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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4,500 | Entropy Estimations Using Correlated Symmetric Stable Random Projections Ping Li Department of Statistical Science Cornell University Ithaca, NY 14853 pingli@cornell.edu Cun-Hui Zhang Department of Statistics and Biostatistics Rutgers University New Brunswick, NJ 08901 czhang@stat.rutgers.edu Ab... | 2012 | 143 |
4,501 | Coding efficiency and detectability of rate fluctuations with non-Poisson neuronal firing Shinsuke Koyama∗ Department of Statistical Modeling The Institute of Statistical Mathematics 10-3 Midori-cho, Tachikawa, Tokyo 190-8562, Japan skoyama@ism.ac.jp Abstract Statistical features of neuronal spike trains a... | 2012 | 144 |
4,502 | Nystr¨om Method vs Random Fourier Features: A Theoretical and Empirical Comparison Tianbao Yang†, Yu-Feng Li‡, Mehrdad Mahdavi♮, Rong Jin♮, Zhi-Hua Zhou‡ †Machine Learning Lab, GE Global Research, San Ramon, CA 94583 ♮Michigan State University, East Lansing, MI 48824 ‡National Key Laboratory for Novel Softwar... | 2012 | 145 |
4,503 | Spiking and saturating dendrites differentially expand single neuron computation capacity. Romain Caz´e INSERM U960, Paris Diderot, Paris 7, ENS 29 rue d’Ulm, 75005 Paris romain.caze@ens.fr Mark Humphries INSERM U960; University of Manchester 29 rue d’Ulm, 75005 Paris; UK mark.humphries@manchester.ac.... | 2012 | 146 |
4,504 | Active Learning of Model Evidence Using Bayesian Quadrature Michael A. Osborne University of Oxford mosb@robots.ox.ac.uk David Duvenaud University of Cambridge dkd23@cam.ac.uk Roman Garnett Carnegie Mellon University rgarnett@cs.cmu.edu Carl E. Rasmussen University of Cambridge cer54@cam.ac.uk... | 2012 | 147 |
4,505 | Diffusion Decision Making for Adaptive k-Nearest Neighbor Classification Yung-Kyun Noh, Frank Chongwoo Park Schl. of Mechanical and Aerospace Engineering Seoul National University Seoul 151-744, Korea {nohyung,fcp}@snu.ac.kr Daniel D. Lee Dept. of Electrical and Systems Engineering University of Penn... | 2012 | 148 |
4,506 | Bayesian Hierarchical Reinforcement Learning Feng Cao Department of EECS Case Western Reserve University Cleveland, OH 44106 fxc100@case.edu Soumya Ray Department of EECS Case Western Reserve University Cleveland, OH 44106 sray@case.edu Abstract We describe an approach to incorporating Bayesian ... | 2012 | 149 |
4,507 | Provable ICA with Unknown Gaussian Noise, with Implications for Gaussian Mixtures and Autoencoders Sanjeev Arora∗ Rong Ge∗ Ankur Moitra † Sushant Sachdeva∗ Abstract We present a new algorithm for Independent Component Analysis (ICA) which has provable performance guarantees. In particular, suppose we ar... | 2012 | 15 |
4,508 | Compressive Sensing MRI with Wavelet Tree Sparsity Chen Chen and Junzhou Huang Department of Computer Science and Engineering University of Texas at Arlington cchen@mavs.uta.edu jzhuang@uta.edu Abstract In Compressive Sensing Magnetic Resonance Imaging (CS-MRI), one can reconstruct a MR image with good qu... | 2012 | 150 |
4,509 | Mixability in Statistical Learning Tim van Erven Universit´e Paris-Sud, France tim@timvanerven.nl Peter D. Gr¨unwald CWI and Leiden University, the Netherlands pdg@cwi.nl Mark D. Reid ANU and NICTA, Australia Mark.Reid@anu.edu.au Robert C. Williamson ANU and NICTA, Australia Bob.Williamson@anu.e... | 2012 | 151 |
4,510 | Symmetric Correspondence Topic Models for Multilingual Text Analysis Kosuke Fukumasu† Koji Eguchi† Eric P. Xing‡ †Graduate School of System Informatics, Kobe University, Kobe 657-8501, Japan ‡School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA fukumasu@cs25.scitec.kobe-u.ac.j... | 2012 | 152 |
4,511 | Learning Halfspaces with the Zero-One Loss: Time-Accuracy Tradeoffs Aharon Birnbaum and Shai Shalev-Shwartz School of Computer Science and Engineering The Hebrew University Jerusalem, Israel Abstract Given α, ϵ, we study the time complexity required to improperly learn a halfspace with misclassification er... | 2012 | 153 |
