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5,200 | The Infinite Mixture of Infinite Gaussian Mixtures Halid Z. Yerebakan Department of Computer and Information Science IUPUI Indianapolis, IN 46202 hzyereba@cs.iupui.edu Bartek Rajwa Bindley Bioscience Center Purdue University W. Lafayette, IN 47907 rajwa@cyto.purdue.edu Murat Dundar Department of... | 2014 | 118 |
5,201 | Partition-wise Linear Models Hidekazu Oiwa∗ Graduate School of Information Science and Technology The University of Tokyo hidekazu.oiwa@gmail.com Ryohei Fujimaki NEC Laboratories America rfujimaki@nec-labs.com Abstract Region-specific linear models are widely used in practical applications because of... | 2014 | 119 |
5,202 | Learning to Discover Efficient Mathematical Identities Wojciech Zaremba Dept. of Computer Science Courant Institute New York Unviersity Karol Kurach Google Zurich & Dept. of Computer Science University of Warsaw Rob Fergus Dept. of Computer Science Courant Institute New York Unviersity Abstra... | 2014 | 12 |
5,203 | Convex Deep Learning via Normalized Kernels ¨Ozlem Aslan Dept of Computing Science University of Alberta, Canada ozlem@cs.ualberta.ca Xinhua Zhang Machine Learning Group NICTA and ANU xizhang@nicta.com.au Dale Schuurmans Dept of Computing Science University of Alberta, Canada dale@cs.ualberta.ca... | 2014 | 120 |
5,204 | Discovering Structure in High-Dimensional Data Through Correlation Explanation Greg Ver Steeg Information Sciences Institute University of Southern California Marina del Rey, CA 90292 gregv@isi.edu Aram Galstyan Information Sciences Institute University of Southern California Marina del Rey, CA 9029... | 2014 | 121 |
5,205 | Difference of Convex Functions Programming for Reinforcement Learning Bilal Piot1,2, Matthieu Geist1, Olivier Pietquin2,3 1MaLIS research group (SUPELEC) - UMI 2958 (GeorgiaTech-CNRS), France 2LIFL (UMR 8022 CNRS/Lille 1) - SequeL team, Lille, France 3 University Lille 1 - IUF (Institut Universitaire de France... | 2014 | 122 |
5,206 | Local Linear Convergence of Forward–Backward under Partial Smoothness Jingwei Liang and Jalal M. Fadili GREYC, CNRS-ENSICAEN-Univ. Caen {Jingwei.Liang,Jalal.Fadili}@greyc.ensicaen.fr Gabriel Peyré CEREMADE, CNRS-Univ. Paris-Dauphine Gabriel.Peyre@ceremade.dauphine.fr Abstract In this paper, we conside... | 2014 | 123 |
5,207 | Improved Distributed Principal Component Analysis Maria-Florina Balcan School of Computer Science Carnegie Mellon University ninamf@cs.cmu.edu Vandana Kanchanapally School of Computer Science Georgia Institute of Technology vvandana@gatech.edu Yingyu Liang Department of Computer Science Princeton ... | 2014 | 124 |
5,208 | Reputation-based Worker Filtering in Crowdsourcing Srikanth Jagabathula1 Lakshminarayanan Subramanian2,3 Ashwin Venkataraman2,3 1Department of IOMS, NYU Stern School of Business 2Department of Computer Science, New York University 3CTED, New York University Abu Dhabi sjagabat@stern.nyu.edu {lakshmi,ashwin}@... | 2014 | 125 |
5,209 | Large Scale Canonical Correlation Analysis with Iterative Least Squares Yichao Lu University of Pennsylvania yichaolu@wharton.upenn.edu Dean P. Foster Yahoo Labs, NYC dean@foster.net Abstract Canonical Correlation Analysis (CCA) is a widely used statistical tool with both well established theory and... | 2014 | 126 |
5,210 | Analysis of Variational Bayesian Latent Dirichlet Allocation: Weaker Sparsity than MAP Shinichi Nakajima Berlin Big Data Center, TU Berlin Berlin 10587 Germany nakajima@tu-berlin.de Issei Sato University of Tokyo Tokyo 113-0033 Japan sato@r.dl.itc.u-tokyo.ac.jp Masashi Sugiyama University of Tokyo... | 2014 | 127 |
5,211 | Iterative Neural Autoregressive Distribution Estimator (NADE-k) Tapani Raiko Aalto University Li Yao Universit´e de Montr´eal KyungHyun Cho Universit´e de Montr´eal Yoshua Bengio Universit´e de Montr´eal, CIFAR Senior Fellow Abstract Training of the neural autoregressive density estimator (NADE)... | 2014 | 128 |
