Table of Contents

• Kernel Mean Estimation via Spectral FilteringKrikamol Muandet, Bharath K. Sriperumbudur, Bernhard Schölkopf. 1-9 [doi]
• Semi-Separable Hamiltonian Monte Carlo for Inference in Bayesian Hierarchical ModelsYichuan Zhang, Charles A. Sutton. 10-18 [doi]
• Communication Efficient Distributed Machine Learning with the Parameter ServerMu Li, David G. Andersen, Alex J. Smola, Kai Yu. 19-27 [doi]
• The Infinite Mixture of Infinite Gaussian MixturesHalid Ziya Yerebakan, Bartek Rajwa, Murat Dundar. 28-36 [doi]
• Robust Classification Under Sample Selection BiasAnqi Liu, Brian D. Ziebart. 37-45 [doi]
• Zeta Hull Pursuits: Learning Nonconvex Data HullsYuanjun Xiong, Wei Liu, Deli Zhao, Xiaoou Tang. 46-54 [doi]
• Grouping-Based Low-Rank Trajectory Completion and 3D ReconstructionKaterina Fragkiadaki, Marta Salas, Pablo Andrés Arbelaez, Jitendra Malik. 55-63 [doi]
• Sparse Space-Time Deconvolution for Calcium Image AnalysisFerran Diego Andilla, Fred A. Hamprecht. 64-72 [doi]
• Restricted Boltzmann machines modeling human choiceTakayuki Osogami, Makoto Otsuka. 73-81 [doi]
• Multiscale Fields of PatternsPedro F. Felzenszwalb, John G. Oberlin. 82-90 [doi]
• large scale canonical correlation analysis with iterative least squaresYichao Lu, Dean P. Foster. 91-99 [doi]
• Altitude Training: Strong Bounds for Single-Layer DropoutStefan Wager, William Fithian, Sida I. Wang, Percy Liang. 100-108 [doi]
• Rounding-based Moves for Metric LabelingM. Pawan Kumar. 109-117 [doi]
• Parallel Double Greedy Submodular MaximizationXinghao Pan, Stefanie Jegelka, Joseph E. Gonzalez, Joseph K. Bradley, Michael I. Jordan. 118-126 [doi]
• Multivariate Regression with CalibrationHan Liu, Lie Wang, Tuo Zhao. 127-135 [doi]
• Exact Post Model Selection Inference for Marginal ScreeningJason D. Lee, Jonathan E. Taylor. 136-144 [doi]
• On a Theory of Nonparametric Pairwise Similarity for Clustering: Connecting Clustering to ClassificationYingzhen Yang, Feng Liang, Shuicheng Yan, Zhangyang Wang, Thomas S. Huang. 145-153 [doi]
• Just-In-Time Learning for Fast and Flexible InferenceS. M. Ali Eslami, Daniel Tarlow, Pushmeet Kohli, John M. Winn. 154-162 [doi]
• Fundamental Limits of Online and Distributed Algorithms for Statistical Learning and EstimationOhad Shamir. 163-171 [doi]
• Quantized Kernel Learning for Feature MatchingDanfeng Qin, Xuanli Chen, Matthieu Guillaumin, Luc J. Van Gool. 172-180 [doi]
• Parallel Direction Method of MultipliersHuahua Wang, Arindam Banerjee, Zhi-Quan Luo. 181-189 [doi]
• (Almost) No Label No CryGiorgio Patrini, Richard Nock, Tiberio Caetano, Paul Rivera. 190-198 [doi]
• Stochastic Multi-Armed-Bandit Problem with Non-stationary RewardsYonatan Gur, Assaf J. Zeevi, Omar Besbes. 199-207 [doi]
• Object Localization based on Structural SVM using Privileged InformationJan Feyereisl, Suha Kwak, Jeany Son, Bohyung Han. 208-216 [doi]
• Multi-View Perceptron: a Deep Model for Learning Face Identity and View RepresentationsZhenyao Zhu, Ping Luo, Xiaogang Wang, Xiaoou Tang. 217-225 [doi]
• Shape and Illumination from Shading using the Generic Viewpoint AssumptionDaniel Zoran, Dilip Krishnan, José Bento, Bill Freeman. 226-234 [doi]
• Parallel Sampling of HDPs using Sub-Cluster SplitsJason Chang, John W. Fisher III. 235-243 [doi]
• From MAP to Marginals: Variational Inference in Bayesian Submodular ModelsJosip Djolonga, Andreas Krause. 244-252 [doi]
• Robust Logistic Regression and ClassificationJiashi Feng, Huan Xu, Shie Mannor, Shuicheng Yan. 253-261 [doi]