4,512 | Learning High-Density Regions for a Generalized Kolmogorov-Smirnov Test in High-Dimensional Data Assaf Glazer Department of Computer Science Technion – Israel Institute of Technology Haifa 32000, Israel assafgr@cs.technion.ac.il Michael Lindenbaoum Department of Computer Science Technion – Israel Inst... | 2012 | 154 |
4,513 | Factorial LDA: Sparse Multi-Dimensional Text Models Michael J. Paul and Mark Dredze Human Language Technology Center of Excellence (HLTCOE) Center for Language and Speech Processing (CLSP) Johns Hopkins University Baltimore, MD 21218 {mpaul,mdredze}@cs.jhu.edu Abstract Latent variable models can be en... | 2012 | 155 |
4,514 | Augment-and-Conquer Negative Binomial Processes Mingyuan Zhou Dept. of Electrical and Computer Engineering Duke University, Durham, NC 27708 mz1@ee.duke.edu Lawrence Carin Dept. of Electrical and Computer Engineering Duke University, Durham, NC 27708 lcarin@ee.duke.edu Abstract By developing data au... | 2012 | 156 |
4,515 | Large Scale Distributed Deep Networks Jeffrey Dean, Greg S. Corrado, Rajat Monga, Kai Chen, Matthieu Devin, Quoc V. Le, Mark Z. Mao, Marc’Aurelio Ranzato, Andrew Senior, Paul Tucker, Ke Yang, Andrew Y. Ng {jeff, gcorrado}@google.com Google Inc., Mountain View, CA Abstract Recent work in unsupervised featu... | 2012 | 157 |
4,516 | Structure estimation for discrete graphical models: Generalized covariance matrices and their inverses Po-Ling Loh Department of Statistics University of California, Berkeley Berkeley, CA 94720 ploh@berkeley.edu Martin J. Wainwright Departments of Statistics and EECS University of California, Berkeley... | 2012 | 158 |
4,517 | Joint Modeling of a Matrix with Associated Text via Latent Binary Features XianXing Zhang Duke University xianxing.zhang@duke.edu Lawrence Carin Duke University lcarin@duke.edu Abstract A new methodology is developed for joint analysis of a matrix and accompanying documents, with the documents assoc... | 2012 | 159 |
4,518 | Learning Image Descriptors with the Boosting-Trick Tomasz Trzcinski, Mario Christoudias, Vincent Lepetit and Pascal Fua CVLab, EPFL, Lausanne, Switzerland firstname.lastname@epfl.ch Abstract In this paper we apply boosting to learn complex non-linear local visual feature representations, drawing inspiration... | 2012 | 16 |
4,519 | Near-Optimal MAP Inference for Determinantal Point Processes Jennifer Gillenwater Alex Kulesza Ben Taskar Computer and Information Science University of Pennsylvania {jengi,kulesza,taskar}@cis.upenn.edu Abstract Determinantal point processes (DPPs) have recently been proposed as computationally efficie... | 2012 | 160 |
4,520 | Image Denoising and Inpainting with Deep Neural Networks Junyuan Xie, Linli Xu, Enhong Chen1 School of Computer Science and Technology University of Science and Technology of China eric.jy.xie@gmail.com, linlixu@ustc.edu.cn, cheneh@ustc.edu.cn Abstract We present a novel approach to low-level vision probl... | 2012 | 161 |
4,521 | Strategic Impatience in Go/NoGo versus Forced-Choice Decision-Making Pradeep Shenoy Cognitive Science Department University of California, San Diego La Jolla, CA, 92093 pshenoy@ucsd.edu Angela J. Yu Cognitive Science Department University of California, San Diego La Jolla, CA, 92093 ajyu@ucsd.edu ... | 2012 | 162 |
4,522 | Cost-Sensitive Exploration in Bayesian Reinforcement Learning Dongho Kim Department of Engineering University of Cambridge, UK dk449@cam.ac.uk Kee-Eung Kim Dept of Computer Science KAIST, Korea kekim@cs.kaist.ac.kr Pascal Poupart School of Computer Science University of Waterloo, Canada ppoupa... | 2012 | 163 |
4,523 | MCMC for continuous-time discrete-state systems Vinayak Rao Gatsby Computational Neuroscience Unit University College London vrao@gatsby.ucl.ac.uk Yee Whye Teh Gatsby Computational Neuroscience Unit University College London ywteh@gatsby.ucl.ac.uk Abstract We propose a simple and novel framework for... | 2012 | 164 |
4,524 | Spectral Learning of General Weighted Automata via Constrained Matrix Completion Borja Balle Universitat Polit`ecnica de Catalunya bballe@lsi.upc.edu Mehryar Mohri Courant Institute and Google Research mohri@cims.nyu.edu Abstract Many tasks in text and speech processing and computational biology requi... | 2012 | 165 |