5,212 | Reducing the Rank of Relational Factorization Models by Including Observable Patterns Maximilian Nickel1,2 Xueyan Jiang3,4 Volker Tresp3,4 1LCSL, Poggio Lab, Massachusetts Institute of Technology, Cambridge, MA, USA 2Istituto Italiano di Tecnologia, Genova, Italy 3Ludwig Maximilian University, Munich, Ger... | 2014 | 129 |
5,213 | Global Sensitivity Analysis for MAP Inference in Graphical Models Jasper De Bock Ghent University, SYSTeMS Ghent (Belgium) jasper.debock@ugent.be Cassio P. de Campos Queen’s University Belfast (UK) c.decampos@qub.ac.uk Alessandro Antonucci IDSIA Lugano (Switzerland) alessandro@idsia.ch Abstr... | 2014 | 13 |
5,214 | Deterministic Symmetric Positive Semidefinite Matrix Completion William E. Bishop1,2, Byron M. Yu2,3,4 1Machine Learning, 2Center for the Neural Basis of Cognition, 3Biomedical Engineering, 4Electrical and Computer Engineering Carnegie Mellon University {wbishop, byronyu}@cmu.edu Abstract We consider the... | 2014 | 130 |
5,215 | Distributed Parameter Estimation in Probabilistic Graphical Models Yariv D. Mizrahi1 Misha Denil2 Nando de Freitas2,3,4 1University of British Columbia, Canada 2University of Oxford, United Kingdom 3Canadian Institute for Advanced Research 4Google DeepMind yariv@math.ubc.ca {misha.denil,nando}@cs.ox... | 2014 | 131 |
5,216 | Two-Layer Feature Reduction for Sparse-Group Lasso via Decomposition of Convex Sets Jie Wang, Jieping Ye Computer Science and Engineering Arizona State University, Tempe, AZ 85287 {jie.wang.ustc, jieping.ye}@asu.edu Abstract Sparse-Group Lasso (SGL) has been shown to be a powerful regression technique for... | 2014 | 132 |
5,217 | The Large Margin Mechanism for Differentially Private Maximization Kamalika Chaudhuri UC San Diego La Jolla, CA kamalika@cs.ucsd.edu Daniel Hsu Columbia University New York, NY djhsu@cs.columbia.edu Shuang Song UC San Diego La Jolla, CA shs037@eng.ucsd.edu Abstract A basic problem in the d... | 2014 | 133 |
5,218 | Causal Inference through a Witness Protection Program Ricardo Silva Department of Statistical Science and CSML University College London ricardo@stats.ucl.ac.uk Robin Evans Department of Statistics University of Oxford evans@stats.ox.ac.uk Abstract One of the most fundamental problems in causal in... | 2014 | 134 |
5,219 | Self-Adaptable Templates for Feature Coding Xavier Boix1,2∗ Gemma Roig1,2∗ Salomon Diether1 Luc Van Gool1 1Computer Vision Laboratory, ETH Zurich, Switzerland 2LCSL, Massachusetts Institute of Technology & Istituto Italiano di Tecnologia, Cambridge, MA {xboix,gemmar}@mit.edu {boxavier,gemmar,sdiether,va... | 2014 | 135 |
5,220 | A Framework for Testing Identifiability of Bayesian Models of Perception Luigi Acerbi1,2 Wei Ji Ma2 Sethu Vijayakumar1 1 School of Informatics, University of Edinburgh, UK 2 Center for Neural Science & Department of Psychology, New York University, USA {luigi.acerbi,weijima}@nyu.edu sethu.vijayakumar@ed.... | 2014 | 136 |
5,221 | Low Rank Approximation Lower Bounds in Row-Update Streams David P. Woodruff IBM Research Almaden dpwoodru@us.ibm.com Abstract We study low-rank approximation in the streaming model in which the rows of an n × d matrix A are presented one at a time in an arbitrary order. At the end of the stream, the str... | 2014 | 137 |
5,222 | Probabilistic ODE Solvers with Runge-Kutta Means Michael Schober MPI for Intelligent Systems Tübingen, Germany mschober@tue.mpg.de David Duvenaud Department of Engineering Cambridge University dkd23@cam.ac.uk Philipp Hennig MPI for Intelligent Systems Tübingen, Germany phennig@tue.mpg.de Abstr... | 2014 | 138 |
5,223 | Learning a Concept Hierarchy from Multi-labeled Documents Viet-An Nguyen1∗, Jordan Boyd-Graber2, Philip Resnik1,3,4, Jonathan Chang5 1Computer Science, 3Linguistics, 4UMIACS Univ. of Maryland, College Park, MD vietan@cs.umd.edu resnik@umd.edu 2Computer Science Univ. of Colorado, Boulder, CO Jordan.Boy... | 2014 | 139 |
5,224 | Recurrent Models of Visual Attention Volodymyr Mnih Nicolas Heess Alex Graves Koray Kavukcuoglu Google DeepMind {vmnih,heess,gravesa,korayk} @ google.com Abstract Applying convolutional neural networks to large images is computationally expensive because the amount of computation scales linearly with th... | 2014 | 14 |
