Table of Contents

• Stochastic Optimization with Importance Sampling for Regularized Loss MinimizationPeilin Zhao, Tong Zhang. 1-9 [doi]
• Approval Voting and Incentives in CrowdsourcingNihar B. Shah, Dengyong Zhou, Yuval Peres. 10-19 [doi]
• A low variance consistent test of relative dependencyWacha Bounliphone, Arthur Gretton, Arthur Tenenhaus, Matthew B. Blaschko. 20-29 [doi]
• An Aligned Subtree Kernel for Weighted GraphsLu Bai, Luca Rossi 0004, Zhihong Zhang, Edwin R. Hancock. 30-39 [doi]
• Spectral Clustering via the Power Method - ProvablyChristos Boutsidis, Prabhanjan Kambadur, Alex Gittens. 40-48 [doi]
• Information Geometry and Minimum Description Length NetworksKe Sun, Jun Wang 0017, Alexandros Kalousis, Stéphane Marchand-Maillet. 49-58 [doi]
• Efficient Training of LDA on a GPU by Mean-for-Mode EstimationJean-Baptiste Tristan, Joseph Tassarotti, Guy L. Steele Jr.. 59-68 [doi]
• Adaptive Stochastic Alternating Direction Method of MultipliersPeilin Zhao, Jinwei Yang, Tong Zhang, Ping Li. 69-77 [doi]
• A Lower Bound for the Optimization of Finite SumsAlekh Agarwal, Léon Bottou. 78-86 [doi]
• Learning Word Representations with Hierarchical Sparse CodingDani Yogatama, Manaal Faruqui, Chris Dyer, Noah A. Smith. 87-96 [doi]
• Learning Transferable Features with Deep Adaptation NetworksMingsheng Long, Yue Cao, Jianmin Wang 0001, Michael Jordan. 97-105 [doi]
• Robust partially observable Markov decision processTakayuki Osogami. 106-115 [doi]
• On the Relationship between Sum-Product Networks and Bayesian NetworksHan Zhao, Mazen Melibari, Pascal Poupart. 116-124 [doi]
• Learning from Corrupted Binary Labels via Class-Probability EstimationAditya Krishna Menon, Brendan van Rooyen, Cheng Soon Ong, Bob Williamson. 125-134 [doi]
• An Explicit Sampling Dependent Spectral Error Bound for Column Subset SelectionTianbao Yang, Lijun Zhang 0005, Rong Jin, Shenghuo Zhu. 135-143 [doi]
• A Stochastic PCA and SVD Algorithm with an Exponential Convergence RateOhad Shamir. 144-152 [doi]
• Attribute Efficient Linear Regression with Distribution-Dependent SamplingDoron Kukliansky, Ohad Shamir. 153-161 [doi]
• Learning Local Invariant Mahalanobis DistancesEthan Fetaya, Shimon Ullman. 162-168 [doi]
• Finding Linear Structure in Large Datasets with Scalable Canonical Correlation AnalysisZhuang Ma, Yichao Lu, Dean P. Foster. 169-178 [doi]
• Abstraction Selection in Model-based Reinforcement LearningNan Jiang, Alex Kulesza, Satinder Singh. 179-188 [doi]
• Surrogate Functions for Maximizing Precision at the TopPurushottam Kar, Harikrishna Narasimhan, Prateek Jain 0002. 189-198 [doi]
• Optimizing Non-decomposable Performance Measures: A Tale of Two ClassesHarikrishna Narasimhan, Purushottam Kar, Prateek Jain 0002. 199-208 [doi]
• Coresets for Nonparametric Estimation - the Case of DP-MeansOlivier Bachem, Mario Lucic, Andreas Krause. 209-217 [doi]
• A Relative Exponential Weighing Algorithm for Adversarial Utility-based Dueling BanditsPratik Gajane, Tanguy Urvoy, Fabrice Clérot. 218-227 [doi]
• Functional Subspace Clustering with Application to Time SeriesMohammad Taha Bahadori, David C. Kale, YingYing Fan, Yan Liu. 228-237 [doi]