4,525 | Learning with Recursive Perceptual Representations Oriol Vinyals UC Berkeley Berkeley, CA Yangqing Jia UC Berkeley Berkeley, CA Li Deng Microsoft Research Redmond, WA Trevor Darrell UC Berkeley Berkeley, CA Abstract Linear Support Vector Machines (SVMs) have become very popular in vision as ... | 2012 | 166 |
4,526 | Scaled Gradients on Grassmann Manifolds for Matrix Completion Thanh T. Ngo and Yousef Saad Department of Computer Science and Engineering University of Minnesota, Twin Cities Minneapolis, MN 55455 thango@cs.umn.edu, saad@cs.umn.edu Abstract This paper describes gradient methods based on a scaled metric ... | 2012 | 167 |
4,527 | Link Prediction in Graphs with Autoregressive Features Emile Richard CMLA UMR CNRS 8536, ENS Cachan, France Stéphane Gaïffas CMAP - Ecole Polytechnique & LSTA - Université Paris 6 Nicolas Vayatis CMLA UMR CNRS 8536, ENS Cachan, France Abstract In the paper, we consider the problem of link predic... | 2012 | 168 |
4,528 | A Generative Model for Parts-based Object Segmentation S. M. Ali Eslami School of Informatics University of Edinburgh s.m.eslami@sms.ed.ac.uk Christopher K. I. Williams School of Informatics University of Edinburgh ckiw@inf.ed.ac.uk Abstract The Shape Boltzmann Machine (SBM) [1] has recently been ... | 2012 | 169 |
4,529 | A latent factor model for highly multi-relational data Rodolphe Jenatton CMAP, UMR CNRS 7641, Ecole Polytechnique, Palaiseau, France jenatton@cmap.polytechnique.fr Nicolas Le Roux INRIA - SIERRA Project Team, Ecole Normale Sup´erieure, Paris, France nicolas@le-roux.name Antoine Bordes Heudiasyc, UMR... | 2012 | 17 |
4,530 | Dimensionality Dependent PAC-Bayes Margin Bound Chi Jin Key Laboratory of Machine Perception, MOE School of Physics Peking University chijin06@gmail.com Liwei Wang Key Laboratory of Machine Perception, MOE School of EECS Peking University wanglw@cis.pku.edu.cn Abstract Margin is one of the most ... | 2012 | 170 |
4,531 | MAP Inference in Chains using Column Generation David Belanger∗, Alexandre Passos∗, Sebastian Riedel†, Andrew McCallum Department of Computer Science, University of Massachusetts, Amherst † Department of Computer Science, University College London {belanger,apassos,mccallum}@cs.umass.edu, s.riedel@cs.ucl.ac.uk ... | 2012 | 171 |
4,532 | Cocktail Party Processing via Structured Prediction Yuxuan Wang1, DeLiang Wang1,2 1Department of Computer Science and Engineering 2Center for Cognitive Science The Ohio State University Columbus, OH 43210 {wangyuxu,dwang}@cse.ohio-state.edu Abstract While human listeners excel at selectively attending t... | 2012 | 172 |
4,533 | Fused sparsity and robust estimation for linear models with unknown variance Yin Chen University Paris Est, LIGM 77455 Marne-la-Valle, FRANCE yin.chen@eleves.enpc.fr Arnak S. Dalalyan ENSAE-CREST-GENES 92245 MALAKOFF Cedex, FRANCE arnak.dalalyan@ensae.fr Abstract In this paper, we develop a novel ... | 2012 | 173 |
4,534 | On the Sample Complexity of Robust PCA Matthew Coudron Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge, MA 02139 mcoudron@mit.edu Gilad Lerman School of Mathematics University of Minnesota Minneapolis, MN 55455 lerman@umn.edu Abstract We ... | 2012 | 174 |
4,535 | Learning to Discover Social Circles in Ego Networks Julian McAuley Stanford, USA jmcauley@cs.stanford.edu Jure Leskovec Stanford, USA jure@cs.stanford.edu Abstract Our personal social networks are big and cluttered, and currently there is no good way to organize them. Social networking sites allow use... | 2012 | 175 |
4,536 | Exact and Stable Recovery of Sequences of Signals with Sparse Increments via Differential ℓ1-Minimization Demba Ba1,2, Behtash Babadi1,2, Patrick Purdon2 and Emery Brown1,2 1MIT Department of BCS, Cambridge, MA 02139 2MGH Department of Anesthesia, Critical Care and Pain Medicine 55 Fruit st, GRJ 4, Boston, ... | 2012 | 176 |
