Abstract is missing.
- Double or Nothing: Multiplicative Incentive Mechanisms for CrowdsourcingNihar Bhadresh Shah, Denny Zhou. 1-9 [doi]
- Learning with Symmetric Label Noise: The Importance of Being UnhingedBrendan van Rooyen, Aditya Krishna Menon, Robert C. Williamson. 10-18 [doi]
- Algorithmic Stability and Uniform GeneralizationIbrahim M. Alabdulmohsin. 19-27 [doi]
- Adaptive Low-Complexity Sequential Inference for Dirichlet Process Mixture ModelsTheodoros Tsiligkaridis, Keith W. Forsythe. 28-36 [doi]
- Covariance-Controlled Adaptive Langevin Thermostat for Large-Scale Bayesian SamplingXiaocheng Shang, Zhanxing Zhu, Benedict J. Leimkuhler, Amos J. Storkey. 37-45 [doi]
- Robust Portfolio OptimizationHuitong Qiu, Fang Han, Han Liu, Brian Caffo. 46-54 [doi]
- Logarithmic Time Online Multiclass predictionAnna Choromanska, John Langford. 55-63 [doi]
- Planar Ultrametrics for Image SegmentationJulian Yarkony, Charless C. Fowlkes. 64-72 [doi]
- Expressing an Image Stream with a Sequence of Natural SentencesCesc C. Park, Gunhee Kim. 73-81 [doi]
- Parallel Correlation Clustering on Big GraphsXinghao Pan, Dimitris S. Papailiopoulos, Samet Oymak, Benjamin Recht, Kannan Ramchandran, Michael I. Jordan. 82-90 [doi]
- Faster R-CNN: Towards Real-Time Object Detection with Region Proposal NetworksShaoqing Ren, Kaiming He, Ross B. Girshick, Jian Sun 0001. 91-99 [doi]
- Space-Time Local EmbeddingsKe Sun, Jun Wang 0017, Alexandros Kalousis, Stéphane Marchand-Maillet. 100-108 [doi]
- A Convergent Gradient Descent Algorithm for Rank Minimization and Semidefinite Programming from Random Linear MeasurementsQinqing Zheng, John D. Lafferty. 109-117 [doi]
- Smooth Interactive Submodular Set CoverBryan D. He, Yisong Yue. 118-126 [doi]
- Galileo: Perceiving Physical Object Properties by Integrating a Physics Engine with Deep LearningJiajun Wu, Ilker Yildirim, Joseph J. Lim, Bill Freeman, Joshua B. Tenenbaum. 127-135 [doi]
- On the Pseudo-Dimension of Nearly Optimal AuctionsJamie Morgenstern, Tim Roughgarden. 136-144 [doi]
- Unlocking neural population non-stationarities using hierarchical dynamics modelsMijung Park, Gergo Bohner, Jakob H. Macke. 145-153 [doi]
- Bayesian Manifold Learning: The Locally Linear Latent Variable Model (LL-LVM)Mijung Park, Wittawat Jitkrittum, Ahmad Qamar, Zoltán Szabó 0001, Lars Buesing, Maneesh Sahani. 154-162 [doi]
- Color Constancy by Learning to Predict Chromaticity from LuminanceAyan Chakrabarti. 163-171 [doi]
- Fast and Accurate Inference of Plackett-Luce ModelsLucas Maystre, Matthias Grossglauser. 172-180 [doi]
- Probabilistic Line Searches for Stochastic OptimizationMaren Mahsereci, Philipp Hennig. 181-189 [doi]
- Inferring Algorithmic Patterns with Stack-Augmented Recurrent NetsArmand Joulin, Tomas Mikolov. 190-198 [doi]
- Where are they looking?Adrià Recasens, Aditya Khosla, Carl Vondrick, Antonio Torralba. 199-207 [doi]
- The Pareto Regret Frontier for BanditsTor Lattimore. 208-216 [doi]
- On the Limitation of Spectral Methods: From the Gaussian Hidden Clique Problem to Rank-One Perturbations of Gaussian TensorsAndrea Montanari, Daniel Reichman, Ofer Zeitouni. 217-225 [doi]
- Measuring Sample Quality with Stein's MethodJackson Gorham, Lester W. Mackey. 226-234 [doi]