• Accelerated Online Low Rank Tensor Learning for Multivariate Spatiotemporal StreamsRose Yu, Dehua Cheng, Yan Liu. 238-247 [doi]
• Atomic Spatial ProcessesSean Jewell, Neil Spencer, Alexandre Bouchard-Côté. 248-256 [doi]
• Classification with Low Rank and Missing DataElad Hazan, Roi Livni, Yishay Mansour. 257-266 [doi]
• Dynamic Sensing: Better Classification under Acquisition ConstraintsOran Richman, Shie Mannor. 267-275 [doi]
• A Modified Orthant-Wise Limited Memory Quasi-Newton Method with Convergence AnalysisPinghua Gong, Jieping Ye. 276-284 [doi]
• Telling cause from effect in deterministic linear dynamical systemsNaji Shajarisales, Dominik Janzing, Bernhard Schölkopf, Michel Besserve. 285-294 [doi]
• High Dimensional Bayesian Optimisation and Bandits via Additive ModelsKirthevasan Kandasamy, Jeff G. Schneider, Barnabás Póczos. 295-304 [doi]
• Theory of Dual-sparse Regularized Randomized ReductionTianbao Yang, Lijun Zhang 0005, Rong Jin, Shenghuo Zhu. 305-314 [doi]
• Generalization error bounds for learning to rank: Does the length of document lists matter?Ambuj Tewari, Sougata Chaudhuri. 315-323 [doi]
• PeakSeg: constrained optimal segmentation and supervised penalty learning for peak detection in count dataToby Hocking, Guillem Rigaill, Guillaume Bourque. 324-332 [doi]
• Mind the duality gap: safer rules for the LassoOlivier Fercoq, Alexandre Gramfort, Joseph Salmon. 333-342 [doi]
• A General Analysis of the Convergence of ADMMRobert Nishihara, Laurent Lessard, Benjamin Recht, Andrew Packard, Michael I. Jordan. 343-352 [doi]
• Stochastic Primal-Dual Coordinate Method for Regularized Empirical Risk MinimizationYuchen Zhang, Xiao Lin. 353-361 [doi]
• DiSCO: Distributed Optimization for Self-Concordant Empirical LossYuchen Zhang, Xiao Lin. 362-370 [doi]
• Spectral MLE: Top-K Rank Aggregation from Pairwise ComparisonsYuxin Chen, Changho Suh. 371-380 [doi]
• Paired-Dual Learning for Fast Training of Latent Variable Hinge-Loss MRFsStephen H. Bach, Bert Huang, Jordan L. Boyd-Graber, Lise Getoor. 381-390 [doi]
• Structural Maxent ModelsCorinna Cortes, Vitaly Kuznetsov, Mehryar Mohri, Umar Syed. 391-399 [doi]
• A Provable Generalized Tensor Spectral Method for Uniform Hypergraph PartitioningDebarghya Ghoshdastidar, Ambedkar Dukkipati. 400-409 [doi]
• The Benefits of Learning with Strongly Convex Approximate InferenceBen London, Bert Huang, Lise Getoor. 410-418 [doi]
• Pushing the Limits of Affine Rank Minimization by Adapting Probabilistic PCABo Xin, David P. Wipf. 419-427 [doi]
• Budget Allocation Problem with Multiple Advertisers: A Game Theoretic ViewTakanori Maehara, Akihiro Yabe, Ken-ichi Kawarabayashi. 428-437 [doi]
• Tracking Approximate Solutions of Parameterized Optimization Problems over Multi-Dimensional (Hyper-)Parameter DomainsKatharina Blechschmidt, Joachim Giesen, Sören Laue. 438-447 [doi]
• Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate ShiftSergey Ioffe, Christian Szegedy. 448-456 [doi]
• Distributed Estimation of Generalized Matrix Rank: Efficient Algorithms and Lower BoundsYuchen Zhang, Martin J. Wainwright, Michael I. Jordan. 457-465 [doi]
• Landmarking Manifolds with Gaussian ProcessesDawen Liang, John Paisley. 466-474 [doi]