4,537 | Tight Bounds on Profile Redundancy and Distinguishability Jayadev Acharya ECE, UCSD jacharya@ucsd.edu Hirakendu Das Yahoo! hdas@yahoo-inc.com Alon Orlitsky ECE & CSE, UCSD alon@ucsd.edu Abstract The minimax KL-divergence of any distribution from all distributions in a collection P has several pra... | 2012 | 177 |
4,538 | On Triangular versus Edge Representations — Towards Scalable Modeling of Networks Qirong Ho School of Computer Science Carnegie Mellon University Pittsburgh, PA 15213 qho@cs.cmu.edu Junming Yin School of Computer Science Carnegie Mellon University Pittsburgh, PA 15213 junmingy@cs.cmu.edu Eric P.... | 2012 | 178 |
4,539 | A Better Way to Pretrain Deep Boltzmann Machines Ruslan Salakhutdinov Department of Statistics and Computer Science University of Toronto rsalakhu@cs.toronto.edu Geoffrey Hinton Department of Computer Science University of Toronto hinton@cs.toronto.edu Abstract We describe how the pretraining algori... | 2012 | 179 |
4,540 | Bayesian estimation of discrete entropy with mixtures of stick-breaking priors Evan Archer⇤124, Il Memming Park⇤234, & Jonathan W. Pillow234 1. Institute for Computational and Engineering Sciences 2. Center for Perceptual Systems, 3. Dept. of Psychology, 4. Division of Statistics & Scientific Computation The... | 2012 | 18 |
4,541 | Semi-supervised Eigenvectors for Locally-biased Learning Toke Jansen Hansen Section for Cognitive Systems DTU Informatics Technical University of Denmark tjha@imm.dtu.dk Michael W. Mahoney Department of Mathematics Stanford University Stanford, CA 94305 mmahoney@cs.stanford.edu Abstract In man... | 2012 | 180 |
4,542 | The variational hierarchical EM algorithm for clustering hidden Markov models Emanuele Coviello ECE Dept., UC San Diego ecoviell@ucsd.edu Antoni B. Chan CS Dept., CityU of Hong Kong abchan@cityu.edu.hk Gert R.G. Lanckriet ECE Dept., UC San Diego gert@ece.ucsd.edu Abstract In this paper, we deriv... | 2012 | 181 |
4,543 | Scalable nonconvex inexact proximal splitting Suvrit Sra Max Planck Institute for Intelligent Systems 72076 T¨ubigen, Germany suvrit@tuebingen.mpg.de Abstract We study a class of large-scale, nonsmooth, and nonconvex optimization problems. In particular, we focus on nonconvex problems with composite objecti... | 2012 | 182 |
4,544 | Bayesian nonparametric models for ranked data Franc¸ois Caron INRIA IMB - University of Bordeaux Talence, France Francois.Caron@inria.fr Yee Whye Teh Department of Statistics University of Oxford Oxford, United Kingdom y.w.teh@stats.ox.ac.uk Abstract We develop a Bayesian nonparametric extension... | 2012 | 183 |
4,545 | GenDeR: A Generic Diversified Ranking Algorithm Jingrui He IBM T.J. Watson Research Yorktown Heights, NY 10598 jingruhe@us.ibm.com Hanghang Tong IBM T.J. Watson Research Yorktown Heights, NY 10598 htong@us.ibm.com Qiaozhu Mei University of Michigan Ann Arbor, MI 48109 qmei@umich.edu Boleslaw K.... | 2012 | 184 |
4,546 | Accuracy at the Top Stephen Boyd Stanford University Packard 264 Stanford, CA 94305 boyd@stanford.edu Corinna Cortes Google Research 76 Ninth Avenue New York, NY 10011 corinna@google.com Mehryar Mohri Courant Institute and Google 251 Mercer Street New York, NY 10012 mohri@cims.nyu.edu An... | 2012 | 185 |
4,547 | Approximating Equilibria in Sequential Auctions with Incomplete Information and Multi-Unit Demand Amy Greenwald and Eric Sodomka Department of Computer Science Brown University Providence, RI 02912 {amy,sodomka}@cs.brown.edu Jiacui Li Department of Applied Math/Economics Brown University Providence,... | 2012 | 186 |
4,548 | Multiresolution Gaussian Processes Emily B. Fox Dept of Statistics, University of Washington ebfox@stat.washington.edu David B. Dunson Dept of Statistical Science, Duke University dunson@stat.duke.edu Abstract We propose a multiresolution Gaussian process to capture long-range, nonMarkovian dependencies... | 2012 | 187 |
4,549 | Emergence of Object-Selective Features in Unsupervised Feature Learning Adam Coates, Andrej Karpathy, Andrew Y. Ng Computer Science Department Stanford University Stanford, CA 94305 {acoates,karpathy,ang}@cs.stanford.edu Abstract Recent work in unsupervised feature learning has focused on the goal of di... | 2012 | 188 |