• Extracting Certainty from Uncertainty: Transductive Pairwise Classification from Pairwise SimilaritiesTianbao Yang, Rong Jin. 262-270 [doi]
• A Unified Semantic Embedding: Relating Taxonomies and AttributesSung Ju Hwang, Leonid Sigal. 271-279 [doi]
• Transportability from Multiple Environments with Limited Experiments: Completeness ResultsElias Bareinboim, Judea Pearl. 280-288 [doi]
• Augmentative Message Passing for Traveling Salesman Problem and Graph PartitioningSiamak Ravanbakhsh, Reihaneh Rabbany, Russell Greiner. 289-297 [doi]
• Causal Inference through a Witness Protection ProgramRicardo Silva, Robin Evans. 298-306 [doi]
• Incremental Clustering: The Case for Extra ClustersMargareta Ackerman, Sanjoy Dasgupta. 307-315 [doi]
• Multi-scale Graphical Models for Spatio-Temporal ProcessesFirdaus Janoos, Huseyin Denli, Niranjan A. Subrahmanya. 316-324 [doi]
• Iterative Neural Autoregressive Distribution Estimator NADE-kTapani Raiko, Yao Li, KyungHyun Cho, Yoshua Bengio. 325-333 [doi]
• Sparse PCA via Covariance ThresholdingYash Deshpande, Andrea Montanari. 334-342 [doi]
• Low-dimensional models of neural population activity in sensory cortical circuitsEvan W. Archer, Urs Köster, Jonathan W. Pillow, Jakob H. Macke. 343-351 [doi]
• A Synaptical Story of Persistent Activity with Graded Lifetime in a Neural SystemYuanyuan Mi, Luozheng Li, Dahui Wang, Si Wu. 352-360 [doi]
• A Representation Theory for Ranking FunctionsHarsh H. Pareek, Pradeep K. Ravikumar. 361-369 [doi]
• Near-optimal sample compression for nearest neighborsLee-Ad Gottlieb, Aryeh Kontorovich, Pinhas Nisnevitch. 370-378 [doi]
• Combinatorial Pure Exploration of Multi-Armed BanditsShouyuan Chen, Tian Lin, Irwin King, Michael R. Lyu, Wei Chen. 379-387 [doi]
• Log-Hilbert-Schmidt metric between positive definite operators on Hilbert spacesMinh Ha Quang, Marco San-Biagio, Vittorio Murino. 388-396 [doi]
• Consistency of Spectral Partitioning of Uniform Hypergraphs under Planted Partition ModelDebarghya Ghoshdastidar, Ambedkar Dukkipati. 397-405 [doi]
• Spectral Clustering of graphs with the Bethe HessianAlaa Saade, Florent Krzakala, Lenka Zdeborová. 406-414 [doi]
• Fast and Robust Least Squares Estimation in Corrupted Linear ModelsBrian McWilliams, Gabriel Krummenacher, Mario Lucic, Joachim M. Buhmann. 415-423 [doi]
• Local Decorrelation For Improved Pedestrian DetectionWoonhyun Nam, Piotr Dollár, Joon Hee Han. 424-432 [doi]
• Robust Kernel Density Estimation by Scaling and Projection in Hilbert SpaceRobert A. Vandermeulen, Clayton Scott. 433-441 [doi]
• Beyond Disagreement-Based Agnostic Active LearningChicheng Zhang, Kamalika Chaudhuri. 442-450 [doi]
• Bayes-Adaptive Simulation-based Search with Value Function ApproximationArthur Guez, Nicolas Heess, David Silver, Peter Dayan. 451-459 [doi]
• A State-Space Model for Decoding Auditory Attentional Modulation from MEG in a Competing-Speaker EnvironmentSahar Akram, Jonathan Z. Simon, Shihab A. Shamma, Behtash Babadi. 460-468 [doi]
• Active Regression by StratificationSivan Sabato, Rémi Munos. 469-477 [doi]
• Sensory Integration and Density EstimationJoseph G. Makin, Philip N. Sabes. 478-486 [doi]
• Learning Deep Features for Scene Recognition using Places DatabaseBolei Zhou, Àgata Lapedriza, Jianxiong Xiao, Antonio Torralba, Aude Oliva. 487-495 [doi]
• A Complete Variational TrackerRyan D. Turner, Steven Bottone, Bhargav Avasarala. 496-504 [doi]