• Markov Mixed Membership ModelsAonan Zhang, John Paisley. 475-483 [doi]
• A Unified Framework for Outlier-Robust PCA-like AlgorithmsWenzhuo Yang, Huan Xu. 484-493 [doi]
• Streaming Sparse Principal Component AnalysisWenzhuo Yang, Huan Xu. 494-503 [doi]
• A Divide and Conquer Framework for Distributed Graph ClusteringWenzhuo Yang, Huan Xu. 504-513 [doi]
• How Can Deep Rectifier Networks Achieve Linear Separability and Preserve Distances?Senjian An, Farid Boussaïd, Mohammed Bennamoun. 514-523 [doi]
• Improved Regret Bounds for Undiscounted Continuous Reinforcement LearningK. Lakshmanan, Ronald Ortner, Daniil Ryabko. 524-532 [doi]
• The Fundamental Incompatibility of Scalable Hamiltonian Monte Carlo and Naive Data SubsamplingMichael Betancourt. 533-540 [doi]
• Faster Rates for the Frank-Wolfe Method over Strongly-Convex SetsDan Garber, Elad Hazan. 541-549 [doi]
• Ordered Stick-Breaking Prior for Sequential MCMC Inference of Bayesian Nonparametric ModelsMrinal Kanti Das, Trapit Bansal, Chiranjib Bhattacharyya. 550-559 [doi]
• Online Learning of EigenvectorsDan Garber, Elad Hazan, Tengyu Ma. 560-568 [doi]
• A Unifying Framework of Anytime Sparse Gaussian Process Regression Models with Stochastic Variational Inference for Big DataTrong Nghia Hoang, Quang Minh Hoang, Bryan Kian Hsiang Low. 569-578 [doi]
• Yinyang K-Means: A Drop-In Replacement of the Classic K-Means with Consistent SpeedupYufei Ding, Yue Zhao, Xipeng Shen, Madanlal Musuvathi, Todd Mytkowicz. 579-587 [doi]
• Ordinal Mixed Membership ModelsSeppo Virtanen, Mark Girolami. 588-596 [doi]
• Online Tracking by Learning Discriminative Saliency Map with Convolutional Neural NetworkSeunghoon Hong, Tackgeun You, Suha Kwak, Bohyung Han. 597-606 [doi]
• Fast Kronecker Inference in Gaussian Processes with non-Gaussian LikelihoodsSeth Flaxman, Andrew Gordon Wilson, Daniel Neill, Hannes Nickisch, Alexander J. Smola. 607-616 [doi]
• Statistical and Algorithmic Perspectives on Randomized Sketching for Ordinary Least-SquaresGarvesh Raskutti, Michael Mahoney. 617-625 [doi]
• On TD(0) with function approximation: Concentration bounds and a centered variant with exponential convergenceNathaniel Korda, Prashanth L. A.. 626-634 [doi]
• Learning Parametric-Output HMMs with Two Aliased StatesRoi Weiss, Boaz Nadler. 635-644 [doi]
• Latent Gaussian Processes for Distribution Estimation of Multivariate Categorical DataYarin Gal, Yutian Chen, Zoubin Ghahramani. 645-654 [doi]
• Improving the Gaussian Process Sparse Spectrum Approximation by Representing Uncertainty in Frequency InputsYarin Gal, Richard Turner. 655-664 [doi]
• Ranking from Stochastic Pairwise Preferences: Recovering Condorcet Winners and Tournament Solution Sets at the TopArun Rajkumar, Suprovat Ghoshal, Lek-Heng Lim, Shivani Agarwal 0001. 665-673 [doi]
• Stochastic Dual Coordinate Ascent with Adaptive ProbabilitiesDominik Csiba, Zheng Qu, Peter Richtárik. 674-683 [doi]
• Vector-Space Markov Random Fields via Exponential FamiliesWesley Tansey, Oscar Hernan Madrid Padilla, Arun Sai Suggala, Pradeep Ravikumar. 684-692 [doi]
• JUMP-Means: Small-Variance Asymptotics for Markov Jump ProcessesJonathan H. Huggins, Karthik Narasimhan, Ardavan Saeedi, Vikash K. Mansinghka. 693-701 [doi]
