index int64 0 20.3k | text stringlengths 0 1.3M | year stringdate 1987-01-01 00:00:00 2024-01-01 00:00:00 | No stringlengths 1 4 |
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4,700 | Semi-Crowdsourced Clustering: Generalizing Crowd Labeling by Robust Distance Metric Learning Jinfeng Yi†, Rong Jin†, Anil K. Jain†, Shaili Jain♮, Tianbao Yang‡ †Michigan State University, East Lansing, MI 48824, USA ♮Yale University, New Haven, CT 06520, USA ‡Machine Learning Lab, GE Global Research, San Ramo... | 2012 | 325 |
4,701 | Online ℓ1-Dictionary Learning with Application to Novel Document Detection Shiva Prasad Kasiviswanathan∗ General Electric Global Research kasivisw@gmail.com Huahua Wang† University of Minnesota huwang@cs.umn.edu Arindam Banerjee† University of Minnesota banerjee@cs.umn.edu Prem Melville IBM T.J.... | 2012 | 326 |
4,702 | Learning curves for multi-task Gaussian process regression Simon R F Ashton King’s College London Department of Mathematics Strand, London WC2R 2LS, U.K. Peter Sollich King’s College London Department of Mathematics Strand, London WC2R 2LS, U.K. peter.sollich@kcl.ac.uk Abstract We study the aver... | 2012 | 327 |
4,703 | Transelliptical Component Analysis Fang Han Department of Biostatistics Johns Hopkins University Baltimore, MD 21210 fhan@jhsph.edu Han Liu Department of Operations Research and Financial Engineering Princeton University, NJ 08544 hanliu@princeton.edu Abstract We propose a high dimensional semip... | 2012 | 328 |
4,704 | Learning the Dependency Structure of Latent Factors Yunlong He∗ Georgia Institute of Technology heyunlong@gatech.edu Yanjun Qi NEC Labs America yanjun@nec-labs.com Koray Kavukcuoglu NEC Labs America koray@nec-labs.com Haesun Park∗ Georgia Institute of Technology hpark@cc.gatech.edu Abstract ... | 2012 | 329 |
4,705 | Deep Learning of Invariant Features via Simulated Fixations in Video Will Y. Zou1, Shenghuo Zhu3, Andrew Y. Ng2, Kai Yu3 1Department of Electrical Engineering, Stanford University, CA 2Department of Computer Science, Stanford University, CA 3NEC Laboratories America, Inc., Cupertino, CA {wzou, ang}@cs.stanf... | 2012 | 33 |
4,706 | Random function priors for exchangeable arrays with applications to graphs and relational data James Robert Lloyd Department of Engineering University of Cambridge Peter Orbanz Department of Statistics Columbia University Zoubin Ghahramani Department of Engineering University of Cambridge Daniel M... | 2012 | 330 |
4,707 | Bayesian Pedigree Analysis using Measure Factorization Alexandre Bouchard-Cˆot´e Statistics Department University of British Columbia bouchard@stat.ubc.ca Bonnie Kirkpatrick Computer Science Department University of British Columbia bbkirk@cs.ubc.ca Abstract Pedigrees, or family trees, are directe... | 2012 | 331 |
4,708 | Density Propagation and Improved Bounds on the Partition Function∗ Stefano Ermon, Carla P. Gomes Dept. of Computer Science Cornell University Ithaca NY 14853, U.S.A. Ashish Sabharwal IBM Watson Research Ctr. Yorktown Heights NY 10598, U.S.A. Bart Selman Dept. of Computer Science Cornell Universi... | 2012 | 332 |
4,709 | A quasi-Newton proximal splitting method S. Becker∗ M.J. Fadili† Abstract A new result in convex analysis on the calculation of proximity operators in certain scaled norms is derived. We describe efficient implementations of the proximity calculation for a useful class of functions; the implementations exploit t... | 2012 | 333 |
4,710 | Waveform Driven Plasticity in BiFeO3 Memristive Devices: Model and Implementation Christian Mayr, Paul Staerke, Johannes Partzsch, Rene Schueffny Institute of Circuits and Systems TU Dresden, Dresden, Germany {christian.mayr,johannes.partzsch,rene.schueffny}@tu-dresden.de Love Cederstroem Zentrum Mikroele... | 2012 | 334 |
4,711 | Multilabel Classification using Bayesian Compressed Sensing Ashish Kapoor†, Prateek Jain‡ and Raajay Viswanathan‡ †Microsoft Research, Redmond, USA ‡Microsoft Research, Bangalore, INDIA {akapoor, prajain, t-rviswa}@microsoft.com Abstract In this paper, we present a Bayesian framework for multilabel classifi... | 2012 | 335 |