• Spike Frequency Adaptation Implements Anticipative Tracking in Continuous Attractor Neural NetworksYuanyuan Mi, C. C. Alan Fung, K. Y. Michael Wong, Si Wu. 505-513 [doi]
• Efficient Sampling for Learning Sparse Additive Models in High DimensionsHemant Tyagi, Bernd Gärtner, Andreas Krause. 514-522 [doi]
• Deep Joint Task Learning for Generic Object ExtractionXiaolong Wang, Liliang Zhang, Liang Lin, Zhujin Liang, Wangmeng Zuo. 523-531 [doi]
• Robust Bayesian Max-Margin ClusteringChangyou Chen, Jun Zhu, Xinhua Zhang. 532-540 [doi]
• Permutation Diffusion Maps (PDM) with Application to the Image Association Problem in Computer VisionDeepti Pachauri, Risi Kondor, Gautam Sargur, Vikas Singh. 541-549 [doi]
• Bounded Regret for Finite-Armed Structured BanditsTor Lattimore, Rémi Munos. 550-558 [doi]
• Coresets for k-Segmentation of Streaming DataGuy Rosman, Mikhail V. Volkov, Dan Feldman, John W. Fisher III, Daniela Rus. 559-567 [doi]
• Two-Stream Convolutional Networks for Action Recognition in VideosKaren Simonyan, Andrew Zisserman. 568-576 [doi]
• Discovering Structure in High-Dimensional Data Through Correlation ExplanationGreg Ver Steeg, Aram Galstyan. 577-585 [doi]
• Positive Curvature and Hamiltonian Monte CarloChristof Seiler, Simon Rubinstein-Salzedo, Susan Holmes. 586-594 [doi]
• Learning Mixed Multinomial Logit Model from Ordinal DataSewoong Oh, Devavrat Shah. 595-603 [doi]
• Near-optimal Reinforcement Learning in Factored MDPsIan Osband, Benjamin Van Roy. 604-612 [doi]
• Efficient learning by implicit exploration in bandit problems with side observationsTomás Kocák, Gergely Neu, Michal Valko, Rémi Munos. 613-621 [doi]
• Repeated Contextual Auctions with Strategic BuyersKareem Amin, Afshin Rostamizadeh, Umar Syed. 622-630 [doi]
• Recursive Inversion Models for PermutationsChristopher Meek, Marina Meila. 631-639 [doi]
• On the Convergence Rate of Decomposable Submodular Function MinimizationRobert Nishihara, Stefanie Jegelka, Michael I. Jordan. 640-648 [doi]
• New Rules for Domain Independent Lifted MAP InferenceHappy Mittal, Prasoon Goyal, Vibhav G. Gogate, Parag Singla. 649-657 [doi]
• PAC-Bayesian AUC classification and scoringJames Ridgway, Pierre Alquier, Nicolas Chopin, Feng Liang. 658-666 [doi]
• Optimization Methods for Sparse Pseudo-Likelihood Graphical Model SelectionSang Oh, Onkar Dalal, Kshitij Khare, Bala Rajaratnam. 667-675 [doi]
• On Prior Distributions and Approximate Inference for Structured VariablesOluwasanmi O. Koyejo, Rajiv Khanna, Joydeep Ghosh, Russell A. Poldrack. 676-684 [doi]
• On Iterative Hard Thresholding Methods for High-dimensional M-EstimationPrateek Jain 0002, Ambuj Tewari, Purushottam Kar. 685-693 [doi]
• Online and Stochastic Gradient Methods for Non-decomposable Loss FunctionsPurushottam Kar, Harikrishna Narasimhan, Prateek Jain 0002. 694-702 [doi]
• Analysis of Learning from Positive and Unlabeled DataMarthinus Christoffel du Plessis, Gang Niu, Masashi Sugiyama. 703-711 [doi]
• Dimensionality Reduction with Subspace Structure PreservationDevansh Arpit, Ifeoma Nwogu, Venu Govindaraju. 712-720 [doi]
• Constrained convex minimization via model-based excessive gapQuoc Tran-Dinh, Volkan Cevher. 721-729 [doi]
• Poisson Process Jumping between an Unknown Number of Rates: Application to Neural Spike DataFlorian Stimberg, Andreas Ruttor, Manfred Opper. 730-738 [doi]
• Probabilistic ODE Solvers with Runge-Kutta MeansMichael Schober, David K. Duvenaud, Philipp Hennig. 739-747 [doi]