• Low Rank Approximation using Error Correcting Coding MatricesShashanka Ubaru, Arya Mazumdar, Yousef Saad. 702-710 [doi]
• Off-policy Model-based Learning under Unknown Factored DynamicsAssaf Hallak, François Schnitzler, Timothy Arthur Mann, Shie Mannor. 711-719 [doi]
• Log-Euclidean Metric Learning on Symmetric Positive Definite Manifold with Application to Image Set ClassificationZhiwu Huang, Ruiping Wang, Shiguang Shan, Xianqiu Li, Xilin Chen. 720-729 [doi]
• Asymmetric Transfer Learning with Deep Gaussian ProcessesMelih Kandemir. 730-738 [doi]
• Towards a Lower Sample Complexity for Robust One-bit Compressed SensingRongda Zhu, Quanquan Gu. 739-747 [doi]
• BilBOWA: Fast Bilingual Distributed Representations without Word AlignmentsStephan Gouws, Yoshua Bengio, Greg Corrado. 748-756 [doi]
• Multi-view Sparse Co-clustering via Proximal Alternating Linearized MinimizationJiangwen Sun, Jin Lu, Tingyang Xu, Jinbo Bi. 757-766 [doi]
• Cascading Bandits: Learning to Rank in the Cascade ModelBranislav Kveton, Csaba Szepesvári, Zheng Wen, Azin Ashkan. 767-776 [doi]
• Latent Topic Networks: A Versatile Probabilistic Programming Framework for Topic ModelsJames R. Foulds, Shachi Kumar, Lise Getoor. 777-786 [doi]
• Random Coordinate Descent Methods for Minimizing Decomposable Submodular FunctionsAlina Ene, Huy L. Nguyen. 787-795 [doi]
• Alpha-Beta Divergences Discover Micro and Macro Structures in DataKarthik S. Narayan, Ali Punjani, Pieter Abbeel. 796-804 [doi]
• Fictitious Self-Play in Extensive-Form GamesJohannes Heinrich, Marc Lanctot, David Silver. 805-813 [doi]
• Counterfactual Risk Minimization: Learning from Logged Bandit FeedbackAdith Swaminathan, Thorsten Joachims. 814-823 [doi]
• The Hedge Algorithm on a ContinuumWalid Krichene, Maximilian Balandat, Claire J. Tomlin, Alexandre M. Bayen. 824-832 [doi]
• A Linear Dynamical System Model for TextDavid Belanger, Sham M. Kakade. 833-842 [doi]
• Unsupervised Learning of Video Representations using LSTMsNitish Srivastava, Elman Mansimov, Ruslan Salakhutdinov. 843-852 [doi]
• Message Passing for Collective Graphical ModelsTao Sun, Daniel Sheldon, Akshat Kumar. 853-861 [doi]
• DP-space: Bayesian Nonparametric Subspace Clustering with Small-variance AsymptoticsYining Wang, Jun Zhu. 862-870 [doi]
• HawkesTopic: A Joint Model for Network Inference and Topic Modeling from Text-Based CascadesXinran He, Theodoros Rekatsinas, James R. Foulds, Lise Getoor, Yan Liu. 871-880 [doi]
• MADE: Masked Autoencoder for Distribution EstimationMathieu Germain, Karol Gregor, Iain Murray, Hugo Larochelle. 881-889 [doi]
• An Online Learning Algorithm for Bilinear ModelsYuanbin Wu, Shiliang Sun. 890-898 [doi]
• Adaptive Belief PropagationGeorgios Papachristoudis, John W. Fisher. 899-907 [doi]
• Large-scale log-determinant computation through stochastic Chebyshev expansionsInsu Han, Dmitry Malioutov, Jinwoo Shin. 908-917 [doi]
• Differentially Private Bayesian OptimizationMatt J. Kusner, Jacob R. Gardner, Roman Garnett, Kilian Q. Weinberger. 918-927 [doi]
• A Nearly-Linear Time Framework for Graph-Structured SparsityChinmay Hegde, Piotr Indyk, Ludwig Schmidt. 928-937 [doi]
• Support Matrix MachinesLuo Luo, Yubo Xie, Zhihua Zhang, Wu-Jun Li. 938-947 [doi]
