Online Social Communities ABSTRACT: Two prevailing theories for explaining social group or community structure are cohesion and identity. The social cohesion approach posits that social groups arise out of an aggregation of individuals that have...
1212.0146
Yiye Ruan
Yiye Ruan and David Fuhry and Srinivasan Parthasarathy
Efficient Community Detection in Large Networks using Content and Links
null
null
null
null
cs.SI physics.soc-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper we discuss a very simple approach of combining content and link information in graph structures for the purpose of community discovery, a fundamental task in network analysis. Our approach hinges on the basic intuition that many networks contain noise in the link structure and that content information c...
[ { "version": "v1", "created": "Sat, 1 Dec 2012 18:41:34 GMT" } ]
2012-12-04T00:00:00
[ [ "Ruan", "Yiye", "" ], [ "Fuhry", "David", "" ], [ "Parthasarathy", "Srinivasan", "" ] ]
TITLE: Efficient Community Detection in Large Networks using Content and Links ABSTRACT: In this paper we discuss a very simple approach of combining content and link information in graph structures for the purpose of community discovery, a fundamental task in network analysis. Our approach hinges on the basic intu...
1212.0317
M HM Krishna Prasad Dr
B. Adinarayana Reddy, O. Srinivasa Rao and M. H. M. Krishna Prasad
An Improved UP-Growth High Utility Itemset Mining
(0975 8887)
International Journal of Computer Applications Volume 58, No.2, 2012, 25-28
10.5120/9255-3424
null
cs.DB
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Efficient discovery of frequent itemsets in large datasets is a crucial task of data mining. In recent years, several approaches have been proposed for generating high utility patterns, they arise the problems of producing a large number of candidate itemsets for high utility itemsets and probably degrades mining per...
[ { "version": "v1", "created": "Mon, 3 Dec 2012 08:50:50 GMT" } ]
2012-12-04T00:00:00
[ [ "Reddy", "B. Adinarayana", "" ], [ "Rao", "O. Srinivasa", "" ], [ "Prasad", "M. H. M. Krishna", "" ] ]
TITLE: An Improved UP-Growth High Utility Itemset Mining ABSTRACT: Efficient discovery of frequent itemsets in large datasets is a crucial task of data mining. In recent years, several approaches have been proposed for generating high utility patterns, they arise the problems of producing a large number of candidat...
1212.0402
Khurram Soomro
Khurram Soomro, Amir Roshan Zamir and Mubarak Shah
UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild
null
null
null
CRCV-TR-12-01
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We introduce UCF101 which is currently the largest dataset of human actions. It consists of 101 action classes, over 13k clips and 27 hours of video data. The database consists of realistic user uploaded videos containing camera motion and cluttered background. Additionally, we provide baseline action recognition res...
[ { "version": "v1", "created": "Mon, 3 Dec 2012 14:45:31 GMT" } ]
2012-12-04T00:00:00
[ [ "Soomro", "Khurram", "" ], [ "Zamir", "Amir Roshan", "" ], [ "Shah", "Mubarak", "" ] ]
TITLE: UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild ABSTRACT: We introduce UCF101 which is currently the largest dataset of human actions. It consists of 101 action classes, over 13k clips and 27 hours of video data. The database consists of realistic user uploaded videos containing camera...
1211.3375
Stephan Seufert
Stephan Seufert, Avishek Anand, Srikanta Bedathur, Gerhard Weikum
High-Performance Reachability Query Processing under Index Size Restrictions
30 pages
null
null
null
cs.DB cs.SI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we propose a scalable and highly efficient index structure for the reachability problem over graphs. We build on the well-known node interval labeling scheme where the set of vertices reachable from a particular node is compactly encoded as a collection of node identifier ranges. We impose an explicit ...
[ { "version": "v1", "created": "Wed, 14 Nov 2012 18:28:28 GMT" }, { "version": "v2", "created": "Mon, 19 Nov 2012 16:06:19 GMT" }, { "version": "v3", "created": "Mon, 26 Nov 2012 14:13:28 GMT" }, { "version": "v4", "created": "Wed, 28 Nov 2012 09:40:31 GMT" }, { "v...
2012-12-03T00:00:00
[ [ "Seufert", "Stephan", "" ], [ "Anand", "Avishek", "" ], [ "Bedathur", "Srikanta", "" ], [ "Weikum", "Gerhard", "" ] ]
TITLE: High-Performance Reachability Query Processing under Index Size Restrictions ABSTRACT: In this paper, we propose a scalable and highly efficient index structure for the reachability problem over graphs. We build on the well-known node interval labeling scheme where the set of vertices reachable from a part...
1211.6851
Chiheb-Eddine Ben n'cir C.B.N'cir
Chiheb-Eddine Ben N'Cir and Nadia Essoussi
Classification Recouvrante Bas\'ee sur les M\'ethodes \`a Noyau
Les 43\`emes Journ\'ees de Statistique
Les 43\`emes Journ\'ees de Statistique 2011
null
null
cs.LG stat.CO stat.ME stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Overlapping clustering problem is an important learning issue in which clusters are not mutually exclusive and each object may belongs simultaneously to several clusters. This paper presents a kernel based method that produces overlapping clusters on a high feature space using mercer kernel techniques to improve sepa...