• Optimal decision-making with time-varying evidence reliabilityJan Drugowitsch, Rubén Moreno-Bote, Alexandre Pouget. 748-756 [doi]
• Learning Shuffle Ideals Under Restricted DistributionsDongqu Chen. 757-765 [doi]
• Discriminative Unsupervised Feature Learning with Convolutional Neural NetworksAlexey Dosovitskiy, Jost Tobias Springenberg, Martin A. Riedmiller, Thomas Brox. 766-774 [doi]
• Distance-Based Network Recovery under Feature CorrelationDavid Adametz, Volker Roth. 775-783 [doi]
• Bandit Convex Optimization: Towards Tight BoundsElad Hazan, Kfir Y. Levy. 784-792 [doi]
• Projective dictionary pair learning for pattern classificationShuhang Gu, Lei Zhang, Wangmeng Zuo, Xiangchu Feng. 793-801 [doi]
• Provable Submodular Minimization using Wolfe's AlgorithmDeeparnab Chakrabarty, Prateek Jain 0002, Pravesh Kothari. 802-809 [doi]
• Exploiting easy data in online optimizationAmir Sani, Gergely Neu, Alessandro Lazaric. 810-818 [doi]
• Sparse Multi-Task Reinforcement LearningDaniele Calandriello, Alessandro Lazaric, Marcello Restelli. 819-827 [doi]
• Best-Arm Identification in Linear BanditsMarta Soare, Alessandro Lazaric, Rémi Munos. 828-836 [doi]
• Mind the Nuisance: Gaussian Process Classification using Privileged NoiseDaniel Hernández-Lobato, Viktoriia Sharmanska, Kristian Kersting, Christoph H. Lampert, Novi Quadrianto. 837-845 [doi]
• Tight Bounds for Influence in Diffusion Networks and Application to Bond Percolation and EpidemiologyRémi Lemonnier, Kevin Scaman, Nicolas Vayatis. 846-854 [doi]
• On the Computational Efficiency of Training Neural NetworksRoi Livni, Shai Shalev-Shwartz, Ohad Shamir. 855-863 [doi]
• Self-Adaptable Templates for Feature CodingXavier Boix, Gemma Roig, Salomon Diether, Luc Van Gool. 864-872 [doi]
• Multilabel Structured Output Learning with Random Spanning Trees of Max-Margin Markov NetworksMario Marchand, HongYu Su, Emilie Morvant, Juho Rousu, John Shawe-Taylor. 873-881 [doi]
• Stochastic Network Design in Bidirected TreesXiaoJian Wu, Daniel R. Sheldon, Shlomo Zilberstein. 882-890 [doi]
• Learning convolution filters for inverse covariance estimation of neural network connectivityGeorge Mohler. 891-899 [doi]
• SerialRank: Spectral Ranking using SeriationFajwel Fogel, Alexandre d'Aspremont, Milan Vojnovic. 900-908 [doi]
• Clamping Variables and Approximate InferenceAdrian Weller, Tony Jebara. 909-917 [doi]
• Predictive Entropy Search for Efficient Global Optimization of Black-box FunctionsJosé Miguel Hernández-Lobato, Matthew W. Hoffman, Zoubin Ghahramani. 918-926 [doi]
• A Block-Coordinate Descent Approach for Large-scale Sparse Inverse Covariance EstimationEran Treister, Javier Turek. 927-935 [doi]
• Efficient Inference of Continuous Markov Random Fields with Polynomial PotentialsShenlong Wang, Alexander G. Schwing, Raquel Urtasun. 936-944 [doi]
• Scalable Methods for Nonnegative Matrix Factorizations of Near-separable Tall-and-skinny MatricesAustin R. Benson, Jason D. Lee, Bartek Rajwa, David F. Gleich. 945-953 [doi]
• Inferring synaptic conductances from spike trains with a biophysically inspired point process modelKenneth W. Latimer, E. J. Chichilnisky, Fred Rieke, Jonathan W. Pillow. 954-962 [doi]
• Expectation Backpropagation: Parameter-Free Training of Multilayer Neural Networks with Continuous or Discrete WeightsDaniel Soudry, Itay Hubara, Ron Meir. 963-971 [doi]
• Incremental Local Gaussian RegressionFranziska Meier, Philipp Hennig, Stefan Schaal. 972-980 [doi]