• Rademacher Observations, Private Data, and BoostingRichard Nock, Giorgio Patrini, Arik Friedman. 948-956 [doi]
• From Word Embeddings To Document DistancesMatt J. Kusner, Yu Sun, Nicholas I. Kolkin, Kilian Q. Weinberger. 957-966 [doi]
• Bayesian and Empirical Bayesian ForestsTaddy Matthew, Chun-Sheng Chen, Jun Yu, Mitch Wyle. 967-976 [doi]
• Inferring Graphs from Cascades: A Sparse Recovery FrameworkJean Pouget-Abadie, Thibaut Horel. 977-986 [doi]
• Distributed Box-Constrained Quadratic Optimization for Dual Linear SVMChing-Pei Lee, Dan Roth. 987-996 [doi]
• Safe Exploration for Optimization with Gaussian ProcessesYanan Sui, Alkis Gotovos, Joel W. Burdick, Andreas Krause. 997-1005 [doi]
• The Ladder: A Reliable Leaderboard for Machine Learning CompetitionsAvrim Blum, Moritz Hardt. 1006-1014 [doi]
• Enabling scalable stochastic gradient-based inference for Gaussian processes by employing the Unbiased LInear System SolvEr (ULISSE)Maurizio Filippone, Raphael Engler. 1015-1024 [doi]
• Finding Galaxies in the Shadows of Quasars with Gaussian ProcessesRoman Garnett, Shirley Ho, Jeff Schneider. 1025-1033 [doi]
• Following the Perturbed Leader for Online Structured LearningAlon Cohen, Tamir Hazan. 1034-1042 [doi]
• Reified Context ModelsJacob Steinhardt, Percy Liang. 1043-1052 [doi]
• Large-Scale Markov Decision Problems with KL Control Cost and its Application to CrowdsourcingYasin Abbasi-Yadkori, Peter L. Bartlett, Xi Chen, Alan Malek. 1053-1062 [doi]
• Learning Fast-Mixing Models for Structured PredictionJacob Steinhardt, Percy Liang. 1063-1072 [doi]
• A Probabilistic Model for Dirty Multi-task Feature SelectionDaniel Hernández-Lobato, José Miguel Hernández-Lobato, Zoubin Ghahramani. 1073-1082 [doi]
• On Deep Multi-View Representation LearningWeiran Wang, Raman Arora, Karen Livescu, Jeff A. Bilmes. 1083-1092 [doi]
• Learning Program Embeddings to Propagate Feedback on Student CodeChris Piech, Jonathan Huang, Andy Nguyen, Mike Phulsuksombati, Mehran Sahami, Leonidas J. Guibas. 1093-1102 [doi]
• Safe Subspace Screening for Nuclear Norm Regularized Least Squares ProblemsQiang Zhou, Qi Zhao. 1103-1112 [doi]
• Efficient Learning in Large-Scale Combinatorial Semi-BanditsZheng Wen, Branislav Kveton, Azin Ashkan. 1113-1122 [doi]
• Swept Approximate Message Passing for Sparse EstimationAndre Manoel, Florent Krzakala, Eric W. Tramel, Lenka Zdeborová. 1123-1132 [doi]
• Simple regret for infinitely many armed banditsAlexandra Carpentier, Michal Valko. 1133-1141 [doi]
• Exponential Integration for Hamiltonian Monte CarloWei-Lun Chao, Justin Solomon, Dominik Michels, Fei Sha. 1142-1151 [doi]
• Optimal Regret Analysis of Thompson Sampling in Stochastic Multi-armed Bandit Problem with Multiple PlaysJunpei Komiyama, Junya Honda, Hiroshi Nakagawa. 1152-1161 [doi]
• Faster cover treesMike Izbicki, Christian R. Shelton. 1162-1170 [doi]
• Blitz: A Principled Meta-Algorithm for Scaling Sparse OptimizationTyler Johnson, Carlos Guestrin. 1171-1179 [doi]
• Unsupervised Domain Adaptation by BackpropagationYaroslav Ganin, Victor S. Lempitsky. 1180-1189 [doi]
• Non-Linear Cross-Domain Collaborative Filtering via Hyper-Structure TransferYan-Fu Liu, Cheng-Yu Hsu, Shan-Hung Wu. 1190-1198 [doi]