4,712 | Online Sum-Product Computation over Trees Mark Herbster Stephen Pasteris Department of Computer Science University College London London WC1E 6BT, England, UK {m.herbster, s.pasteris}@cs.ucl.ac.uk Fabio Vitale Department of Computer Science University of Milan 20135 Milan, Italy fabio.vitale@unimi... | 2012 | 336 |
4,713 | Risk Aversion in Markov Decision Processes via Near-Optimal Chernoff Bounds Teodor Mihai Moldovan Department of Computer Science University of California at Berkeley Berkeley CA 94720, USA moldovan@cs.berkeley.edu Pieter Abbeel Department of Computer Science University of California at Berkeley Berk... | 2012 | 337 |
4,714 | Calibrated Elastic Regularization in Matrix Completion Tingni Sun Statistics Department, The Wharton School University of Pennsylvania Philadelphia, Pennsylvania 19104 tingni@wharton.upenn.edu Cun-Hui Zhang Department of Statistics and Biostatistics Rutgers University Piscataway, New Jersey 08854 ... | 2012 | 338 |
4,715 | Expectation Propagation in Gaussian Process Dynamical Systems Marc Peter Deisenroth∗ Department of Computer Science Technische Universit¨at Darmstadt, Germany Shakir Mohamed∗ Department of Computer Science University of British Columbia, Canada Abstract Rich and complex time-series data, such as those... | 2012 | 339 |
4,716 | Homeostatic plasticity in Bayesian spiking networks as Expectation Maximization with posterior constraints Stefan Habenschuss∗, Johannes Bill∗, Bernhard Nessler Institute for Theoretical Computer Science, Graz University of Technology {habenschuss,bill,nessler}@igi.tugraz.at Abstract Recent spiking network ... | 2012 | 34 |
4,717 | Finite Sample Convergence Rates of Zero-Order Stochastic Optimization Methods John C. Duchi1 Michael I. Jordan1,2 Martin J. Wainwright1,2 Andre Wibisono1 1Department of Electrical Engineering and Computer Science and 2Department of Statistics University of California, Berkeley Berkeley, CA USA 94720 {... | 2012 | 340 |
4,718 | Query Complexity of Derivative-Free Optimization Kevin G. Jamieson University of Wisconsin Madison, WI 53706, USA kgjamieson@wisc.edu Robert D. Nowak University of Wisconsin Madison, WI 53706, USA nowak@engr.wisc.edu Benjamin Recht University of Wisconsin Madison, WI 53706, USA brecht@cs.wisc.ed... | 2012 | 341 |
4,719 | Communication-Efficient Algorithms for Statistical Optimization Yuchen Zhang1 John C. Duchi1 Martin Wainwright1,2 1Department of Electrical Engineering and Computer Science and 2Department of Statistics University of California, Berkeley Berkeley, CA 94720 {yuczhang,jduchi,wainwrig}@eecs.berkeley.edu A... | 2012 | 342 |
4,720 | Selecting Diverse Features via Spectral Regularization Abhimanyu Das∗ Microsoft Research Mountain View abhidas@microsoft.com Anirban Dasgupta Yahoo! Labs Sunnyvale anirban@yahoo-inc.com Ravi Kumar∗ Google Mountain View ravi.k53@gmail.com Abstract We study the problem of diverse feature sel... | 2012 | 343 |
4,721 | Fast Bayesian Inference for Non-Conjugate Gaussian Process Regression Mohammad Emtiyaz Khan, Shakir Mohamed, and Kevin P. Murphy Department of Computer Science, University of British Columbia Abstract We present a new variational inference algorithm for Gaussian process regression with non-conjugate likelihoo... | 2012 | 344 |
4,722 | Natural Images, Gaussian Mixtures and Dead Leaves Daniel Zoran Interdisciplinary Center for Neural Computation Hebrew University of Jerusalem Israel http : //www . cs . hu j i . ac .il/ daniez Abstract Yair Weiss School of Computer Science and Engineering Hebrew University of Jerusalem Isr... | 2012 | 345 |
4,723 | Memorability of Image Regions Aditya Khosla Jianxiong Xiao Antonio Torralba Aude Oliva Massachusetts Institute of Technology {khosla,xiao,torralba,oliva}@csail.mit.edu Abstract While long term human visual memory can store a remarkable amount of visual information, it tends to degrade over time. Recen... | 2012 | 346 |
4,724 | Projection Retrieval for Classification Madalina Fiterau Machine Learning Department Carnegie Mellon University Pittsburgh, PA 15213 mfiterau@cs.cmu.edu Artur Dubrawski School of Computer Science Carnegie Mellon University Pittsburgh, PA 15213 awd@cs.cmu.edu Abstract In many applications, classifi... | 2012 | 347 |