- Bidirectional Recurrent Convolutional Networks for Multi-Frame Super-ResolutionYan Huang, Wei Wang 0025, Liang Wang 0001. 235-243 [doi]
- Bounding errors of Expectation-PropagationGuillaume P. Dehaene, Simon Barthelmé. 244-252 [doi]
- A fast, universal algorithm to learn parametric nonlinear embeddingsMiguel Á. Carreira-Perpiñán, Max Vladymyrov. 253-261 [doi]
- Texture Synthesis Using Convolutional Neural NetworksLeon A. Gatys, Alexander S. Ecker, Matthias Bethge. 262-270 [doi]
- Extending Gossip Algorithms to Distributed Estimation of U-statisticsIgor Colin, Aurélien Bellet, Joseph Salmon, Stéphan Clémençon. 271-279 [doi]
- Streaming, Distributed Variational Inference for Bayesian NonparametricsTrevor Campbell, Julian Straub, John W. Fisher III, Jonathan P. How. 280-288 [doi]
- Learning visual biases from human imaginationCarl Vondrick, Hamed Pirsiavash, Aude Oliva, Antonio Torralba. 289-297 [doi]
- Smooth and Strong: MAP Inference with Linear ConvergenceOfer Meshi, Mehrdad Mahdavi, Alex Schwing. 298-306 [doi]
- Copeland Dueling BanditsMasrour Zoghi, Zohar S. Karnin, Shimon Whiteson, Maarten de Rijke. 307-315 [doi]
- Optimal Ridge Detection using Coverage RiskYen-Chi Chen, Christopher R. Genovese, Shirley Ho, Larry A. Wasserman. 316-324 [doi]
- Top-k Multiclass SVMMaksim Lapin, Matthias Hein 0001, Bernt Schiele. 325-333 [doi]
- Policy Evaluation Using the Ω-ReturnPhilip S. Thomas, Scott Niekum, Georgios Theocharous, George Konidaris. 334-342 [doi]
- Orthogonal NMF through Subspace ExplorationMegasthenis Asteris, Dimitris S. Papailiopoulos, Alexandros G. Dimakis. 343-351 [doi]
- Stochastic Online Greedy Learning with Semi-bandit FeedbacksTian Lin, Jian Li, Wei Chen. 352-360 [doi]
- Deeply Learning the Messages in Message Passing InferenceGuosheng Lin, Chunhua Shen, Ian D. Reid 0001, Anton van den Hengel. 361-369 [doi]
- Synaptic Sampling: A Bayesian Approach to Neural Network Plasticity and RewiringDavid Kappel, Stefan Habenschuss, Robert A. Legenstein, Wolfgang Maass. 370-378 [doi]
- Accelerated Proximal Gradient Methods for Nonconvex ProgrammingHuan Li, Zhouchen Lin. 379-387 [doi]
- Approximating Sparse PCA from Incomplete DataAbhisek Kundu, Petros Drineas, Malik Magdon-Ismail. 388-396 [doi]
- Nonparametric von Mises Estimators for Entropies, Divergences and Mutual InformationsKirthevasan Kandasamy, Akshay Krishnamurthy, Barnabás Póczos, Larry A. Wasserman, James M. Robins. 397-405 [doi]
- Column Selection via Adaptive SamplingSaurabh Paul, Malik Magdon-Ismail, Petros Drineas. 406-414 [doi]
- HONOR: Hybrid Optimization for NOn-convex Regularized problemsPinghua Gong, Jieping Ye. 415-423 [doi]
- 3D Object Proposals for Accurate Object Class DetectionXiaozhi Chen, Kaustav Kundu, Yukun Zhu, Andrew G. Berneshawi, Huimin Ma, Sanja Fidler, Raquel Urtasun. 424-432 [doi]
- Algorithms with Logarithmic or Sublinear Regret for Constrained Contextual BanditsHuasen Wu, R. Srikant, Xin Liu, Chong Jiang. 433-441 [doi]
- Tensorizing Neural NetworksAlexander Novikov, Dmitry Podoprikhin, Anton Osokin, Dmitry P. Vetrov. 442-450 [doi]
- Parallelizing MCMC with Random Partition TreesXiangyu Wang, Fangjian Guo, Katherine A. Heller, David B. Dunson. 451-459 [doi]