• General Table Completion using a Bayesian Nonparametric ModelIsabel Valera, Zoubin Ghahramani. 981-989 [doi]
• Universal Option ModelsHengshuai Yao, Csaba Szepesvári, Richard S. Sutton, Joseph Modayil, Shalabh Bhatnagar. 990-998 [doi]
• Approximating Hierarchical MV-sets for Hierarchical ClusteringAssaf Glazer, Omer Weissbrod, Michael Lindenbaum, Shaul Markovitch. 999-1007 [doi]
• Constant Nullspace Strong Convexity and Fast Convergence of Proximal Methods under High-Dimensional SettingsEn-Hsu Yen, Cho-Jui Hsieh, Pradeep K. Ravikumar, Inderjit S. Dhillon. 1008-1016 [doi]
• Stochastic Gradient Descent, Weighted Sampling, and the Randomized Kaczmarz algorithmDeanna Needell, Rachel Ward, Nathan Srebro. 1017-1025 [doi]
• A Framework for Testing Identifiability of Bayesian Models of PerceptionLuigi Acerbi, Wei Ji Ma, Sethu Vijayakumar. 1026-1034 [doi]
• Optimistic Planning in Markov Decision Processes Using a Generative ModelBalázs Szörényi, Gunnar Kedenburg, Rémi Munos. 1035-1043 [doi]
• Gaussian Process Volatility ModelYue Wu, José Miguel Hernández-Lobato, Zoubin Ghahramani. 1044-1052 [doi]
• A Safe Screening Rule for Sparse Logistic RegressionJie Wang, Jiayu Zhou, Jun Liu, Peter Wonka, Jieping Ye. 1053-1061 [doi]
• Hardness of parameter estimation in graphical modelsGuy Bresler, David Gamarnik, Devavrat Shah. 1062-1070 [doi]
• Learning Neural Network Policies with Guided Policy Search under Unknown DynamicsSergey Levine, Pieter Abbeel. 1071-1079 [doi]
• Magnitude-sensitive preference formation`Nisheeth Srivastava, Ed Vul, Paul R. Schrater. 1080-1088 [doi]
• Extreme banditsAlexandra Carpentier, Michal Valko. 1089-1097 [doi]
• Distributed Estimation, Information Loss and Exponential FamiliesQiang Liu, Alexander T. Ihler. 1098-1106 [doi]
• Non-convex Robust PCAPraneeth Netrapalli, Niranjan U. N, Sujay Sanghavi, Animashree Anandkumar, Prateek Jain 0002. 1107-1115 [doi]
• Simultaneous Model Selection and Optimization through Parameter-free Stochastic LearningFrancesco Orabona. 1116-1124 [doi]
• Learning From Weakly Supervised Data by The Expectation Loss SVM (e-SVM) algorithmJun Zhu, Junhua Mao, Alan L. Yuille. 1125-1133 [doi]
• Message Passing Inference for Large Scale Graphical Models with High Order PotentialsJian Zhang, Alexander G. Schwing, Raquel Urtasun. 1134-1142 [doi]
• Encoding High Dimensional Local Features by Sparse Coding Based Fisher VectorsLingqiao Liu, Chunhua Shen, Lei Wang, Anton van den Hengel, Chao Wang. 1143-1151 [doi]
• Dependent nonparametric trees for dynamic hierarchical clusteringKumar Dubey, Qirong Ho, Sinead A. Williamson, Eric P. Xing. 1152-1160 [doi]
• Causal Strategic Inference in Networked Microfinance EconomiesMohammad Tanvir Irfan, Luis E. Ortiz. 1161-1169 [doi]
• Learning Multiple Tasks in Parallel with a Shared AnnotatorHaim Cohen, Koby Crammer. 1170-1178 [doi]
• Reducing the Rank in Relational Factorization Models by Including Observable PatternsMaximilian Nickel, Xueyan Jiang, Volker Tresp. 1179-1187 [doi]
• Clustering from Labels and Time-Varying GraphsShiau Hong Lim, Yudong Chen, Huan Xu. 1188-1196 [doi]
• From Stochastic Mixability to Fast RatesNishant A. Mehta, Robert C. Williamson. 1197-1205 [doi]
• Recovery of Coherent Data via Low-Rank Dictionary PursuitGuangcan Liu, Ping Li 0001. 1206-1214 [doi]
• Inferring sparse representations of continuous signals with continuous orthogonal matching pursuitKarin C. Knudson, Jacob Yates, Alexander Huk, Jonathan W. Pillow. 1215-1223 [doi]