4,725 | One Permutation Hashing Ping Li Department of Statistical Science Cornell University Art B Owen Department of Statistics Stanford University Cun-Hui Zhang Department of Statistics Rutgers University Abstract Minwise hashing is a standard procedure in the context of search, for efficiently estimat... | 2012 | 348 |
4,726 | The representer theorem for Hilbert spaces: a necessary and sufficient condition Francesco Dinuzzo and Bernhard Sch¨olkopf Max Planck Institute for Intelligent Systems Spemannstrasse 38,72076 T¨ubingen Germany [fdinuzzo@tuebingen.mpg.de, bs@tuebingen.mpg.de] Abstract The representer theorem is a property... | 2012 | 349 |
4,727 | Nonparametric Bayesian Inverse Reinforcement Learning for Multiple Reward Functions Jaedeug Choi and Kee-Eung Kim Department of Computer Science Korea Advanced Institute of Science and Technology Daejeon 305-701, Korea jdchoi@ai.kaist.ac.kr, kekim@cs.kaist.ac.kr Abstract We present a nonparametric Bay... | 2012 | 35 |
4,728 | A Geometric take on Metric Learning Søren Hauberg MPI for Intelligent Systems T¨ubingen, Germany soren.hauberg@tue.mpg.de Oren Freifeld Brown University Providence, US freifeld@dam.brown.edu Michael J. Black MPI for Intelligent Systems T¨ubingen, Germany black@tue.mpg.de Abstract Multi-metri... | 2012 | 350 |
4,729 | Iterative Thresholding Algorithm for Sparse Inverse Covariance Estimation Dominique Guillot Dept. of Statistics Stanford University Stanford, CA 94305 dguillot@stanford.edu Bala Rajaratnam Dept. of Statistics Stanford University Stanford, CA 94305 brajarat@stanford.edu Benjamin T. Rolfs ICME ... | 2012 | 351 |
4,730 | Online allocation and homogeneous partitioning for piecewise constant mean-approximation Odalric Ambrym Maillard Montanuniversit¨at Leoben Franz-Josef Strasse 18 A-8700 Leoben, Austria odalricambrym.maillard@gmail.com Alexandra Carpentier Statistical Laboratory, CMS Wilberforce Road, Cambridge CB3 0... | 2012 | 352 |
4,731 | Efficient coding provides a direct link between prior and likelihood in perceptual Bayesian inference Xue-Xin Wei and Alan A. Stocker∗ Departments of Psychology and Electrical and Systems Engineering University of Pennsylvania Philadelphia, PA-19104, U.S.A. Abstract A common challenge for Bayesian models... | 2012 | 353 |
4,732 | Pointwise Tracking the Optimal Regression Function Ran El-Yaniv and Yair Wiener Computer Science Department Technion – Israel Institute of Technology {rani,wyair}@{cs,tx}.technion.ac.il Abstract This paper examines the possibility of a ‘reject option’ in the context of least squares regression. It is show... | 2012 | 354 |
4,733 | Globally Convergent Dual MAP LP Relaxation Solvers using Fenchel-Young Margins Alexander G. Schwing ETH Zurich aschwing@inf.ethz.ch Tamir Hazan TTI Chicago tamir@ttic.edu Marc Pollefeys ETH Zurich pomarc@inf.ethz.ch Raquel Urtasun TTI Chicago rurtasun@ttic.edu Abstract While finding the exa... | 2012 | 355 |
4,734 | Nonparametric Reduced Rank Regression Rina Foygel†,∗, Michael Horrell†, Mathias Drton†,‡, John Lafferty† ∗Department of Statistics †Department of Statistics ‡Department of Statistics Stanford University University of Chicago University of Washington Abstract We propose an approach to multivariate nonp... | 2012 | 356 |
4,735 | Density-Difference Estimation Masashi Sugiyama1 Takafumi Kanamori2 Taiji Suzuki3 Marthinus Christoffel du Plessis1 Song Liu1 Ichiro Takeuchi4 1Tokyo Institute of Technology, Japan 2Nagoya University, Japan 3University of Tokyo, Japan 4Nagoya Institute of Technology, Japan Abstract We address the... | 2012 | 357 |
4,736 | Learning the Architecture of Sum-Product Networks Using Clustering on Variables Aaron Dennis Department of Computer Science Brigham Young University Provo, UT 84602 adennis@byu.edu Dan Ventura Department of Computer Science Brigham Young University Provo, UT 84602 ventura@cs.byu.edu Abstract T... | 2012 | 358 |