- A Reduced-Dimension fMRI Shared Response ModelPo-Hsuan Chen, Janice Chen, Yaara Yeshurun, Uri Hasson, James V. Haxby, Peter J. Ramadge. 460-468 [doi]
- Spectral Learning of Large Structured HMMs for Comparative EpigenomicsChicheng Zhang, Jimin Song, Kamalika Chaudhuri, Kevin C. Chen. 469-477 [doi]
- Individual Planning in Infinite-Horizon Multiagent Settings: Inference, Structure and ScalabilityXia Qu, Prashant Doshi. 478-486 [doi]
- Estimating Mixture Models via Mixtures of PolynomialsSida I. Wang, Arun Tejasvi Chaganty, Percy Liang. 487-495 [doi]
- On the Global Linear Convergence of Frank-Wolfe Optimization VariantsSimon Lacoste-Julien, Martin Jaggi. 496-504 [doi]
- Deep Knowledge TracingChris Piech, Jonathan Bassen, Jonathan Huang, Surya Ganguli, Mehran Sahami, Leonidas J. Guibas, Jascha Sohl-Dickstein. 505-513 [doi]
- Rethinking LDA: Moment Matching for Discrete ICAAnastasia Podosinnikova, Francis R. Bach, Simon Lacoste-Julien. 514-522 [doi]
- Efficient Compressive Phase Retrieval with Constrained Sensing VectorsSohail Bahmani, Justin K. Romberg. 523-531 [doi]
- Barrier Frank-Wolfe for Marginal InferenceRahul G. Krishnan, Simon Lacoste-Julien, David Sontag. 532-540 [doi]
- Learning Theory and Algorithms for Forecasting Non-stationary Time SeriesVitaly Kuznetsov, Mehryar Mohri. 541-549 [doi]
- Compressive spectral embedding: sidestepping the SVDDinesh Ramasamy, Upamanyu Madhow. 550-558 [doi]
- A Nonconvex Optimization Framework for Low Rank Matrix EstimationTuo Zhao, Zhaoran Wang, Han Liu. 559-567 [doi]
- Automatic Variational Inference in StanAlp Kucukelbir, Rajesh Ranganath, Andrew Gelman, David M. Blei. 568-576 [doi]
- Attention-Based Models for Speech RecognitionJan Chorowski, Dzmitry Bahdanau, Dmitriy Serdyuk, KyungHyun Cho, Yoshua Bengio. 577-585 [doi]
- Closed-form Estimators for High-dimensional Generalized Linear ModelsEunho Yang, Aurelie C. Lozano, Pradeep Ravikumar. 586-594 [doi]
- Online F-Measure OptimizationRóbert Busa-Fekete, Balázs Szörényi, Krzysztof Dembczynski, Eyke Hüllermeier. 595-603 [doi]
- Online Rank Elicitation for Plackett-Luce: A Dueling Bandits ApproachBalázs Szörényi, Róbert Busa-Fekete, Adil Paul, Eyke Hüllermeier. 604-612 [doi]
- M-Best-Diverse Labelings for Submodular Energies and BeyondAlexander Kirillov, Dmytro Shlezinger, Dmitry P. Vetrov, Carsten Rother, Bogdan Savchynskyy. 613-621 [doi]
- Tractable Bayesian Network Structure Learning with Bounded Vertex Cover NumberJanne H. Korhonen, Pekka Parviainen. 622-630 [doi]
- Learning Large-Scale Poisson DAG Models based on OverDispersion ScoringGunwoong Park, Garvesh Raskutti. 631-639 [doi]
- Training Restricted Boltzmann Machine via the Thouless-Anderson-Palmer free energyMarylou Gabrié, Eric W. Tramel, Florent Krzakala. 640-648 [doi]
- Character-level Convolutional Networks for Text ClassificationXiang Zhang, Junbo Zhao, Yann LeCun. 649-657 [doi]
- Robust Feature-Sample Linear Discriminant Analysis for Brain Disorders DiagnosisEhsan Adeli Mosabbeb, Kim-Han Thung, Le An, Feng Shi, Dinggang Shen. 658-666 [doi]
- Black-box optimization of noisy functions with unknown smoothnessJean-Bastien grill, Michal Valko, Rémi Munos. 667-675 [doi]