4,550 | Truly Nonparametric Online Variational Inference for Hierarchical Dirichlet Processes Michael Bryant and Erik B. Sudderth Department of Computer Science, Brown University, Providence, RI mbryantj@gmail.com, sudderth@cs.brown.edu Abstract Variational methods provide a computationally scalable alternative to ... | 2012 | 189 |
4,551 | Timely Object Recognition Sergey Karayev UC Berkeley Tobias Baumgartner RWTH Aachen University Mario Fritz MPI for Informatics Trevor Darrell UC Berkeley Abstract In a large visual multi-class detection framework, the timeliness of results can be crucial. Our method for timely multi-class detectio... | 2012 | 19 |
4,552 | 3D Object Detection and Viewpoint Estimation with a Deformable 3D Cuboid Model Sanja Fidler TTI Chicago fidler@ttic.edu Sven Dickinson University of Toronto sven@cs.toronto.edu Raquel Urtasun TTI Chicago rurtasun@ttic.edu Abstract This paper addresses the problem of category-level 3D object dete... | 2012 | 190 |
4,553 | Risk–Aversion in Multi–armed Bandits Amir Sani Alessandro Lazaric Rémi Munos INRIA Lille - Nord Europe, Team SequeL {amir.sani,alessandro.lazaric,remi.munos}@inria.fr Abstract Stochastic multi–armed bandits solve the Exploration–Exploitation dilemma and ultimately maximize the expected reward. Nonethele... | 2012 | 191 |
4,554 | Approximate Message Passing with Consistent Parameter Estimation and Applications to Sparse Learning Ulugbek S. Kamilov EPFL ulugbek.kamilov@epfl.ch Sundeep Rangan Polytechnic Institute of New York University srangan@poly.edu Alyson K. Fletcher University of California, Santa Cruz afletcher@soe.uc... | 2012 | 192 |
4,555 | Gradient-based kernel method for feature extraction and variable selection Kenji Fukumizu The Institute of Statistical Mathematics 10-3 Midori-cho, Tachikawa, Tokyo 190-8562 Japan fukumizu@ism.ac.jp Chenlei Leng National University of Singapore 6 Science Drive 2, Singapore, 117546 stalc@nus.edu.sg A... | 2012 | 193 |
4,556 | Scalable imputation of genetic data with a discrete fragmentation-coagulation process Lloyd T. Elliott Gatsby Computational Neuroscience Unit University College London 17 Queen Square London WC1N 3AR, U.K. elliott@gatsby.ucl.ac.uk Yee Whye Teh Department of Statistics University of Oxford 1 South ... | 2012 | 194 |
4,557 | Non-parametric Approximate Dynamic Programming via the Kernel Method Nikhil Bhat Graduate School of Business Columbia University New York, NY 10027 nbhat15@gsb.columbai.edu Vivek F. Farias Sloan School of Management Massachusetts Institute of Technology Cambridge, MA 02142 vivekf@mit.edu Ciamac ... | 2012 | 195 |
4,558 | Probabilistic n-Choose-k Models for Classification and Ranking Kevin Swersky Daniel Tarlow Dept. of Computer Science University of Toronto [kswersky,dtarlow]@cs.toronto.edu Ryan P. Adams School of Eng. and Appl. Sciences Harvard University rpa@seas.harvard.edu Richard S. Zemel Dept. of Computer S... | 2012 | 196 |
4,559 | Delay Compensation with Dynamical Synapses C. C. Alan Fung, K. Y. Michael Wong Hong Kong University of Science and Technology, Hong Kong, China alanfung@ust.hk, phkywong@ust.hk Si Wu State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China wusi@bnu.ed... | 2012 | 197 |
4,560 | Visual Recognition using Embedded Feature Selection for Curvature Self-Similarity Angela Eigenstetter HCI & IWR, University of Heidelberg aeigenst@iwr.uni-heidelberg.de Bj¨orn Ommer HCI & IWR, University of Heidelberg ommer@uni-heidelberg.de Abstract Category-level object detection has a crucial need ... | 2012 | 198 |
4,561 | High-Order Multi-Task Feature Learning to Identify Longitudinal Phenotypic Markers for Alzheimer’s Disease Progression Prediction Hua Wang, Feiping Nie, Heng Huang, Department of Computer Science and Engineering, University of Texas at Arlington, Arlington, TX 76019 {huawangcs, feipingnie}@gmail.com, heng@u... | 2012 | 199 |