4,737 | Towards a learning-theoretic analysis of spike-timing dependent plasticity David Balduzzi MPI for Intelligent Systems, T¨ubingen, Germany ETH Zurich, Switzerland david.balduzzi@inf.ethz.ch Michel Besserve MPI for Intelligent Systems and MPI for Biological Cybernetics T¨ubingen, Germany michel.besserve... | 2012 | 359 |
4,738 | Human memory search as a random walk in a semantic network Joshua T. Abbott Department of Psychology University of California, Berkeley Berkeley, CA 94720 joshua.abbott@berkeley.edu Joseph L. Austerweil Department of Psychology University of California, Berkeley Berkeley, CA 94720 joseph.austerwei... | 2012 | 36 |
4,739 | Angular Quantization-based Binary Codes for Fast Similarity Search Yunchao Gong†, Sanjiv Kumar⋆, Vishal Verma†, Svetlana Lazebnik‡ ⋆Google Research, New York, NY 10011, USA †Computer Science Department, University of North Carolina at Chapel Hill, NC 27599, USA ‡Computer Science Department, University of Illi... | 2012 | 360 |
4,740 | Matrix reconstruction with the local max norm Rina Foygel Department of Statistics Stanford University rinafb@stanford.edu Nathan Srebro Toyota Technological Institute at Chicago nati@ttic.edu Ruslan Salakhutdinov Dept. of Statistics and Dept. of Computer Science University of Toronto rsalakhu@utsta... | 2012 | 361 |
4,741 | Near-optimal Differentially Private Principal Components Kamalika Chaudhuri UC San Diego kchaudhuri@ucsd.edu Anand D. Sarwate TTI-Chicago asarwate@ttic.edu Kaushik Sinha UC San Diego ksinha@cs.ucsd.edu Abstract Principal components analysis (PCA) is a standard tool for identifying good lowdimens... | 2012 | 362 |
4,742 | Mandatory Leaf Node Prediction in Hierarchical Multilabel Classification Wei Bi James T. Kwok Department of Computer Science and Engineering Hong Kong University of Science and Technology Clear Water Bay, Hong Kong {weibi,jamesk}@cse.ust.hk Abstract In hierarchical classification, the prediction paths m... | 2012 | 363 |
4,743 | Synchronization can Control Regularization in Neural Systems via Correlated Noise Processes Jake Bouvrie Department of Mathematics Duke University Durham, NC 27708 jvb@math.duke.edu Jean-Jacques Slotine Nonlinear Systems Laboratory Massachusetts Institute of Technology Cambridge, MA 02138 jjs@mit.... | 2012 | 364 |
4,744 | Online Regret Bounds for Undiscounted Continuous Reinforcement Learning Ronald Ortner∗† ∗Montanuniversitaet Leoben 8700 Leoben, Austria rortner@unileoben.ac.at Daniil Ryabko† †INRIA Lille-Nord Europe, ´equipe SequeL 59650 Villeneuve d’Ascq, France daniil@ryabko.net Abstract We derive sublinear reg... | 2012 | 365 |
4,745 | Perceptron Learning of SAT Alex Flint Department of Engineering Science University of Oxford alexf@robots.ox.ac.uk Matthew B. Blaschko Center for Visual Computing Ecole Centrale Paris matthew.blaschko@inria.fr Abstract Boolean satisfiability (SAT) as a canonical NP-complete decision problem is one ... | 2012 | 366 |
4,746 | On Lifting the Gibbs Sampling Algorithm Deepak Venugopal Department of Computer Science The University of Texas at Dallas Richardson, TX, 75080, USA dxv021000@utdallas.edu Vibhav Gogate Department of Computer Science The University of Texas at Dallas Richardson, TX, 75080, USA vgogate@hlt.utdallas.e... | 2012 | 367 |
4,747 | Q-MKL: Matrix-induced Regularization in Multi-Kernel Learning with Applications to Neuroimaging∗ Chris Hinrichs†‡ Vikas Singh†‡ Jiming Peng§ Sterling C. Johnson†‡ †University of Wisconsin §University of Illinois ‡Geriatric Research Education & Clinical Center Madison, WI Urbana-Champaign, IL Wm.... | 2012 | 368 |
4,748 | Label Ranking with Partial Abstention based on Thresholded Probabilistic Models Weiwei Cheng Mathematics and Computer Science Philipps-Universit¨at Marburg Marburg, Germany cheng@mathematik.uni-marburg.de Eyke H¨ullermeier Mathematics and Computer Science Philipps-Universit¨at Marburg Marburg, Germa... | 2012 | 369 |
4,749 | Multi-criteria Anomaly Detection using Pareto Depth Analysis Ko-Jen Hsiao, Kevin S. Xu, Jeff Calder, and Alfred O. Hero III University of Michigan, Ann Arbor, MI, USA 48109 {coolmark,xukevin,jcalder,hero}@umich.edu Abstract We consider the problem of identifying patterns in a data set that exhibit anomalous... | 2012 | 37 |