• Analysis of Variational Bayesian Latent Dirichlet Allocation: Weaker Sparsity Than MAPShinichi Nakajima, Issei Sato, Masashi Sugiyama, Kazuho Watanabe, Hiroko Kobayashi. 1224-1232 [doi]
• Discovering, Learning and Exploiting RelevanceCem Tekin, Mihaela van der Schaar. 1233-1241 [doi]
• Divide-and-Conquer Learning by Anchoring a Conical HullTianyi Zhou, Jeff A. Bilmes, Carlos Guestrin. 1242-1250 [doi]
• Extended and Unscented Gaussian ProcessesDaniel M. Steinberg, Edwin V. Bonilla. 1251-1259 [doi]
• Spectral Methods meet EM: A Provably Optimal Algorithm for CrowdsourcingYuchen Zhang, Xi Chen, Dengyong Zhou, Michael I. Jordan. 1260-1268 [doi]
• Exploiting Linear Structure Within Convolutional Networks for Efficient EvaluationEmily L. Denton, Wojciech Zaremba, Joan Bruna, Yann LeCun, Rob Fergus. 1269-1277 [doi]
• Learning to Discover Efficient Mathematical IdentitiesWojciech Zaremba, Karol Kurach, Rob Fergus. 1278-1286 [doi]
• The Large Margin Mechanism for Differentially Private MaximizationKamalika Chaudhuri, Daniel Hsu, Shuang Song. 1287-1295 [doi]
• DFacTo: Distributed Factorization of TensorsJoon Hee Choi, S. Vishwanathan. 1296-1304 [doi]
• Localized Data Fusion for Kernel k-Means Clustering with Application to Cancer BiologyMehmet Gönen, Adam A. Margolin. 1305-1313 [doi]
• Conditional Swap Regret and Conditional Correlated EquilibriumMehryar Mohri, Scott Yang. 1314-1322 [doi]
• Mode Estimation for High Dimensional Discrete Tree Graphical ModelsChao Chen, Han Liu, Dimitris Metaxas, Tianqi Zhao. 1323-1331 [doi]
• Large-scale L-BFGS using MapReduceWeizhu Chen, Zhenghao Wang, Jingren Zhou. 1332-1340 [doi]
• Submodular Attribute Selection for Action Recognition in VideoJingjing Zheng, Zhuolin Jiang, Rama Chellappa, P. Jonathon Phillips. 1341-1349 [doi]
• Efficient Structured Matrix Rank MinimizationAdams Wei Yu, Wanli Ma, Yaoliang Yu, Jaime G. Carbonell, Suvrit Sra. 1350-1358 [doi]
• On Integrated Clustering and Outlier DetectionLionel Ott, Linsey Xiaolin Pang, Fabio Tozeto Ramos, Sanjay Chawla. 1359-1367 [doi]
• A Drifting-Games Analysis for Online Learning and Applications to BoostingHaipeng Luo, Robert E. Schapire. 1368-1376 [doi]
• Projecting Markov Random Field Parameters for Fast MixingXianghang Liu, Justin Domke. 1377-1385 [doi]
• Automatic Discovery of Cognitive Skills to Improve the Prediction of Student LearningRobert V. Lindsey, Mohammad Khajah, Michael C. Mozer. 1386-1394 [doi]
• Near-Optimal-Sample Estimators for Spherical Gaussian MixturesAnanda Theertha Suresh, Alon Orlitsky, Jayadev Acharya, Ashkan Jafarpour. 1395-1403 [doi]
• Automated Variational Inference for Gaussian Process ModelsTrung V. Nguyen, Edwin V. Bonilla. 1404-1412 [doi]
• Learning Mixtures of Submodular Functions for Image Collection SummarizationSebastian Tschiatschek, Rishabh K. Iyer, Haochen Wei, Jeff A. Bilmes. 1413-1421 [doi]
• Robust Tensor Decomposition with Gross CorruptionQuanquan Gu, Huan Gui, Jiawei Han. 1422-1430 [doi]
• Provable Tensor Factorization with Missing DataPrateek Jain 0002, Sewoong Oh. 1431-1439 [doi]
• Parallel Successive Convex Approximation for Nonsmooth Nonconvex OptimizationMeisam Razaviyayn, Mingyi Hong, Zhi-Quan Luo, Jong-Shi Pang. 1440-1448 [doi]
• Using Convolutional Neural Networks to Recognize Rhythm Stimuli from Electroencephalography RecordingsSebastian Stober, Daniel J. Cameron, Jessica A. Grahn. 1449-1457 [doi]