- Recovering Communities in the General Stochastic Block Model Without Knowing the ParametersEmmanuel Abbe, Colin Sandon. 676-684 [doi]
- Deep learning with Elastic Averaging SGDSixin Zhang, Anna Choromanska, Yann LeCun. 685-693 [doi]
- Monotone k-Submodular Function Maximization with Size ConstraintsNaoto Ohsaka, Yuichi Yoshida. 694-702 [doi]
- Active Learning from Weak and Strong LabelersChicheng Zhang, Kamalika Chaudhuri. 703-711 [doi]
- On the Optimality of Classifier Chain for Multi-label ClassificationWeiwei Liu, Ivor W. Tsang. 712-720 [doi]
- Robust Regression via Hard ThresholdingKush Bhatia, Prateek Jain 0002, Purushottam Kar. 721-729 [doi]
- Sparse Local Embeddings for Extreme Multi-label ClassificationKush Bhatia, Himanshu Jain, Purushottam Kar, Manik Varma, Prateek Jain 0002. 730-738 [doi]
- Solving Random Quadratic Systems of Equations Is Nearly as Easy as Solving Linear SystemsYuxin Chen, Emmanuel J. Candès. 739-747 [doi]
- A Framework for Individualizing Predictions of Disease Trajectories by Exploiting Multi-Resolution StructurePeter Schulam, Suchi Saria. 748-756 [doi]
- Subspace Clustering with Irrelevant Features via Robust Dantzig SelectorChao Qu, Huan Xu. 757-765 [doi]
- Sparse PCA via Bipartite MatchingsMegasthenis Asteris, Dimitris S. Papailiopoulos, Anastasios T. Kyrillidis, Alexandros G. Dimakis. 766-774 [doi]
- Fast Randomized Kernel Ridge Regression with Statistical GuaranteesAhmed El Alaoui, Michael W. Mahoney. 775-783 [doi]
- Online Learning for Adversaries with Memory: Price of Past MistakesOren Anava, Elad Hazan, Shie Mannor. 784-792 [doi]
- Convolutional spike-triggered covariance analysis for neural subunit modelsAnqi Wu, Il Memming Park, Jonathan W. Pillow. 793-801 [doi]
- Convolutional LSTM Network: A Machine Learning Approach for Precipitation NowcastingXingjian Shi, Zhourong Chen, Hao Wang, Dit-Yan Yeung, Wai-Kin Wong, Wang-chun Woo. 802-810 [doi]
- GAP Safe screening rules for sparse multi-task and multi-class modelsEugène Ndiaye, Olivier Fercoq, Alexandre Gramfort, Joseph Salmon. 811-819 [doi]
- Empirical Localization of Homogeneous Divergences on Discrete Sample SpacesTakashi Takenouchi, Takafumi Kanamori. 820-828 [doi]
- Statistical Model Criticism using Kernel Two Sample TestsJames Robert Lloyd, Zoubin Ghahramani. 829-837 [doi]
- Precision-Recall-Gain Curves: PR Analysis Done RightPeter A. Flach, Meelis Kull. 838-846 [doi]
- A Generalization of Submodular Cover via the Diminishing Return Property on the Integer LatticeTasuku Soma, Yuichi Yoshida. 847-855 [doi]
- Bidirectional Recurrent Neural Networks as Generative ModelsMathias Berglund, Tapani Raiko, Mikko Honkala, Leo Kärkkäinen, Akos Vetek, Juha Karhunen. 856-864 [doi]
- Quartz: Randomized Dual Coordinate Ascent with Arbitrary SamplingZheng Qu, Peter Richtárik, Tong Zhang 0001. 865-873 [doi]
- Maximum Likelihood Learning With Arbitrary Treewidth via Fast-Mixing Parameter SetsJustin Domke. 874-882 [doi]
- Hessian-free Optimization for Learning Deep Multidimensional Recurrent Neural NetworksMinhyung Cho, Chandra Shekhar Dhir, Jaehyung Lee. 883-891 [doi]
- Large-scale probabilistic predictors with and without guarantees of validityVladimir Vovk, Ivan Petej, Valentina Fedorova. 892-900 [doi]