4,750 | Weighted Likelihood Policy Search with Model Selection Tsuyoshi Ueno ∗ Japan Science and Technology Agency ueno@ar.sanken.osaka-u.ac.jp Kohei Hayashi University of Tokyo hayashi.kohei@gmail.com Takashi Washio Osaka University washio@ar.sanken.osaka-u.ac.jp Yoshinobu Kawahara Osaka University k... | 2012 | 370 |
4,751 | A Spectral Algorithm for Latent Dirichlet Allocation Anima Anandkumar University of California Irvine, CA a.anandkumar@uci.edu Dean P. Foster University of Pennsylvania Philadelphia, PA dean@foster.net Daniel Hsu Microsoft Research Cambridge, MA dahsu@microsoft.com Sham M. Kakade Microsoft R... | 2012 | 38 |
4,752 | The Perturbed Variation Maayan Harel Department of Electrical Engineering Technion, Haifa, Israel maayanga@tx.technion.ac.il Shie Mannor Department of Electrical Engineering Technion, Haifa, Israel shie@ee.technion.ac.il Abstract We introduce a new discrepancy score between two distributions that gi... | 2012 | 39 |
4,753 | The Bethe Partition Function of Log-supermodular Graphical Models Nicholas Ruozzi Communication Theory Laboratory EPFL Lausanne, Switzerland nicholas.ruozzi@epfl.ch Abstract Sudderth, Wainwright, and Willsky conjectured that the Bethe approximation corresponding to any fixed point of the belief propagati... | 2012 | 4 |
4,754 | Discriminatively Trained Sparse Code Gradients for Contour Detection Xiaofeng Ren and Liefeng Bo Intel Science and Technology Center for Pervasive Computing, Intel Labs Seattle, WA 98195, USA {xiaofeng.ren,liefeng.bo}@intel.com Abstract Finding contours in natural images is a fundamental problem that serv... | 2012 | 40 |
4,755 | A Bayesian Approach for Policy Learning from Trajectory Preference Queries Aaron Wilson ∗ School of EECS Oregon State University Alan Fern † School of EECS Oregon State University Prasad Tadepalli ‡ School of EECS Oregon State University Abstract We consider the problem of learning control polic... | 2012 | 41 |
4,756 | Kernel Hyperalignment Alexander Lorbert & Peter J. Ramadge Department of Electrical Engineering Princeton University Abstract We offer a regularized, kernel extension of the multi-set, orthogonal Procrustes problem, or hyperalignment. Our new method, called Kernel Hyperalignment, expands the scope of hype... | 2012 | 42 |
4,757 | Multi-Task Averaging Sergey Feldman, Maya R. Gupta, and Bela A. Frigyik Department of Electrical Engineering University of Washington Seattle, WA 98103 Abstract We present a multi-task learning approach to jointly estimate the means of multiple independent data sets. The proposed multi-task averaging (MTA) ... | 2012 | 43 |
4,758 | A Unifying Perspective of Parametric Policy Search Methods for Markov Decision Processes Thomas Furmston Department of Computer Science University College London T.Furmston@cs.ucl.ac.uk David Barber Department of Computer Science University College London D.Barber@cs.ucl.ac.uk Abstract Parametric ... | 2012 | 44 |
4,759 | Convergence and Energy Landscape for Cheeger Cut Clustering Xavier Bresson City University of Hong Kong Hong Kong xbresson@cityu.edu.hk Thomas Laurent University of California, Riversize Riverside, CA 92521 laurent@math.ucr.edu David Uminsky University of San Francisco San Francisco, CA 94117 ... | 2012 | 45 |
4,760 | A Divide-and-Conquer Procedure for Sparse Inverse Covariance Estimation Cho-Jui Hsieh Dept. of Computer Science University of Texas, Austin cjhsieh@cs.utexas.edu Inderjit S. Dhillon Dept. of Computer Science University of Texas, Austin inderjit@cs.utexas.edu Pradeep Ravikumar Dept. of Computer Sci... | 2012 | 46 |
4,761 | Nonconvex Penalization Using Laplace Exponents and Concave Conjugates Zhihua Zhang and Bojun Tu College of Computer Science & Technology Zhejiang University Hangzhou, China 310027 {zhzhang, tubojun}@zju.edu.cn Abstract In this paper we study sparsity-inducing nonconvex penalty functions using L´evy pr... | 2012 | 47 |