• Blossom Tree Graphical ModelsZhe Liu, John D. Lafferty. 1458-1465 [doi]
• Model-based Reinforcement Learning and the Eluder DimensionIan Osband, Benjamin Van Roy. 1466-1474 [doi]
• Minimax-optimal Inference from Partial RankingsBruce E. Hajek, Sewoong Oh, Jiaming Xu. 1475-1483 [doi]
• Spectral Methods for Indian Buffet Process InferenceHsiao-Yu Tung, Alex J. Smola. 1484-1492 [doi]
• On the Statistical Consistency of Plug-in Classifiers for Non-decomposable Performance MeasuresHarikrishna Narasimhan, Rohit Vaish, Shivani Agarwal 0001. 1493-1501 [doi]
• Top Rank Optimization in Linear TimeNan Li, Rong Jin, Zhi-Hua Zhou. 1502-1510 [doi]
• Spectral Methods for Supervised Topic ModelsYining Wang, Jun Zhu. 1511-1519 [doi]
• Graphical Models for Recovering Probabilistic and Causal Queries from Missing DataKarthika Mohan, Judea Pearl. 1520-1528 [doi]
• Sparse PCA with Oracle PropertyQuanquan Gu, Zhaoran Wang, Han Liu. 1529-1537 [doi]
• Unsupervised Transcription of Piano MusicTaylor Berg-Kirkpatrick, Jacob Andreas, Dan Klein. 1538-1546 [doi]
• Decoupled Variational Gaussian InferenceMohammad E. Khan. 1547-1555 [doi]
• Estimation with Norm RegularizationArindam Banerjee, Sheng Chen, Farideh Fazayeli, Vidyashankar Sivakumar. 1556-1564 [doi]
• Decomposing Parameter Estimation ProblemsKhaled S. Refaat, Arthur Choi, Adnan Darwiche. 1565-1573 [doi]
• Stochastic Proximal Gradient Descent with Acceleration TechniquesAtsushi Nitanda. 1574-1582 [doi]
• Learning to Optimize via Information-Directed SamplingDaniel Russo, Benjamin Van Roy. 1583-1591 [doi]
• Covariance shrinkage for autocorrelated dataDaniel Bartz, Klaus-Robert Müller. 1592-1600 [doi]
• Do Convnets Learn Correspondence?Jonathan Long, Ning Zhang, Trevor Darrell. 1601-1609 [doi]
• The Blinded Bandit: Learning with Adaptive FeedbackOfer Dekel, Elad Hazan, Tomer Koren. 1610-1618 [doi]
• Convex Optimization Procedure for Clustering: Theoretical RevisitChangbo Zhu, Huan Xu, Chenlei Leng, Shuicheng Yan. 1619-1627 [doi]
• Sparse Bayesian structure learning with dependent relevance determination priorsAnqi Wu, Mijung Park, Oluwasanmi O. Koyejo, Jonathan W. Pillow. 1628-1636 [doi]
• Weakly-supervised Discovery of Visual Pattern ConfigurationsHyun Oh Song, Yong Jae Lee, Stefanie Jegelka, Trevor Darrell. 1637-1645 [doi]
• SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly Convex Composite ObjectivesAaron Defazio, Francis R. Bach, Simon Lacoste-Julien. 1646-1654 [doi]
• Exclusive Feature Learning on Arbitrary Structures via \ell_{1, 2}-normDeguang Kong, Ryohei Fujimaki, Ji Liu 0002, Feiping Nie, Chris H. Q. Ding. 1655-1663 [doi]
• Time-Data Tradeoffs by Aggressive SmoothingJohn J. Bruer, Joel A. Tropp, Volkan Cevher, Stephen Becker. 1664-1672 [doi]
• Distributed Power-law Graph Computing: Theoretical and Empirical AnalysisCong Xie, Ling Yan, Wu-Jun Li, Zhihua Zhang. 1673-1681 [doi]
• A Multi-World Approach to Question Answering about Real-World Scenes based on Uncertain InputMateusz Malinowski, Mario Fritz. 1682-1690 [doi]
• Efficient Partial Monitoring with Prior InformationHastagiri P. Vanchinathan, Gábor Bartók, Andreas Krause. 1691-1699 [doi]
• Distributed Parameter Estimation in Probabilistic Graphical ModelsYariv Dror Mizrahi, Misha Denil, Nando de Freitas. 1700-1708 [doi]
• Unsupervised Deep Haar Scattering on GraphsXu Chen, Xiuyuan Cheng, Stéphane Mallat. 1709-1717 [doi]
• Online Optimization for Max-Norm RegularizationJie Shen, Huan Xu, Ping Li. 1718-1726 [doi]