5,225 | Dependent nonparametric trees for dynamic hierarchical clustering Avinava Dubey∗†, Qirong Ho∗‡, Sinead Williamson£, Eric P. Xing† † Machine Learning Department, Carnegie Mellon University ‡ Institute for Infocomm Research, A*STAR £ McCombs School of Business, University of Texas at Austin akdubey@cs.c... | 2014 | 140 |
5,226 | A Statistical Decision-Theoretic Framework for Social Choice Hossein Azari Soufiani∗ David C. Parkes † Lirong Xia‡ Abstract In this paper, we take a statistical decision-theoretic viewpoint on social choice, putting a focus on the decision to be made on behalf of a system of agents. In our framework, we ... | 2014 | 141 |
5,227 | Generative Adversarial Nets Ian J. Goodfellow∗, Jean Pouget-Abadie†, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair‡, Aaron Courville, Yoshua Bengio§ D´epartement d’informatique et de recherche op´erationnelle Universit´e de Montr´eal Montr´eal, QC H3C 3J7 Abstract We propose a new framework for ... | 2014 | 142 |
5,228 | Delay-Tolerant Algorithms for Asynchronous Distributed Online Learning H. Brendan McMahan Google, Inc. Seattle, WA mcmahan@google.com Matthew Streeter Duolingo, Inc.∗ Pittsburgh, PA matt@duolingo.com Abstract We analyze new online gradient descent algorithms for distributed systems with large de... | 2014 | 143 |
5,229 | Sequential Monte Carlo for Graphical Models Christian A. Naesseth Div. of Automatic Control Link¨oping University Link¨oping, Sweden chran60@isy.liu.se Fredrik Lindsten Dept. of Engineering The University of Cambridge Cambridge, UK fsml2@cam.ac.uk Thomas B. Sch¨on Dept. of Information Technology... | 2014 | 144 |
5,230 | Learning Time-Varying Coverage Functions Nan Du†, Yingyu Liang‡, Maria-Florina Balcan⋄, Le Song† †College of Computing, Georgia Institute of Technology ‡Department of Computer Science, Princeton University ⋄School of Computer Science, Carnegie Mellon University dunan@gatech.edu,yingyul@cs.princeton.edu nina... | 2014 | 145 |
5,231 | Learning Shuffle Ideals Under Restricted Distributions Dongqu Chen Department of Computer Science Yale University dongqu.chen@yale.edu Abstract The class of shuffle ideals is a fundamental sub-family of regular languages. The shuffle ideal generated by a string set U is the collection of all strings contai... | 2014 | 146 |
5,232 | Spectral Clustering of Graphs with the Bethe Hessian Alaa Saade Laboratoire de Physique Statistique, CNRS UMR 8550 ´Ecole Normale Superieure, 24 Rue Lhomond Paris 75005 Florent Krzakala∗ Sorbonne Universit´es, UPMC Univ Paris 06 Laboratoire de Physique Statistique, CNRS UMR 8550 ´Ecole Normale Superieure,... | 2014 | 147 |
5,233 | Optimal Regret Minimization in Posted-Price Auctions with Strategic Buyers Mehryar Mohri Courant Institute and Google Research 251 Mercer Street New York, NY 10012 mohri@cims.nyu.edu Andres Mu˜noz Medina Courant Institute 251 Mercer Street New York, NY 10012 munoz@cims.nyu.edu Abstract We stud... | 2014 | 148 |
5,234 | Fundamental Limits of Online and Distributed Algorithms for Statistical Learning and Estimation Ohad Shamir Weizmann Institute of Science ohad.shamir@weizmann.ac.il Abstract Many machine learning approaches are characterized by information constraints on how they interact with the training data. These inc... | 2014 | 149 |
5,235 | LSDA: Large Scale Detection through Adaptation Judy Hoffman⋄, Sergio Guadarrama⋄, Eric Tzeng⋄, Ronghang Hu∇, Jeff Donahue⋄, ⋄EECS, UC Berkeley, ∇EE, Tsinghua University {jhoffman, sguada, tzeng, jdonahue}@eecs.berkeley.edu hrh11@mails.tsinghua.edu.cn Ross Girshick⋄, Trevor Darrell⋄, Kate Saenko△ ⋄EECS, UC B... | 2014 | 15 |
5,236 | Repeated Contextual Auctions with Strategic Buyers Kareem Amin University of Pennsylvania akareem@cis.upenn.edu Afshin Rostamizadeh Google Research rostami@google.com Umar Syed Google Research usyed@google.com Abstract Motivated by real-time advertising exchanges, we analyze the problem of pricing... | 2014 | 150 |