- Shepard Convolutional Neural NetworksJimmy S. J. Ren, Li Xu, Qiong Yan, Wenxiu Sun. 901-909 [doi]
- Matrix Manifold Optimization for Gaussian MixturesReshad Hosseini, Suvrit Sra. 910-918 [doi]
- Semi-supervised Convolutional Neural Networks for Text Categorization via Region EmbeddingRie Johnson, Tong Zhang 0001. 919-927 [doi]
- Parallel Recursive Best-First AND/OR Search for Exact MAP Inference in Graphical ModelsAkihiro Kishimoto, Radu Marinescu 0002, Adi Botea. 928-936 [doi]
- Convolutional Neural Networks with Intra-Layer Recurrent Connections for Scene LabelingMing Liang, Xiaolin Hu, Bo Zhang. 937-945 [doi]
- Bounding the Cost of Search-Based Lifted InferenceDavid B. Smith 0002, Vibhav Gogate. 946-954 [doi]
- Gradient-free Hamiltonian Monte Carlo with Efficient Kernel Exponential FamiliesHeiko Strathmann, Dino Sejdinovic, Samuel Livingstone, Zoltán Szabó 0001, Arthur Gretton. 955-963 [doi]
- Linear Multi-Resource Allocation with Semi-Bandit FeedbackTor Lattimore, Koby Crammer, Csaba Szepesvári. 964-972 [doi]
- Unsupervised Learning by Program SynthesisKevin Ellis, Armando Solar-Lezama, Joshua B. Tenenbaum. 973-981 [doi]
- Enforcing balance allows local supervised learning in spiking recurrent networksRalph Bourdoukan, Sophie Denève. 982-990 [doi]
- Fast and Guaranteed Tensor Decomposition via SketchingYining Wang, Hsiao-Yu Tung, Alexander J. Smola, Anima Anandkumar. 991-999 [doi]
- Differentially private subspace clusteringYining Wang, Yu-Xiang Wang, Aarti Singh. 1000-1008 [doi]
- Predtron: A Family of Online Algorithms for General Prediction ProblemsPrateek Jain 0002, Nagarajan Natarajan, Ambuj Tewari. 1009-1017 [doi]
- Weighted Theta Functions and Embeddings with Applications to Max-Cut, Clustering and SummarizationFredrik D. Johansson, Ankani Chattoraj, Chiranjib Bhattacharyya, Devdatt P. Dubhashi. 1018-1026 [doi]
- SGD Algorithms based on Incomplete U-statistics: Large-Scale Minimization of Empirical RiskGuillaume Papa, Stéphan Clémençon, Aurélien Bellet. 1027-1035 [doi]
- On Top-k Selection in Multi-Armed Bandits and Hidden Bipartite GraphsWei Cao, Jian Li, Yufei Tao, Zhize Li. 1036-1044 [doi]
- The Brain Uses Reliability of Stimulus Information when Making Perceptual DecisionsSebastian Bitzer, Stefan J. Kiebel. 1045-1053 [doi]
- Fast Classification Rates for High-dimensional Gaussian Generative ModelsTianyang Li, Adarsh Prasad, Pradeep Ravikumar. 1054-1062 [doi]
- Fast Distributed k-Center Clustering with Outliers on Massive DataGustavo Malkomes, Matt J. Kusner, Wenlin Chen, Kilian Q. Weinberger, Benjamin Moseley. 1063-1071 [doi]
- Human Memory Search as Initial-Visit Emitting Random WalkKwang-Sung Jun, Xiaojin Zhu, Timothy T. Rogers, Zhuoran Yang, Ming Yuan. 1072-1080 [doi]
- Non-convex Statistical Optimization for Sparse Tensor Graphical ModelWei Sun, Zhaoran Wang, Han Liu, Guang Cheng. 1081-1089 [doi]
- Convergence Rates of Active Learning for Maximum Likelihood EstimationKamalika Chaudhuri, Sham M. Kakade, Praneeth Netrapalli, Sujay Sanghavi. 1090-1098 [doi]
- Weakly-supervised Disentangling with Recurrent Transformations for 3D View SynthesisJimei Yang, Scott E. Reed, Ming-Hsuan Yang, Honglak Lee. 1099-1107 [doi]