• Manifold-valued Dirichlet ProcessesHyunwoo J. Kim, Jia Xu, Baba C. Vemuri, Vikas Singh. 1199-1208 [doi]
• Multi-Task Learning for Subspace SegmentationYu Wang, David Wipf, Qing Ling, Wei Chen, Ian J. Wassell. 1209-1217 [doi]
• Markov Chain Monte Carlo and Variational Inference: Bridging the GapTim Salimans, Diederik P. Kingma, Max Welling. 1218-1226 [doi]
• Scalable Model Selection for Large-Scale Factorial Relational ModelsChunchen Liu, Lu Feng, Ryohei Fujimaki, Yusuke Muraoka. 1227-1235 [doi]
• The Power of Randomization: Distributed Submodular Maximization on Massive DatasetsRafael Barbosa, Alina Ene, Huy L. Nguyen, Justin Ward. 1236-1244 [doi]
• Dealing with small data: On the generalization of context treesRalf Eggeling, Mikko Koivisto, Ivo Grosse. 1245-1253 [doi]
• Non-Gaussian Discriminative Factor Models via the Max-Margin Rank-LikelihoodXin Yuan, Ricardo Henao, Ephraim Tsalik, Raymond Langley, Lawrence Carin. 1254-1263 [doi]
• A Bayesian nonparametric procedure for comparing algorithmsAlessio Benavoli, Giorgio Corani, Francesca Mangili, Marco Zaffalon. 1264-1272 [doi]
• Convergence rate of Bayesian tensor estimator and its minimax optimalityTaiji Suzuki. 1273-1282 [doi]
• On Identifying Good Options under Combinatorially Structured Feedback in Finite Noisy EnvironmentsYifan Wu, András György, Csaba Szepesvári. 1283-1291 [doi]
• Nested Sequential Monte Carlo MethodsChristian Andersson Naesseth, Fredrik Lindsten, Thomas B. Schön. 1292-1301 [doi]
• Sparse Variational Inference for Generalized GP ModelsRishit Sheth, Yuyang Wang, Roni Khardon. 1302-1311 [doi]
• Universal Value Function ApproximatorsTom Schaul, Daniel Horgan, Karol Gregor, David Silver. 1312-1320 [doi]
• Approximate Dynamic Programming for Two-Player Zero-Sum Markov GamesJulien Perolat, Bruno Scherrer, Bilal Piot, Olivier Pietquin. 1321-1329 [doi]
• On Greedy Maximization of EntropyDravyansh Sharma, Ashish Kapoor, Amit Deshpande. 1330-1338 [doi]
• Metadata Dependent Mondrian ProcessesYi Wang, Bin Li, Yang Wang 0002, Fang Chen. 1339-1347 [doi]
• Complex Event Detection using Semantic Saliency and Nearly-Isotonic SVMXiaojun Chang, Yi Yang, Eric P. Xing, Yaoliang Yu. 1348-1357 [doi]
• Rebuilding Factorized Information Criterion: Asymptotically Accurate Marginal LikelihoodKohei Hayashi, Shin-ichi Maeda, Ryohei Fujimaki. 1358-1366 [doi]
• Double Nyström Method: An Efficient and Accurate Nyström Scheme for Large-Scale Data SetsWoosang Lim, Minhwan Kim, Haesun Park, Kyomin Jung. 1367-1375 [doi]
• The Composition Theorem for Differential PrivacyPeter Kairouz, Sewoong Oh, Pramod Viswanath. 1376-1385 [doi]
• Convex Formulation for Learning from Positive and Unlabeled DataMarthinus Christoffel du Plessis, Gang Niu, Masashi Sugiyama. 1386-1394 [doi]
• Threshold Influence Model for Allocating Advertising BudgetsAtsushi Miyauchi, Yuni Iwamasa, Takuro Fukunaga, Naonori Kakimura. 1395-1404 [doi]
• Strongly Adaptive Online LearningAmit Daniely, Alon Gonen, Shai Shalev-Shwartz. 1405-1411 [doi]
• CUR Algorithm for Partially Observed MatricesMiao Xu, Rong Jin, Zhi-Hua Zhou. 1412-1421 [doi]