5,237 | Learning with Pseudo-Ensembles Philip Bachman McGill University Montreal, QC, Canada phil.bachman@gmail.com Ouais Alsharif McGill University Montreal, QC, Canada ouais.alsharif@gmail.com Doina Precup McGill University Montreal, QC, Canada dprecup@cs.mcgill.ca Abstract We formalize the notion... | 2014 | 151 |
5,238 | Top Rank Optimization in Linear Time Nan Li1 Rong Jin2 Zhi-Hua Zhou1 1National Key Laboratory for Novel Software Technology, Nanjing University, Nanjing 210023, China 2Department of Computer Science and Engineering, Michigan State University, East Lansing, MI 48824 {lin,zhouzh}@lamda.nju.edu.cn rongji... | 2014 | 152 |
5,239 | Learning Neural Network Policies with Guided Policy Search under Unknown Dynamics Sergey Levine and Pieter Abbeel Department of Electrical Engineering and Computer Science University of California, Berkeley Berkeley, CA 94709 {svlevine, pabbeel}@eecs.berkeley.edu Abstract We present a policy search meth... | 2014 | 153 |
5,240 | Optimizing F-Measures by Cost-Sensitive Classification Shameem A. Puthiya Parambath, Nicolas Usunier, Yves Grandvalet Universit´e de Technologie de Compi`egne – CNRS, Heudiasyc UMR 7253 Compi`egne, France {sputhiya,nusunier,grandval}@utc.fr Abstract We present a theoretical analysis of F-measures for binary,... | 2014 | 154 |
5,241 | Distributed Power-law Graph Computing: Theoretical and Empirical Analysis Cong Xie Dept. of Comp. Sci. and Eng. Shanghai Jiao Tong University 800 Dongchuan Road Shanghai 200240, China xcgoner1108@gmail.com Ling Yan Dept. of Comp. Sci. and Eng. Shanghai Jiao Tong University 800 Dongchuan Road Sha... | 2014 | 155 |
5,242 | Parallel Successive Convex Approximation for Nonsmooth Nonconvex Optimization Meisam Razaviyayn∗ meisamr@stanford.edu Mingyi Hong† mingyi@iastate.edu Zhi-Quan Luo‡ luozq@umn.edu Jong-Shi Pang§ jongship@usc.edu Abstract Consider the problem of minimizing the sum of a smooth (possibly non-convex) ... | 2014 | 156 |
5,243 | Active Regression by Stratification Sivan Sabato Department of Computer Science Ben Gurion University, Beer Sheva, Israel sabatos@cs.bgu.ac.il Remi Munos∗ INRIA Lille, France remi.munos@inria.fr Abstract We propose a new active learning algorithm for parametric linear regression with random design.... | 2014 | 157 |
5,244 | Distance-Based Network Recovery under Feature Correlation David Adametz, Volker Roth Department of Mathematics and Computer Science University of Basel, Switzerland {david.adametz,volker.roth}@unibas.ch Abstract We present an inference method for Gaussian graphical models when only pairwise distances of n... | 2014 | 158 |
5,245 | Rounding-based Moves for Metric Labeling M. Pawan Kumar Ecole Centrale Paris & INRIA Saclay pawan.kumar@ecp.fr Abstract Metric labeling is a special case of energy minimization for pairwise Markov random fields. The energy function consists of arbitrary unary potentials, and pairwise potentials that are propor... | 2014 | 159 |
5,246 | Analog Memories in a Balanced Rate-Based Network of E-I Neurons Dylan Festa Guillaume Hennequin M´at´e Lengyel df325@cam.ac.uk gjeh2@cam.ac.uk m.lengyel@eng.cam.ac.uk Computational & Biological Learning Lab, Department of Engineering University of Cambridge, UK Abstract The persistent and graded a... | 2014 | 16 |
5,247 | Transportability from Multiple Environments with Limited Experiments: Completeness Results Elias Bareinboim Computer Science UCLA eb@cs.ucla.edu Judea Pearl Computer Science UCLA judea@cs.ucla.edu Abstract This paper addresses the problem of mz-transportability, that is, transferring causal know... | 2014 | 160 |
5,248 | Fast and Robust Least Squares Estimation in Corrupted Linear Models Brian McWilliams⇤ Gabriel Krummenacher⇤ Mario Lucic Joachim M. Buhmann Department of Computer Science ETH Z¨urich, Switzerland {mcbrian,gabriel.krummenacher,lucic,jbuhmann}@inf.ethz.ch Abstract Subsampling methods have been recently... | 2014 | 161 |
5,249 | Incremental Local Gaussian Regression Franziska Meier1 fmeier@usc.edu Philipp Hennig2 phennig@tue.mpg.de Stefan Schaal1,2 sschaal@usc.edu 1University of Southern California Los Angeles, CA 90089, USA 2Max Planck Institute for Intelligent Systems Spemannstraße 38, T¨ubingen, Germany Abstract Loca... | 2014 | 162 |