4,762 | How They Vote: Issue-Adjusted Models of Legislative Behavior Sean M. Gerrish∗ Department of Computer Science Princeton University Princeton, NJ 08540 sgerrish@cs.princeton.edu David M. Blei Department of Computer Science Princeton University Princeton, NJ 08540 blei@cs.princeton.edu Abstract W... | 2012 | 48 |
4,763 | Multiclass Learning Approaches: A Theoretical Comparison with Implications Amit Daniely Department of Mathematics The Hebrew University Jerusalem, Israel Sivan Sabato Microsoft Research 1 Memorial Drive Cambridge, MA 02142, USA Shai Shalev-Shwartz School of CS and Eng. The Hebrew University Je... | 2012 | 49 |
4,764 | Selective Labeling via Error Bound Minimization Quanquan Gu†, Tong Zhang‡, Chris Ding§, Jiawei Han† †Department of Computer Science, University of Illinois at Urbana-Champaign ‡Department. of Statistics, Rutgers University §Department. of Computer Science & Engineering, University of Texas at Arlington qgu3@i... | 2012 | 5 |
4,765 | Dynamical And-Or Graph Learning for Object Shape Modeling and Detection Xiaolong Wang Sun Yat-Sen University Guangzhou, P.R. China 510006 dragonwxl123@gmail.com Liang Lin∗ Sun Yat-Sen University Guangzhou, P.R. China 510006 linliang@ieee.org Abstract This paper studies a novel discriminative part-... | 2012 | 50 |
4,766 | Augmented-SVM: Automatic space partitioning for combining multiple non-linear dynamics Ashwini Shukla ashwini.shukla@epfl.ch Aude Billard aude.billard@epfl.ch Learning Algorithms and Systems Laboratory (LASA) ´Ecole Polytechnique F´ed´erale de Lausanne (EPFL) Lausanne, Switzerland - 1015 Abstract No... | 2012 | 51 |
4,767 | 3D Social Saliency from Head-mounted Cameras Hyun Soo Park Carnegie Mellon University hyunsoop@cs.cmu.edu Eakta Jain Texas Instruments e-jain@ti.com Yaser Sheikh Carnegie Mellon University yaser@cs.cmu.edu Abstract A gaze concurrence is a point in 3D where the gaze directions of two or more peop... | 2012 | 52 |
4,768 | Coupling Nonparametric Mixtures via Latent Dirichlet Processes Dahua Lin MIT CSAIL dhlin@mit.edu John Fisher MIT CSAIL fisher@csail.mit.edu Abstract Mixture distributions are often used to model complex data. In this paper, we develop a new method that jointly estimates mixture models over multiple da... | 2012 | 53 |
4,769 | Multiclass Learning with Simplex Coding Youssef Mroueh♯,‡, Tomaso Poggio♯,‡, Lorenzo Rosasco♯,‡ Jean-Jacques E. Slotine† ♯- CBCL, McGovern Institute, MIT;† -LCSL, MIT- IIT; † - ME, BCS, MIT ymroueh, lrosasco,jjs@mit.edu tp@ai.mit.edu Abstract In this paper we discuss a novel framework for multiclass learning,... | 2012 | 54 |
4,770 | Clustering Sparse Graphs Yudong Chen Department of Electrical and Computer Engineering The University of Texas at Austin Austin, TX 78712 ydchen@utexas.edu Sujay Sanghavi Department of Electrical and Computer Engineering The University of Texas at Austin Austin, TX 78712 sanghavi@mail.utexas.edu H... | 2012 | 55 |
4,771 | On-line Reinforcement Learning Using Incremental Kernel-Based Stochastic Factorization Andr´e M. S. Barreto School of Computer Science McGill University Montreal, Canada amsb@cs.mcgill.ca Doina Precup School of Computer Science McGill University Montreal, Canada dprecup@cs.mcgill.ca Joelle Pinea... | 2012 | 56 |
4,772 | Accelerated Training for Matrix-norm Regularization: A Boosting Approach Xinhua Zhang∗, Yaoliang Yu and Dale Schuurmans Department of Computing Science, University of Alberta, Edmonton AB T6G 2E8, Canada {xinhua2,yaoliang,dale}@cs.ualberta.ca Abstract Sparse learning models typically combine a smooth loss w... | 2012 | 57 |
4,773 | Supervised Learning with Similarity Functions Purushottam Kar Indian Institute of Technology Kanpur, INDIA purushot@cse.iitk.ac.in Prateek Jain Microsoft Research Lab Bangalore, INDIA prajain@microsoft.com Abstract We address the problem of general supervised learning when data can only be accessed ... | 2012 | 58 |
4,774 | A Simple and Practical Algorithm for Differentially Private Data Release Moritz Hardt IBM Almaden Research San Jose, CA mhardt@us.ibm.com Katrina Ligett⇤ Caltech katrina@caltech.edu Frank McSherry Microsoft Research SVC mcsherry@microsoft.com Abstract We present a new algorithm for differentia... | 2012 | 59 |