4,562 | Clustering Aggregation as Maximum-Weight Independent Set Nan Li Longin Jan Latecki Department of Computer and Information Sciences Temple University, Philadelphia, USA {nan.li,latecki}@temple.edu Abstract We formulate clustering aggregation as a special instance of Maximum-Weight Independent Set (MWIS... | 2012 | 2 |
4,563 | Efficient high-dimensional maximum entropy modeling via symmetric partition functions Paul Vernaza The Robotics Institute Carnegie Mellon University Pittsburgh, PA 15213 pvernaza@cmu.edu J. Andrew Bagnell The Robotics Institute Carnegie Mellon University Pittsburgh, PA 15213 dbagnell@ri.cmu.edu A... | 2012 | 20 |
4,564 | Multiresolution analysis on the symmetric group Risi Kondor and Walter Dempsey Department of Statistics and Department of Computer Science The University of Chicago {risi,wdempsey}@uchicago.edu Abstract There is no generally accepted way to define wavelets on permutations. We address this issue by introducin... | 2012 | 200 |
4,565 | Learned Prioritization for Trading Off Accuracy and Speed∗ Jiarong Jiang∗ Adam Teichert† Hal Daum´e III∗ Jason Eisner† ∗Department of Computer Science University of Maryland College Park, MD 20742 {jiarong,hal}@umiacs.umd.edu †Department of Computer Science Johns Hopkins University Baltimore, MD... | 2012 | 201 |
4,566 | Learning as MAP Inference in Discrete Graphical Models Xianghang Liu NICTA/UNSW Sydney, Australia xianghang.liu@nicta.com.au James Petterson NICTA/ANU Canberra, Australia james.petterson@nicta.com.au Tiberio S. Caetano NICTA/ANU/University of Sydney Canberra and Sydney, Australia tiberio.caeta... | 2012 | 202 |
4,567 | Hierarchical Optimistic Region Selection driven by Curiosity Odalric-Ambrym Maillard Lehrstuhl f¨ur Informationstechnologie Montanuniversit¨at Leoben Leoben, A-8700, Austria odalricambrym.maillard@gmail.com Abstract This paper aims to take a step forwards making the term “intrinsic motivation” from re... | 2012 | 203 |
4,568 | Trajectory-Based Short-Sighted Probabilistic Planning Felipe W. Trevizan Machine Learning Department Manuela M. Veloso Computer Science Department Carnegie Mellon University - Pittsburgh, PA {fwt,mmv}@cs.cmu.edu Abstract Probabilistic planning captures the uncertainty of plan execution by probabilisti... | 2012 | 204 |
4,569 | Best Arm Identification: A Unified Approach to Fixed Budget and Fixed Confidence Victor Gabillon Mohammad Ghavamzadeh Alessandro Lazaric INRIA Lille - Nord Europe, Team SequeL Victor Gabillon, Mohammad Ghavamzadeh & Alessandro Lazaric Abstract We study the problem of identifying the best arm(s) in the stoc... | 2012 | 205 |
4,570 | On the Use of Non-Stationary Policies for Stationary Infinite-Horizon Markov Decision Processes Bruno Scherrer Inria, Villers-l`es-Nancy, F-54600, France bruno.scherrer@inria.fr Boris Lesner Inria, Villers-l`es-Nancy, F-54600, France boris.lesner@inria.fr Abstract We consider infinite-horizon stationary... | 2012 | 206 |
4,571 | Deep Spatio-Temporal Architectures and Learning for Protein Structure Prediction Pietro Di Lena, Ken Nagata, Pierre Baldi Department of Computer Science, Institute for Genomics and Bioinformatics University of California, Irvine {pdilena,knagata,pfbaldi}@[ics.]uci.edu Abstract Residue-residue contact pred... | 2012 | 207 |
4,572 | Isotropic Hashing Weihao Kong, Wu-Jun Li Shanghai Key Laboratory of Scalable Computing and Systems Department of Computer Science and Engineering, Shanghai Jiao Tong University, China {kongweihao,liwujun}@cs.sjtu.edu.cn Abstract Most existing hashing methods adopt some projection functions to project the or... | 2012 | 208 |
4,573 | Repulsive Mixtures Francesca Petralia Department of Statistical Science Duke University fp12@duke.edu Vinayak Rao Gatsby Computational Neuroscience Unit University College London vrao@gatsby.ucl.ac.uk David B. Dunson Department of Statistical Science Duke University dunson@stat.duke.edu Abstra... | 2012 | 209 |
4,574 | Topic-Partitioned Multinetwork Embeddings Peter Krafft∗ CSAIL MIT pkrafft@mit.edu Juston Moore†, Bruce Desmarais‡, Hanna Wallach† †Department of Computer Science, ‡Department of Political Science University of Massachusetts Amherst †{jmoore, wallach}@cs.umass.edu ‡desmarais@polsci.umass.edu Abstract... | 2012 | 21 |