5,250 | Controlling privacy in recommender systems Yu Xin CSAIL, MIT yuxin@mit.edu Tommi Jaakkola CSAIL, MIT tommi@csail.mit.edu Abstract Recommender systems involve an inherent trade-off between accuracy of recommendations and the extent to which users are willing to release information about their preferenc... | 2014 | 163 |
5,251 | Localized Data Fusion for Kernel k-Means Clustering with Application to Cancer Biology Mehmet G¨onen gonen@ohsu.edu Department of Biomedical Engineering Oregon Health & Science University Portland, OR 97239, USA Adam A. Margolin margolin@ohsu.edu Department of Biomedical Engineering Oregon Health & ... | 2014 | 164 |
5,252 | Object Localization based on Structural SVM using Privileged Information Jan Feyereisl, Suha Kwak∗, Jeany Son, Bohyung Han Dept. of Computer Science and Engineering, POSTECH, Pohang, Korea thefillm@gmail.com, {mercury3,jeany,bhhan}@postech.ac.kr Abstract We propose a structured prediction algorithm for obje... | 2014 | 165 |
5,253 | Robust Logistic Regression and Classification Jiashi Feng EECS Department & ICSI UC Berkeley jshfeng@berkeley.edu Huan Xu ME Department National University of Singapore mpexuh@nus.edu.sg Shie Mannor EE Department Technion shie@ee.technion.ac.il Shuicheng Yan ECE Department National Universi... | 2014 | 166 |
5,254 | Flexible Transfer Learning under Support and Model Shift Xuezhi Wang Computer Science Department Carnegie Mellon University xuezhiw@cs.cmu.edu Jeff Schneider Robotics Institute Carnegie Mellon University schneide@cs.cmu.edu Abstract Transfer learning algorithms are used when one has sufficient trai... | 2014 | 167 |
5,255 | Computing Nash Equilibria in Generalized Interdependent Security Games Hau Chan Luis E. Ortiz Department of Computer Science, Stony Brook University {hauchan,leortiz}@cs.stonybrook.edu Abstract We study the computational complexity of computing Nash equilibria in generalized interdependent-security (IDS) ... | 2014 | 168 |
5,256 | Multitask learning meets tensor factorization: task imputation via convex optimization Kishan Wimalawarne Tokyo Institute of Technology Meguro-ku, Tokyo, Japan kishan@sg.cs.titech.ac.jp Masashi Sugiyama The University of Tokyo Bunkyo-ku, Tokyo, Japan sugi@k.u-tokyo.ac.jp Ryota Tomioka TTI-C Illi... | 2014 | 169 |
5,257 | Efficient Partial Monitoring with Prior Information Hastagiri P Vanchinathan Dept. of Computer Science ETH Z¨urich, Switzerland hastagiri@inf.ethz.ch G´abor Bart´ok Dept. of Computer Science ETH Z¨urich, Switzerland bartok@inf.ethz.ch Andreas Krause Dept. of Computer Science ETH Z¨urich, Switzerla... | 2014 | 17 |
5,258 | Mind the Nuisance: Gaussian Process Classification using Privileged Noise Daniel Hern´andez-Lobato Universidad Aut´onoma de Madrid Madrid, Spain daniel.hernandez@uam.es Viktoriia Sharmanska IST Austria Klosterneuburg, Austria vsharman@ist.ac.at Kristian Kersting TU Dortmund Dortmund, Germany fi... | 2014 | 170 |
5,259 | On Integrated Clustering and Outlier Detection Lionel Ott University of Sydney lott4241@uni.sydney.edu.au Linsey Pang University of Sydney qlinsey@it.usyd.edu.au Fabio Ramos University of Sydney fabio.ramos@sydney.edu.au Sanjay Chawla University of Sydney sanjay.chawla@sydney.edu.au Abstract ... | 2014 | 171 |
5,260 | Latent Support Measure Machines for Bag-of-Words Data Classification Yuya Yoshikawa Nara Institute of Science and Technology Nara, 630-0192, Japan yoshikawa.yuya.yl9@is.naist.jp Tomoharu Iwata NTT Communication Science Laboratories Kyoto, 619-0237, Japan iwata.tomoharu@lab.ntt.co.jp Hiroshi Sawada ... | 2014 | 172 |
5,261 | Sparse Polynomial Learning and Graph Sketching Murat Kocaoglu1∗, Karthikeyan Shanmugam1†, Alexandros G.Dimakis1‡, Adam Klivans2⋆ 1Department of Electrical and Computer Engineering, 2Department of Computer Science The University of Texas at Austin, USA ∗mkocaoglu@utexas.edu, †karthiksh@utexas.edu ‡dimakis@aust... | 2014 | 173 |