4,775 | Practical Bayesian Optimization of Machine Learning Algorithms Jasper Snoek Department of Computer Science University of Toronto jasper@cs.toronto.edu Hugo Larochelle Department of Computer Science University of Sherbrooke hugo.larochelle@usherbrooke.edu Ryan P. Adams School of Engineering and App... | 2012 | 6 |
4,776 | Persistent Homology for Learning Densities with Bounded Support Florian T. Pokorny Carl Henrik Ek Hedvig Kjellstr¨om Danica Kragic ∗ Computer Vision and Active Perception Lab, Centre for Autonomous Systems School of Computer Science and Communication KTH Royal Institute of Technology, Stockholm, Sweden ... | 2012 | 60 |
4,777 | Proper losses for learning from partial labels Jes´us Cid-Sueiro Department of Signal Theory and Communications Universidad Carlos III de Madrid Legans-Madrid, 28911 Spain jcid@tsc.uc3m.es Abstract This paper discusses the problem of calibrating posterior class probabilities from partially labelled data... | 2012 | 61 |
4,778 | Predicting Action Content On-Line and in Real Time before Action Onset — an Intracranial Human Study Uri Maoz California Institute of Technology Pasadena, CA urim@caltech.edu Shengxuan Ye California Institute of Technology Pasadena, CA sye@caltech.edu Ian Ross Huntington Hospital Pasadena, CA ... | 2012 | 62 |
4,779 | Classification Calibration Dimension for General Multiclass Losses Harish G. Ramaswamy Shivani Agarwal Department of Computer Science and Automation Indian Institute of Science, Bangalore 560012, India {harish gurup,shivani}@csa.iisc.ernet.in Abstract We study consistency properties of surrogate loss fun... | 2012 | 63 |
4,780 | Analog readout for optical reservoir computers A. Smerieri1, F. Duport1, Y. Paquot1, B. Schrauwen2, M. Haelterman1, S. Massar3 1Service OPERA-photonique, Université Libre de Bruxelles (U.L.B.), 50 Avenue F. D. Roosevelt, CP 194/5, B-1050 Bruxelles, Belgium 2Department of Electronics and Information Systems (ELI... | 2012 | 64 |
4,781 | Perfect Dimensionality Recovery by Variational Bayesian PCA Shinichi Nakajima Nikon Corporation Tokyo, 140-8601, Japan nakajima.s@nikon.co.jp Ryota Tomioka The University of Tokyo Tokyo 113-8685, Japan tomioka@mist.i.u-tokyo.ac.jp Masashi Sugiyama Tokyo Institute of Technology Tokyo 152-8552, Ja... | 2012 | 65 |
4,782 | Compressive neural representation of sparse, high-dimensional probabilities xaq pitkow Department of Brain and Cognitive Sciences University of Rochester Rochester, NY 14607 xpitkow@bcs.rochester.edu Abstract This paper shows how sparse, high-dimensional probability distributions could be represented ... | 2012 | 66 |
4,783 | Shifting Weights: Adapting Object Detectors from Image to Video Kevin Tang1 Vignesh Ramanathan2 Li Fei-Fei1 Daphne Koller1 1Computer Science Department, Stanford University, Stanford, CA 94305 2Department of Electrical Engineering, Stanford University, Stanford, CA 94305 {kdtang,vigneshr,feifeili,koller... | 2012 | 67 |
4,784 | Minimization of Continuous Bethe Approximations: A Positive Variation Jason L. Pacheco and Erik B. Sudderth Department of Computer Science, Brown University, Providence, RI {pachecoj,sudderth}@cs.brown.edu Abstract We develop convergent minimization algorithms for Bethe variational approximations which expl... | 2012 | 68 |
4,785 | Optimal Regularized Dual Averaging Methods for Stochastic Optimization Xi Chen Machine Learning Department Carnegie Mellon University xichen@cs.cmu.edu Qihang Lin Javier Pe˜na Tepper School of Business Carnegie Mellon University {qihangl,jfp}@andrew.cmu.edu Abstract This paper considers a wide s... | 2012 | 69 |
4,786 | Optimal Neural Tuning Curves for Arbitrary Stimulus Distributions: Discrimax, Infomax and Minimum Lp Loss Zhuo Wang Department of Mathematics University of Pennsylvania Philadelphia, PA 19104 wangzhuo@sas.upenn.edu Alan A. Stocker Department of Psychology University of Pennsylvania Philadelphia, P... | 2012 | 7 |
4,787 | Gradient Weights help Nonparametric Regressors Samory Kpotufe∗ Max Planck Institute for Intelligent Systems samory@tuebingen.mpg.de Abdeslam Boularias Max Planck Institute for Intelligent Systems boularias@tuebingen.mpg.de Abstract In regression problems over Rd, the unknown function f often varies more... | 2012 | 70 |