• Probabilistic low-rank matrix completion on finite alphabetsJean Lafond, Olga Klopp, Eric Moulines, Joseph Salmon. 1727-1735 [doi]
• Articulated Pose Estimation by a Graphical Model with Image Dependent Pairwise RelationsXianjie Chen, Alan L. Yuille. 1736-1744 [doi]
• Bayesian Inference for Structured Spike and Slab PriorsMichael Riis Andersen, Ole Winther, Lars Kai Hansen. 1745-1753 [doi]
• Bayesian Nonlinear Support Vector Machines and Discriminative Factor ModelingRicardo Henao, Xin Yuan, Lawrence Carin. 1754-1762 [doi]
• Generalized Higher-Order Orthogonal Iteration for Tensor Decomposition and CompletionYuanyuan Liu, Fanhua Shang, Wei Fan, James Cheng, Hong Cheng. 1763-1771 [doi]
• Making Pairwise Binary Graphical Models AttractiveNicholas Ruozzi, Tony Jebara. 1772-1780 [doi]
• Low Rank Approximation Lower Bounds in Row-Update StreamsDavid P. Woodruff. 1781-1789 [doi]
• Deep Convolutional Neural Network for Image DeconvolutionLi Xu, Jimmy S. Ren, Ce Liu, Jiaya Jia. 1790-1798 [doi]
• Joint Training of a Convolutional Network and a Graphical Model for Human Pose EstimationJonathan J. Tompson, Arjun Jain, Yann LeCun, Christoph Bregler. 1799-1807 [doi]
• Learning Generative Models with Visual AttentionYichuan Tang, Nitish Srivastava, Ruslan Salakhutdinov. 1808-1816 [doi]
• Metric Learning for Temporal Sequence AlignmentRémi Lajugie, Damien Garreau, Francis R. Bach, Sylvain Arlot. 1817-1825 [doi]
• Learning Optimal Commitment to Overcome InsecurityAvrim Blum, Nika Haghtalab, Ariel D. Procaccia. 1826-1834 [doi]
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• Low-Rank Time-Frequency SynthesisCédric Févotte, Matthieu Kowalski. 3563-3571 [doi]
• Pre-training of Recurrent Neural Networks via Linear AutoencodersLuca Pasa, Alessandro Sperduti. 3572-3580 [doi]
• Semi-supervised Learning with Deep Generative ModelsDiederik P. Kingma, Shakir Mohamed, Danilo Jimenez Rezende, Max Welling. 3581-3589 [doi]
• Signal Aggregate Constraints in Additive Factorial HMMs, with Application to Energy DisaggregationMingjun Zhong, Nigel H. Goddard, Charles A. Sutton. 3590-3598 [doi]
• Stochastic variational inference for hidden Markov modelsNicholas J. Foti, Jason Xu, Dillon Laird, Emily B. Fox. 3599-3607 [doi]
• A Wild Bootstrap for Degenerate Kernel TestsKacper Chwialkowski, Dino Sejdinovic, Arthur Gretton. 3608-3616 [doi]
• Biclustering Usinig Message PassingLuke O'Connor, Soheil Feizi. 3617-3625 [doi]
• Fast Kernel Learning for Multidimensional Pattern ExtrapolationAndrew Gordon Wilson, Elad Gilboa, John P. Cunningham, Arye Nehorai. 3626-3634 [doi]
• Learning on graphs using Orthonormal Representation is Statistically ConsistentRakesh Shivanna, Chiranjib Bhattacharyya. 3635-3643 [doi]
• Spectral k-Support Norm RegularizationAndrew M. McDonald, Massimiliano Pontil, Dimitris Stamos. 3644-3652 [doi]
• Unsupervised learning of an efficient short-term memory networkPietro Vertechi, Wieland Brendel, Christian K. Machens. 3653-3661 [doi]
• Quantized Estimation of Gaussian Sequence Models in Euclidean BallsYuancheng Zhu, John D. Lafferty. 3662-3670 [doi]
• Learning a Concept Hierarchy from Multi-labeled DocumentsViet-An Nguyen, Jordan L. Boyd-Graber, Philip Resnik, Jonathan Chang. 3671-3679 [doi]
• Variational Gaussian Process State-Space ModelsRoger Frigola, Yutian Chen, Carl E. Rasmussen. 3680-3688 [doi]
• Fast Prediction for Large-Scale Kernel MachinesCho-Jui Hsieh, Si Si, Inderjit S. Dhillon. 3689-3697 [doi]