[ { "version": "v1", "created": "Thu, 29 Nov 2012 09:22:19 GMT" } ]
2012-11-30T00:00:00
[ [ "N'Cir", "Chiheb-Eddine Ben", "" ], [ "Essoussi", "Nadia", "" ] ]
TITLE: Classification Recouvrante Bas\'ee sur les M\'ethodes \`a Noyau ABSTRACT: Overlapping clustering problem is an important learning issue in which clusters are not mutually exclusive and each object may belongs simultaneously to several clusters. This paper presents a kernel based method that produces overlapp...
1211.6859
Chiheb-Eddine Ben n'cir C.B.N'cir
Chiheb-Eddine Ben N'Cir and Nadia Essoussi and Patrice Bertrand
Overlapping clustering based on kernel similarity metric
Second Meeting on Statistics and Data Mining 2010
Second Meeting on Statistics and Data Mining Second Meeting on Statistics and Data Mining March 11-12, 2010
null
null
stat.ML cs.LG stat.ME
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Producing overlapping schemes is a major issue in clustering. Recent proposed overlapping methods relies on the search of an optimal covering and are based on different metrics, such as Euclidean distance and I-Divergence, used to measure closeness between observations. In this paper, we propose the use of another me...
[ { "version": "v1", "created": "Thu, 29 Nov 2012 09:35:30 GMT" } ]
2012-11-30T00:00:00
[ [ "N'Cir", "Chiheb-Eddine Ben", "" ], [ "Essoussi", "Nadia", "" ], [ "Bertrand", "Patrice", "" ] ]
TITLE: Overlapping clustering based on kernel similarity metric ABSTRACT: Producing overlapping schemes is a major issue in clustering. Recent proposed overlapping methods relies on the search of an optimal covering and are based on different metrics, such as Euclidean distance and I-Divergence, used to measure clo...
1211.2881
Junyoung Chung
Junyoung Chung, Donghoon Lee, Youngjoo Seo, and Chang D. Yoo
Deep Attribute Networks
This paper has been withdrawn by the author due to a crucial grammatical errors
null
null
null
cs.CV cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Obtaining compact and discriminative features is one of the major challenges in many of the real-world image classification tasks such as face verification and object recognition. One possible approach is to represent input image on the basis of high-level features that carry semantic meaning which humans can underst...
[ { "version": "v1", "created": "Tue, 13 Nov 2012 03:41:31 GMT" }, { "version": "v2", "created": "Tue, 20 Nov 2012 11:30:46 GMT" }, { "version": "v3", "created": "Wed, 28 Nov 2012 08:39:03 GMT" } ]
2012-11-29T00:00:00
[ [ "Chung", "Junyoung", "" ], [ "Lee", "Donghoon", "" ], [ "Seo", "Youngjoo", "" ], [ "Yoo", "Chang D.", "" ] ]
TITLE: Deep Attribute Networks ABSTRACT: Obtaining compact and discriminative features is one of the major challenges in many of the real-world image classification tasks such as face verification and object recognition. One possible approach is to represent input image on the basis of high-level features that carr...
1208.3665
Christian Riess
Vincent Christlein, Christian Riess, Johannes Jordan, Corinna Riess and Elli Angelopoulou
An Evaluation of Popular Copy-Move Forgery Detection Approaches
Main paper: 14 pages, supplemental material: 12 pages, main paper appeared in IEEE Transaction on Information Forensics and Security
IEEE Transactions on Information Forensics and Security, volume 7, number 6, 2012, pp. 1841-1854
10.1109/TIFS.2012.2218597
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A copy-move forgery is created by copying and pasting content within the same image, and potentially post-processing it. In recent years, the detection of copy-move forgeries has become one of the most actively researched topics in blind image forensics. A considerable number of different algorithms have been propose...
[ { "version": "v1", "created": "Fri, 17 Aug 2012 19:41:23 GMT" }, { "version": "v2", "created": "Mon, 26 Nov 2012 20:53:51 GMT" } ]
2012-11-27T00:00:00
[ [ "Christlein", "Vincent", "" ], [ "Riess", "Christian", "" ], [ "Jordan", "Johannes", "" ], [ "Riess", "Corinna", "" ], [ "Angelopoulou", "Elli", "" ] ]
TITLE: An Evaluation of Popular Copy-Move Forgery Detection Approaches ABSTRACT: A copy-move forgery is created by copying and pasting content within the same image, and potentially post-processing it. In recent years, the detection of copy-move forgeries has become one of the most actively researched topics in bli...
1211.5625
Sriganesh Srihari Dr
Sriganesh Srihari, Hon Wai Leong
A survey of computational methods for protein complex prediction from protein interaction networks
27 pages, 5 figures, 4 tables
Srihari, S., Leong, HW., J Bioinform Comput Biol 11(2): 1230002, 2013
10.1142/S021972001230002X
null
cs.CE q-bio.MN
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Complexes of physically interacting proteins are one of the fundamental functional units responsible for driving key biological mechanisms within the cell. Their identification is therefore necessary not only to understand complex formation but also the higher level organization of the cell. With the advent of high-t...
[ { "version": "v1", "created": "Sat, 24 Nov 2012 00:30:33 GMT" } ]
2012-11-27T00:00:00
[ [ "Srihari", "Sriganesh", "" ], [ "Leong", "Hon Wai", "" ] ]
TITLE: A survey of computational methods for protein complex prediction from protein interaction networks ABSTRACT: Complexes of physically interacting proteins are one of the fundamental functional units responsible for driving key biological mechanisms within the cell. Their identification is therefore necessar...