5,262 | The Noisy Power Method: A Meta Algorithm with Applications Moritz Hardt∗ IBM Research Almaden Eric Price† IBM Research Almaden Abstract We provide a new robust convergence analysis of the well-known power method for computing the dominant singular vectors of a matrix that we call the noisy power metho... | 2014 | 174 |
5,263 | Robust Tensor Decomposition with Gross Corruption Quanquan Gu∗ Department of Operations Research and Financial Engineering Princeton University Princeton, NJ 08544 qgu@princeton.edu Huan Gui∗Jiawei Han Department of Computer Science University of Illinois at Urbana-Champaign Urbana, IL 61801 {hu... | 2014 | 175 |
5,264 | RAAM: The Benefits of Robustness in Approximating Aggregated MDPs in Reinforcement Learning Marek Petrik IBM T. J. Watson Research Center Yorktown Heights, NY 10598 mpetrik@us.ibm.com Dharmashankar Subramanian IBM T. J. Watson Research Center Yorktown Heights, NY 10598 dharmash@us.ibm.com Abstract ... | 2014 | 176 |
5,265 | On Prior Distributions and Approximate Inference for Structured Variables Oluwasanmi Koyejo Psychology Dept., Stanford sanmi@stanford.edu Rajiv Khanna ECE Dept., UT Austin rajivak@utexas.edu Joydeep Ghosh ECE Dept., UT Austin ghosh@ece.utexas.edu Russell A. Poldrack Psychology Dept., Stanford ... | 2014 | 177 |
5,266 | A Residual Bootstrap for High-Dimensional Regression with Near Low-Rank Designs Miles E. Lopes Department of Statistics University of California, Berkeley Berkeley, CA 94720 mlopes@stat.berkeley.edu Abstract We study the residual bootstrap (RB) method in the context of high-dimensional linear regressi... | 2014 | 178 |
5,267 | Tighten after Relax: Minimax-Optimal Sparse PCA in Polynomial Time Zhaoran Wang Huanran Lu Han Liu Department of Operations Research and Financial Engineering Princeton University Princeton, NJ 08540 {zhaoran,huanranl,hanliu}@princeton.edu Abstract We provide statistical and computational analysis o... | 2014 | 179 |
5,268 | Near-optimal Reinforcement Learning in Factored MDPs Ian Osband Stanford University iosband@stanford.edu Benjamin Van Roy Stanford University bvr@stanford.edu Abstract Any reinforcement learning algorithm that applies to all Markov decision processes (MDPs) will suffer Ω( Ô SAT) regret on some MD... | 2014 | 18 |
5,269 | Learning to Search in Branch-and-Bound Algorithms⇤ He He Hal Daum´e 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 Branch-an... | 2014 | 180 |
5,270 | Bayesian Inference for Structured Spike and Slab Priors Michael Riis Andersen, Ole Winther & Lars Kai Hansen DTU Compute, Technical University of Denmark DK-2800 Kgs. Lyngby, Denmark {miri, olwi, lkh}@dtu.dk Abstract Sparse signal recovery addresses the problem of solving underdetermined linear inverse ... | 2014 | 181 |
5,271 | Just-In-Time Learning for Fast and Flexible Inference S. M. Ali Eslami, Daniel Tarlow, Pushmeet Kohli and John Winn Microsoft Research {alie,dtarlow,pkohli,jwinn}@microsoft.com Abstract Much of research in machine learning has centered around the search for inference algorithms that are both general-purpose... | 2014 | 182 |
5,272 | Fast Kernel Learning for Multidimensional Pattern Extrapolation Andrew Gordon Wilson∗ CMU Elad Gilboa∗ WUSTL Arye Nehorai WUSTL John P. Cunningham Columbia Abstract The ability to automatically discover patterns and perform extrapolation is an essential quality of intelligent systems. Kernel metho... | 2014 | 183 |
5,273 | Recursive Context Propagation Network for Semantic Scene Labeling Abhishek Sharma University of Maryland College Park, MD bhokaal@cs.umd.edu Oncel Tuzel Ming-Yu Liu Mitsubishi Electric Research Labs (MERL) Cambridge, MA {oncel,mliu}@merl.com Abstract We propose a deep feed-forward neural network... | 2014 | 184 |
5,274 | Spectral Methods Meet EM: A Provably Optimal Algorithm for Crowdsourcing Yuchen Zhang† Xi Chen♯ Dengyong Zhou∗ Michael I. Jordan† †University of California, Berkeley, Berkeley, CA 94720 {yuczhang,jordan}@berkeley.edu ♯New York University, New York, NY 10012 xichen@nyu.edu ∗Microsoft Research, 1 Micr... | 2014 | 185 |