4,575 | Forward-Backward Activation Algorithm for Hierarchical Hidden Markov Models Kei Wakabayashi Faculty of Library, Information and Media Science University of Tsukuba, Japan kwakaba@slis.tsukuba.ac.jp Takao Miura Department of Engineering Hosei University, Japan miurat@hosei.ac.jp Abstract Hierarchic... | 2012 | 210 |
4,576 | Finding Exemplars from Pairwise Dissimilarities via Simultaneous Sparse Recovery Ehsan Elhamifar EECS Department University of California, Berkeley Guillermo Sapiro ECE, CS Department Duke University Ren´e Vidal Center for Imaging Science Johns Hopkins University Abstract Given pairwise dissimil... | 2012 | 211 |
4,577 | Mirror Descent Meets Fixed Share (and feels no regret) Nicolò Cesa-Bianchi Università degli Studi di Milano nicolo.cesa-bianchi@unimi.it Pierre Gaillard Ecole Normale Supérieure∗, Paris pierre.gaillard@ens.fr Gábor Lugosi ICREA & Universitat Pompeu Fabra, Barcelona gabor.lugosi@upf.edu Gilles Stol... | 2012 | 212 |
4,578 | Semi-Supervised Domain Adaptation with Non-Parametric Copulas David Lopez-Paz MPI for Intelligent Systems dlopez@tue.mpg.de Jos´e Miguel Hern´andez-Lobato University of Cambridge jmh233@cam.ac.uk Bernhard Sch¨olkopf MPI for Intelligent Systems bs@tue.mpg.de Abstract A new framework based on the ... | 2012 | 213 |
4,579 | The Lov´asz ϑ function, SVMs and finding large dense subgraphs Vinay Jethava ∗ Computer Science & Engineering Department, Chalmers University of Technology 412 96, Goteborg, SWEDEN jethava@chalmers.se Anders Martinsson Department of Mathematics, Chalmers University of Technology 412 96, Goteborg, SWE... | 2012 | 214 |
4,580 | Slice sampling normalized kernel-weighted completely random measure mixture models Nicholas J. Foti Department of Computer Science Dartmouth College Hanover, NH 03755 nfoti@cs.dartmouth.edu Sinead A. Williamson Department of Machine Learning Carnegie Mellon University Pittsburgh, PA 15213 sinead@c... | 2012 | 215 |
4,581 | Automatic Feature Induction for Stagewise Collaborative Filtering Joonseok Leea, Mingxuan Suna, Seungyeon Kima, Guy Lebanona, b a College of Computing, Georgia Institute of Technology, Atlanta, GA 30332 b Google Research, Mountain View, CA 94043 {jlee716, msun3, seungyeon.kim}@gatech.edu, lebanon@cc.gatech.ed... | 2012 | 216 |
4,582 | A Stochastic Gradient Method with an Exponential Convergence Rate for Finite Training Sets Nicolas Le Roux SIERRA Project-Team INRIA - ENS Paris, France nicolas@le-roux.name Mark Schmidt SIERRA Project-Team INRIA - ENS Paris, France mark.schmidt@inria.fr Francis Bach SIERRA Project-Team INRI... | 2012 | 217 |
4,583 | Monte Carlo Methods for Maximum Margin Supervised Topic Models Qixia Jiang†‡, Jun Zhu†‡, Maosong Sun†, and Eric P. Xing∗∗ †Department of Computer Science & Technology, Tsinghua National TNList Lab, †State Key Lab of Intelligent Tech. & Sys., Tsinghua University, Beijing 100084, China ∗School of Computer Scien... | 2012 | 218 |
4,584 | Analyzing 3D Objects in Cluttered Images Mohsen Hejrati UC Irvine shejrati@ics.uci.edu Deva Ramanan UC Irvine dramanan@ics.uci.edu Abstract We present an approach to detecting and analyzing the 3D configuration of objects in real-world images with heavy occlusion and clutter. We focus on the applicatio... | 2012 | 219 |
4,585 | Recovery of Sparse Probability Measures via Convex Programming Mert Pilanci and Laurent El Ghaoui Electrical Engineering and Computer Science University of California Berkeley Berkeley, CA 94720 {mert,elghaoui}@eecs.berkeley.edu Venkat Chandrasekaran Department of Computing and Mathematical Sciences C... | 2012 | 22 |
4,586 | A mechanistic model of early sensory processing based on subtracting sparse representations Shaul Druckmann* Tao Hu* Dmitri B. Chklovskii * - Equal contribution ... | 2012 | 220 |
4,587 | Ensemble weighted kernel estimators for multivariate entropy estimation Kumar Sricharan, Alfred O. Hero III Department of EECS University of Michigan Ann Arbor, MI 48104 {kksreddy,hero}@umich.edu Abstract The problem of estimation of entropy functionals of probability densities has received much atten... | 2012 | 221 |