4,788 | Regularized Off-Policy TD-Learning Bo Liu, Sridhar Mahadevan Computer Science Department University of Massachusetts Amherst, MA 01003 {boliu, mahadeva}@cs.umass.edu Ji Liu Computer Science Department University of Wisconsin Madison, WI 53706 ji-liu@cs.wisc.edu Abstract We present a novel l1 reg... | 2012 | 71 |
4,789 | Locating Changes in Highly Dependent Data with Unknown Number of Change Points Azadeh Khaleghi SequeL-INRIA/LIFL-CNRS, Universit´e de Lille, France azadeh.khaleghi@inria.fr Daniil Ryabko SequeL-INRIA/LIFL-CNRS, daniil@ryabko.net Abstract The problem of multiple change point estimation is considered ... | 2012 | 72 |
4,790 | Controlled Recognition Bounds for Visual Learning and Exploration Vasiliy Karasev1 Alessandro Chiuso2 Stefano Soatto1 1University of California, Los Angeles 2University of Padova Abstract We describe the tradeoff between the performance in a visual recognition problem and the control authority that th... | 2012 | 73 |
4,791 | Multi-Stage Multi-Task Feature Learning∗ †Pinghua Gong, ‡Jieping Ye, †Changshui Zhang †State Key Laboratory on Intelligent Technology and Systems Tsinghua National Laboratory for Information Science and Technology (TNList) Department of Automation, Tsinghua University, Beijing 100084, China ‡Computer Scie... | 2012 | 74 |
4,792 | Fast Resampling Weighted v-Statistics Chunxiao Zhou Mark O. Hatfield Clinical Research Center National Institutes of Health Bethesda, MD 20892 chunxiao.zhou@nih.gov Jiseong Park Dept of Math George Mason Univ Fairfax, VA 22030 jiseongp@gmail.com Yun Fu Dept of ECE Northeastern Univ Boston, MA... | 2012 | 75 |
4,793 | Rational inference of relative preferences Nisheeth Srivastava Dept of Computer Science University of Minnesota Paul R Schrater Dept of Psychology University of Minnesota Abstract Statistical decision theory axiomatically assumes that the relative desirability of different options that humans perceive... | 2012 | 76 |
4,794 | Latent Graphical Model Selection: Efficient Methods for Locally Tree-like Graphs Animashree Anandkumar UC Irvine a.anandkumar@uci.edu Ragupathyraj Valluvan UC Irvine rvalluva@uci.edu Abstract Graphical model selection refers to the problem of estimating the unknown graph structure given observations ... | 2012 | 77 |
4,795 | On the connections between saliency and tracking Vijay Mahadevan Yahoo! Labs Bangalore, India vmahadev@yahoo-inc.com Nuno Vasconcelos Statistical Visual Computing Laboratory UC San Diego, La Jolla, CA 92092 nuno@ece.ucsd.edu Abstract A model connecting visual tracking and saliency has recently been ... | 2012 | 78 |
4,796 | Symbolic Dynamic Programming for Continuous State and Observation POMDPs Zahra Zamani ANU & NICTA Canberra, Australia zahra.zamani@anu.edu.au Scott Sanner NICTA & ANU Canberra, Australia scott.sanner@nicta.com.au Pascal Poupart U. of Waterloo Waterloo, Canada ppoupart@uwaterloo.ca Kristian K... | 2012 | 79 |
4,797 | Probabilistic Event Cascades for Alzheimer’s disease Jonathan Huang Stanford University jhuang11@stanford.edu Daniel Alexander University College London d.alexander@cs.ucl.ac.uk Abstract Accurate and detailed models of neurodegenerative disease progression are crucially important for reliable early di... | 2012 | 8 |
4,798 | Imitation Learning by Coaching He He Hal Daumé III Department of Computer Science University of Maryland College Park, MD 20740 {hhe,hal}@cs.umd.edu Jason Eisner Department of Computer Science Johns Hopkins University Baltimore, MD 21218 jason@cs.jhu.edu Abstract Imitation Learning has been sh... | 2012 | 80 |
4,799 | Learning about Canonical Views from Internet Image Collections Elad Mezuman Interdisciplinary Center for Neural Computation Edmond & Lily Safra Center for Brain Sciences Hebrew University of Jerusalem http://www.cs.huji.ac.il/~mezuman Yair Weiss School of Computer Science and Engineering Edmond & Lily... | 2012 | 81 |
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