5,275 | Fairness in Multi-Agent Sequential Decision-Making Chongjie Zhang and Julie A. Shah Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology Cambridge, MA 02139 {chongjie,julie a shah}@csail.mit.edu Abstract We define a fairness solution criterion for multi-agent decisio... | 2014 | 186 |
5,276 | Multi-Class Deep Boosting Vitaly Kuznetsov Courant Institute 251 Mercer Street New York, NY 10012 vitaly@cims.nyu.edu Mehryar Mohri Courant Institute & Google Research 251 Mercer Street New York, NY 10012 mohri@cims.nyu.edu Umar Syed Google Research 76 Ninth Avenue New York, NY 10011 usyed... | 2014 | 187 |
5,277 | Depth Map Prediction from a Single Image using a Multi-Scale Deep Network David Eigen deigen@cs.nyu.edu Christian Puhrsch cpuhrsch@nyu.edu Rob Fergus fergus@cs.nyu.edu Dept. of Computer Science, Courant Institute, New York University Abstract Predicting depth is an essential component in understandi... | 2014 | 188 |
5,278 | Provable Submodular Minimization using Wolfe’s Algorithm Deeparnab Chakrabarty∗ Prateek Jain∗ Pravesh Kothari† Abstract Owing to several applications in large scale learning and vision problems, fast submodular function minimization (SFM) has become a critical problem. Theoretically, unconstrained SFM can... | 2014 | 189 |
5,279 | Robust Kernel Density Estimation by Scaling and Projection in Hilbert Space Robert A. Vandermeulen Department of EECS University of Michigan Ann Arbor, MI 48109 rvdm@umich.edu Clayton D. Scott Deparment of EECS Univeristy of Michigan Ann Arbor, MI 48109 clayscot@umich.edu Abstract While robust... | 2014 | 19 |
5,280 | Online and Stochastic Gradient Methods for Non-decomposable Loss Functions Purushottam Kar∗ Harikrishna Narasimhan† Prateek Jain∗ ∗Microsoft Research, INDIA †Indian Institute of Science, Bangalore, INDIA {t-purkar,prajain}@microsoft.com, harikrishna@csa.iisc.ernet.in Abstract Modern applications in se... | 2014 | 190 |
5,281 | On Model Parallelization and Scheduling Strategies for Distributed Machine Learning †Seunghak Lee, †Jin Kyu Kim, †Xun Zheng, §Qirong Ho, †Garth A. Gibson, †Eric P. Xing †School of Computer Science Carnegie Mellon University Pittsburgh, PA 15213 seunghak@, jinkyuk@, xunzheng@, garth@, epxing@cs.cmu.edu §... | 2014 | 191 |
5,282 | Shape and Illumination from Shading using the Generic Viewpoint Assumption Daniel Zoran ∗ CSAIL, MIT danielz@mit.edu Dilip Krishnan ∗ CSAIL, MIT dilipkay@mit.edu Jose Bento Boston College jose.bento@bc.edu William T. Freeman CSAIL, MIT billf@mit.edu Abstract The Generic Viewpoint Assumptio... | 2014 | 192 |
5,283 | Asynchronous Anytime Sequential Monte Carlo Brooks Paige Frank Wood Department of Engineering Science University of Oxford Oxford, UK {brooks,fwood}@robots.ox.ac.uk Arnaud Doucet Yee Whye Teh Department of Statistics University of Oxford Oxford, UK {doucet,y.w.teh}@stats.ox.ac.uk Abstract We... | 2014 | 193 |
5,284 | Sparse space-time deconvolution for Calcium image analysis Ferran Diego Fred A. Hamprecht Heidelberg Collaboratory for Image Processing (HCI) Interdisciplinary Center for Scientific Computing (IWR) University of Heidelberg, Heidelberg 69115, Germany {ferran.diego,fred.hamprecht}@iwr.uni-heidelberg.de Abs... | 2014 | 194 |
5,285 | From Stochastic Mixability to Fast Rates Nishant A. Mehta Research School of Computer Science Australian National University nishant.mehta@anu.edu.au Robert C. Williamson Research School of Computer Science Australian National University and NICTA bob.williamson@anu.edu.au Abstract Empirical risk mi... | 2014 | 195 |
5,286 | Algorithm selection by rational metareasoning as a model of human strategy selection Falk Lieder Helen Wills Neuroscience Institute, UC Berkeley falk.lieder@berkeley.edu Dillon Plunkett Department of Psychology, UC Berkeley dillonplunkett@berkeley.edu Jessica B. Hamrick Department of Psychology, UC Be... | 2014 | 196 |
5,287 | PAC-Bayesian AUC classification and scoring James Ridgway∗ CREST and CEREMADE University Dauphine james.ridgway@ensae.fr Pierre Alquier CREST (ENSAE) pierre.alquier@ucd.ie Nicolas Chopin CREST (ENSAE) and HEC Paris nicolas.chopin@ensae.fr Feng Liang University of Illinois at Urbana-Champaign lian... | 2014 | 197 |