• A Deterministic Analysis of Noisy Sparse Subspace Clustering for Dimensionality-reduced DataYining Wang, Yu-Xiang Wang, Aarti Singh. 1422-1431 [doi]
• MRA-based Statistical Learning from Incomplete RankingsEric Sibony, Stéphan Clémençon, Jérémie Jakubowicz. 1432-1441 [doi]
• Risk and Regret of Hierarchical Bayesian LearnersJonathan Huggins, Josh Tenenbaum. 1442-1451 [doi]
• Towards a Learning Theory of Cause-Effect InferenceDavid Lopez-Paz, Krikamol Muandet, Bernhard Schölkopf, Iliya Tolstikhin. 1452-1461 [doi]
• DRAW: A Recurrent Neural Network For Image GenerationKarol Gregor, Ivo Danihelka, Alex Graves, Danilo Jimenez Rezende, Daan Wierstra. 1462-1471 [doi]
• Multiview Triplet Embedding: Learning Attributes in Multiple MapsEhsan Amid, Antti Ukkonen. 1472-1480 [doi]
• Distributed Gaussian ProcessesMarc Peter Deisenroth, Jun Wei Ng. 1481-1490 [doi]
• Guaranteed Tensor Decomposition: A Moment ApproachGongguo Tang, Parikshit Shah. 1491-1500 [doi]
• \(\ell_{1, p}\)-Norm Regularization: Error Bounds and Convergence Rate Analysis of First-Order MethodsZirui Zhou, Qi Zhang, Anthony Man-Cho So. 1501-1510 [doi]
• Consistent estimation of dynamic and multi-layer block modelsQiuyi Han, Kevin S. Xu, Edoardo Airoldi. 1511-1520 [doi]
• On the Rate of Convergence and Error Bounds for LSTD(\(\lambda\))Manel Tagorti, Bruno Scherrer. 1521-1529 [doi]
• Variational Inference with Normalizing FlowsDanilo Jimenez Rezende, Shakir Mohamed. 1530-1538 [doi]
• Controversy in mechanistic modelling with Gaussian processesBenn Macdonald, Catherine F. Higham, Dirk Husmeier. 1539-1547 [doi]
• Convex Learning of Multiple Tasks and their StructureCarlo Ciliberto, Youssef Mroueh, Tomaso A. Poggio, Lorenzo Rosasco. 1548-1557 [doi]
• K-hyperplane Hinge-Minimax ClassifierMargarita Osadchy, Tamir Hazan, Daniel Keren. 1558-1566 [doi]
• Non-Stationary Approximate Modified Policy IterationBoris Lesner, Bruno Scherrer. 1567-1575 [doi]
• Entropy evaluation based on confidence intervals of frequency estimates : Application to the learning of decision treesMathieu Serrurier, Henri Prade. 1576-1584 [doi]
• Geometric Conditions for Subspace-Sparse RecoveryChong You, René Vidal. 1585-1593 [doi]
• An Empirical Study of Stochastic Variational Inference Algorithms for the Beta Bernoulli ProcessAmar Shah, David A. Knowles, Zoubin Ghahramani. 1594-1603 [doi]
• Long Short-Term Memory Over Recursive StructuresXiao-Dan Zhu, Parinaz Sobhani, Hongyu Guo. 1604-1612 [doi]
• Weight Uncertainty in Neural NetworkCharles Blundell, Julien Cornebise, Koray Kavukcuoglu, Daan Wierstra. 1613-1622 [doi]
• Learning Submodular Losses with the Lovasz HingeJiaqian Yu, Matthew B. Blaschko. 1623-1631 [doi]
• Coordinate Descent Converges Faster with the Gauss-Southwell Rule Than Random SelectionJulie Nutini, Mark W. Schmidt, Issam H. Laradji, Michael P. Friedlander, Hoyt A. Koepke. 1632-1641 [doi]
• Hashing for Distributed DataCong Leng, Jiaxiang Wu, Jian Cheng, Xi Zhang, Hanqing Lu. 1642-1650 [doi]
• Large-scale Distributed Dependent Nonparametric TreesZhiting Hu, Qirong Ho, Avinava Dubey, Eric P. Xing. 1651-1659 [doi]
• Qualitative Multi-Armed Bandits: A Quantile-Based ApproachBalázs Szörényi, Róbert Busa-Fekete, Paul Weng, Eyke Hüllermeier. 1660-1668 [doi]