4,588 | Active Comparison of Prediction Models Christoph Sawade, Niels Landwehr, and Tobias Scheffer University of Potsdam Department of Computer Science August-Bebel-Strasse 89, 14482 Potsdam, Germany {sawade, landwehr, scheffer}@cs.uni-potsdam.de Abstract We address the problem of comparing the risks of two giv... | 2012 | 222 |
4,589 | Reducing statistical time-series problems to binary classification Daniil Ryabko SequeL-INRIA/LIFL-CNRS, Universit´e de Lille, France daniil@ryabko.net J´er´emie Mary SequeL-INRIA/LIFL-CNRS, Universit´e de Lille, France Jeremie.Mary@inria.fr Abstract We show how binary classification methods develop... | 2012 | 223 |
4,590 | Max-Margin Structured Output Regression for Spatio-Temporal Action Localization Du Tran and Junsong Yuan School of Electrical and Electronic Engineering Nanyang Technological University, Singapore trandu@gmail.com, jsyuan@ntu.edu.sg Abstract Structured output learning has been successfully applied to obje... | 2012 | 224 |
4,591 | Minimizing Sparse High-Order Energies by Submodular Vertex-Cover Andrew Delong University of Toronto andrew.delong@gmail.com Olga Veksler Western University olga@csd.uwo.ca Anton Osokin Moscow State University anton.osokin@gmail.com Yuri Boykov Western University yuri@csd.uwo.ca Abstract I... | 2012 | 225 |
4,592 | A new metric on the manifold of kernel matrices with application to matrix geometric means Suvrit Sra Max Planck Institute for Intelligent Systems 72076 T¨ubigen, Germany suvrit@tuebingen.mpg.de Abstract Symmetric positive definite (spd) matrices pervade numerous scientific disciplines, including machine le... | 2012 | 226 |
4,593 | Wavelet based multi-scale shape features on arbitrary surfaces for cortical thickness discrimination Won Hwa Kim†¶∗Deepti Pachauri† Charles Hatt‡ Moo K. Chung§ Sterling C. Johnson∗¶ Vikas Singh§†∗¶ †Dept. of Computer Sciences, University of Wisconsin, Madison, WI §Dept. of Biostatistics & Med. Informatics, Un... | 2012 | 227 |
4,594 | Cardinality Restricted Boltzmann Machines Kevin Swersky Daniel Tarlow Ilya Sutskever Dept. of Computer Science University of Toronto [kswersky,dtarlow,ilya]@cs.toronto.edu Ruslan Salakhutdinov†,‡ Richard S. Zemel† Dept. of Computer Science† and Statistics‡ University of Toronto [rsalakhu,zemel]@cs... | 2012 | 228 |
4,595 | Sparse Prediction with the k-Support Norm Andreas Argyriou ´Ecole Centrale Paris argyrioua@ecp.fr Rina Foygel Department of Statistics, Stanford University rinafb@stanford.edu Nathan Srebro Toyota Technological Institute at Chicago nati@ttic.edu Abstract We derive a novel norm that corresponds to ... | 2012 | 229 |
4,596 | Proximal Newton-type methods for convex optimization Jason D. Lee∗and Yuekai Sun∗ Institute for Computational and Mathematical Engineering Stanford University, Stanford, CA {jdl17,yuekai}@stanford.edu Michael A. Saunders Department of Management Science and Engineering Stanford University, Stanford, CA ... | 2012 | 23 |
4,597 | A Marginalized Particle Gaussian Process Regression Yali Wang and Brahim Chaib-draa Department of Computer Science Laval University Quebec, Quebec G1V0A6 {wang,chaib}@damas.ift.ulaval.ca Abstract We present a novel marginalized particle Gaussian process (MPGP) regression, which provides a fast, accu... | 2012 | 230 |
4,598 | Iterative Ranking from Pair-wise Comparisons Sahand Negahban Department of EECS Massachusetts Institute of Technology sahandn@mit.edu Sewoong Oh Department of IESE University of Illinois at Urbana Champaign swoh@illinois.edu Devavrat Shah Department of EECS Massachusetts Institute of Technology ... | 2012 | 231 |
4,599 | Training sparse natural image models with a fast Gibbs sampler of an extended state space Lucas Theis Werner Reichardt Centre for Integrative Neuroscience lucas@bethgelab.org Jascha Sohl-Dickstein Redwood Center for Theoretical Neuroscience jascha@berkeley.edu Matthias Bethge Werner Reichardt Cent... | 2012 | 232 |
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