5,288 | Probabilistic Differential Dynamic Programming Yunpeng Pan and Evangelos A. Theodorou Daniel Guggenheim School of Aerospace Engineering Institute for Robotics and Intelligent Machines Georgia Institute of Technology Atlanta, GA 30332 ypan37@gatech.edu, evangelos.theodorou@ae.gatech.edu Abstract We prese... | 2014 | 198 |
5,289 | Improved Multimodal Deep Learning with Variation of Information Kihyuk Sohn, Wenling Shang and Honglak Lee University of Michigan Ann Arbor, MI, USA {kihyuks,shangw,honglak}@umich.edu Abstract Deep learning has been successfully applied to multimodal representation learning problems, with a common strategy ... | 2014 | 199 |
5,290 | Exploiting easy data in online optimization Amir Sani Gergely Neu Alessandro Lazaric SequeL team, INRIA Lille – Nord Europe, France {amir.sani,gergely.neu,alessandro.lazaric}@inria.fr Abstract We consider the problem of online optimization, where a learner chooses a decision from a given decision set and ... | 2014 | 2 |
5,291 | Extracting Certainty from Uncertainty: Transductive Pairwise Classification from Pairwise Similarities Tianbao Yang†, Rong Jin‡♮ †The University of Iowa, Iowa City, IA 52242 ‡Michigan State University, East Lansing, MI 48824 ♮Alibaba Group, Hangzhou 311121, China tianbao-yang@uiowa.edu, rongjin@msu.edu Abs... | 2014 | 20 |
5,292 | On Sparse Gaussian Chain Graph Models Calvin McCarter Machine Learning Department Carnegie Mellon University calvinm@cmu.edu Seyoung Kim Lane Center for Computational Biology Carnegie Mellon University sssykim@cs.cmu.edu Abstract In this paper, we address the problem of learning the structure of Gau... | 2014 | 200 |
5,293 | Convolutional Kernel Networks Julien Mairal, Piotr Koniusz, Zaid Harchaoui, and Cordelia Schmid Inria∗ firstname.lastname@inria.fr Abstract An important goal in visual recognition is to devise image representations that are invariant to particular transformations. In this paper, we address this goal with a ... | 2014 | 201 |
5,294 | Learning Chordal Markov Networks by Dynamic Programming Kustaa Kangas Teppo Niinim¨aki Mikko Koivisto Helsinki Institute for Information Technology HIIT Department of Computer Science, University of Helsinki {jwkangas,tzniinim,mkhkoivi}@cs.helsinki.fi Abstract We present an algorithm for finding a chor... | 2014 | 202 |
5,295 | From MAP to Marginals: Variational Inference in Bayesian Submodular Models Josip Djolonga Department of Computer Science ETH Z¨urich josipd@inf.ethz.ch Andreas Krause Department of Computer Science ETH Z¨urich krausea@ethz.ch Abstract Submodular optimization has found many applications in machine ... | 2014 | 203 |
5,296 | Algorithms for CVaR Optimization in MDPs Yinlam Chow∗ Institute of Computational & Mathematical Engineering, Stanford University Mohammad Ghavamzadeh† Adobe Research & INRIA Lille - Team SequeL Abstract In many sequential decision-making problems we may want to manage risk by minimizing some measure of va... | 2014 | 204 |
5,297 | Structure Regularization for Structured Prediction Xu Sun∗† ∗MOE Key Laboratory of Computational Linguistics, Peking University †School of Electronics Engineering and Computer Science, Peking University xusun@pku.edu.cn Abstract While there are many studies on weight regularization, the study on structure r... | 2014 | 205 |
5,298 | Bayes-Adaptive Simulation-based Search with Value Function Approximation Arthur Guez∗,1,2 Nicolas Heess2 David Silver2 Peter Dayan1 ∗aguez@google.com 1Gatsby Unit, UCL 2Google DeepMind Abstract Bayes-adaptive planning offers a principled solution to the explorationexploitation trade-off under model ... | 2014 | 206 |
5,299 | Optimal Teaching for Limited-Capacity Human Learners Kaustubh Raosaheb Patil Affective Brain Lab, UCL & MIT Sloan Neuroeconomics Lab kaustubh.patil@gmail.com Xiaojin Zhu Department of Computer Sciences University of Wisconsin-Madison jerryzhu@cs.wisc.edu Łukasz Kope´c Experimental Psychology Uni... | 2014 | 207 |
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