• Deep Edge-Aware FiltersLi Xu, Jimmy Ren, Qiong Yan, Renjie Liao, Jiaya Jia. 1669-1678 [doi]
• A Convex Optimization Framework for Bi-ClusteringShiau Hong Lim, Yudong Chen, Huan Xu. 1679-1688 [doi]
• Is Feature Selection Secure against Training Data Poisoning?Huang Xiao, Battista Biggio, Gavin Brown, Giorgio Fumera, Claudia Eckert, Fabio Roli. 1689-1698 [doi]
• Predictive Entropy Search for Bayesian Optimization with Unknown ConstraintsJosé Miguel Hernández-Lobato, Michael A. Gelbart, Matthew W. Hoffman, Ryan P. Adams, Zoubin Ghahramani. 1699-1707 [doi]
• A Theoretical Analysis of Metric Hypothesis Transfer LearningMichaël Perrot, Amaury Habrard. 1708-1717 [doi]
• Generative Moment Matching NetworksYujia Li, Kevin Swersky, Richard S. Zemel. 1718-1727 [doi]
• Stay on path: PCA along graph pathsMegasthenis Asteris, Anastasios Kyrillidis, Alexandros G. Dimakis, Han-Gyol Yi, Bharath Chandrasekaran. 1728-1736 [doi]
• Deep Learning with Limited Numerical PrecisionSuyog Gupta, Ankur Agrawal, Kailash Gopalakrishnan, Pritish Narayanan. 1737-1746 [doi]
• Safe Screening for Multi-Task Feature Learning with Multiple Data MatricesJie Wang, Jieping Ye. 1747-1756 [doi]
• Harmonic Exponential Families on ManifoldsTaco Cohen, Max Welling. 1757-1765 [doi]
• Training Deep Convolutional Neural Networks to Play GoChristopher Clark, Amos J. Storkey. 1766-1774 [doi]
• Kernel Interpolation for Scalable Structured Gaussian Processes (KISS-GP)Andrew Gordon Wilson, Hannes Nickisch. 1775-1784 [doi]
• Learning Deep Structured ModelsLiang-Chieh Chen, Alexander G. Schwing, Alan L. Yuille, Raquel Urtasun. 1785-1794 [doi]
• Community Detection Using Time-Dependent Personalized PageRankHaim Avron, Lior Horesh. 1795-1803 [doi]
• Scalable Variational Inference in Log-supermodular ModelsJosip Djolonga, Andreas Krause. 1804-1813 [doi]
• Variational Inference for Gaussian Process Modulated Poisson ProcessesChris M. Lloyd, Tom Gunter, Michael A. Osborne, Stephen J. Roberts. 1814-1822 [doi]
• Scalable Deep Poisson Factor Analysis for Topic ModelingZhe Gan, Changyou Chen, Ricardo Henao, David E. Carlson, Lawrence Carin. 1823-1832 [doi]
• Hidden Markov Anomaly DetectionNico Görnitz, Mikio L. Braun, Marius Kloft. 1833-1842 [doi]
• Robust Estimation of Transition Matrices in High Dimensional Heavy-tailed Vector Autoregressive ProcessesHuitong Qiu, Sheng Xu, Fang Han, Han Liu, Brian Caffo. 1843-1851 [doi]
• Convex Calibrated Surrogates for Hierarchical ClassificationHarish G. Ramaswamy, Ambuj Tewari, Shivani Agarwal 0001. 1852-1860 [doi]
• Probabilistic Backpropagation for Scalable Learning of Bayesian Neural NetworksJosé Miguel Hernández-Lobato, Ryan Adams. 1861-1869 [doi]
• Active Nearest Neighbors in Changing EnvironmentsChristopher Berlind, Ruth Urner. 1870-1879 [doi]
• Bipartite Edge Prediction via Transductive Learning over Product GraphsHanxiao Liu, Yiming Yang. 1880-1888 [doi]
• Trust Region Policy OptimizationJohn Schulman, Sergey Levine, Pieter Abbeel, Michael I. Jordan, Philipp Moritz. 1889-1897 [doi]
• Discovering Temporal Causal Relations from Subsampled DataMingming Gong, Kun Zhang, Bernhard Schölkopf, Dacheng Tao, Philipp Geiger. 1898-1906 [doi]
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