- Efficient Exact Gradient Update for training Deep Networks with Very Large Sparse TargetsPascal Vincent, Alexandre de Brébisson, Xavier Bouthillier. 1108-1116 [doi]
- Backpropagation for Energy-Efficient Neuromorphic ComputingSteven K. Esser, Rathinakumar Appuswamy, Paul Merolla, John V. Arthur, Dharmendra S. Modha. 1117-1125 [doi]
- Alternating Minimization for Regression Problems with Vector-valued OutputsPrateek Jain 0002, Ambuj Tewari. 1126-1134 [doi]
- Learning both Weights and Connections for Efficient Neural NetworkSong Han, Jeff Pool, John Tran, William J. Dally. 1135-1143 [doi]
- Optimal Rates for Random Fourier FeaturesBharath K. Sriperumbudur, Zoltán Szabó 0001. 1144-1152 [doi]
- The Population Posterior and Bayesian Modeling on StreamsJames McInerney, Rajesh Ranganath, David M. Blei. 1153-1161 [doi]
- Frank-Wolfe Bayesian Quadrature: Probabilistic Integration with Theoretical GuaranteesFrançois-Xavier Briol, Chris J. Oates, Mark A. Girolami, Michael A. Osborne. 1162-1170 [doi]
- Scheduled Sampling for Sequence Prediction with Recurrent Neural NetworksSamy Bengio, Oriol Vinyals, Navdeep Jaitly, Noam Shazeer. 1171-1179 [doi]
- Unified View of Matrix Completion under General Structural ConstraintsSuriya Gunasekar, Arindam Banerjee, Joydeep Ghosh. 1180-1188 [doi]
- Efficient Output Kernel Learning for Multiple TasksPratik Jawanpuria, Maksim Lapin, Matthias Hein 0001, Bernt Schiele. 1189-1197 [doi]
- Scalable Adaptation of State Complexity for Nonparametric Hidden Markov ModelsMichael C. Hughes, William T. Stephenson, Erik B. Sudderth. 1198-1206 [doi]
- Variational Consensus Monte CarloMaxim Rabinovich, Elaine Angelino, Michael I. Jordan. 1207-1215 [doi]
- Newton-Stein Method: A Second Order Method for GLMs via Stein's LemmaMurat A. Erdogdu. 1216-1224 [doi]
- Practical and Optimal LSH for Angular DistanceAlexandr Andoni, Piotr Indyk, Thijs Laarhoven, Ilya P. Razenshteyn, Ludwig Schmidt. 1225-1233 [doi]
- Learning to Linearize Under UncertaintyRoss Goroshin, Michaël Mathieu, Yann LeCun. 1234-1242 [doi]
- Finite-Time Analysis of Projected Langevin Monte CarloSébastien Bubeck, Ronen Eldan, Joseph Lehec. 1243-1251 [doi]
- Deep Visual Analogy-MakingScott E. Reed, Yi Zhang, Yuting Zhang, Honglak Lee. 1252-1260 [doi]
- Matrix Completion from Fewer Entries: Spectral Detectability and Rank EstimationAlaa Saade, Florent Krzakala, Lenka Zdeborová. 1261-1269 [doi]
- Online Learning with Adversarial DelaysKent Quanrud, Daniel Khashabi. 1270-1278 [doi]
- Multi-Layer Feature Reduction for Tree Structured Group Lasso via Hierarchical ProjectionJie Wang, Jieping Ye. 1279-1287 [doi]
- Minimum Weight Perfect Matching via Blossom Belief PropagationSungsoo Ahn, Sejun Park, Michael Chertkov, Jinwoo Shin. 1288-1296 [doi]
- Efficient Thompson Sampling for Online Matrix-Factorization RecommendationJaya Kawale, Hung Hai Bui, Branislav Kveton, Long Tran-Thanh, Sanjay Chawla. 1297-1305 [doi]
- Improved Iteration Complexity Bounds of Cyclic Block Coordinate Descent for Convex ProblemsRuoyu Sun, Mingyi Hong. 1306-1314 [doi]
- Lifted Symmetry Detection and Breaking for MAP InferenceTimothy Kopp, Parag Singla, Henry A. Kautz. 1315-1323 [doi]
- Evaluating the statistical significance of biclustersJason D. Lee, Yuekai Sun, Jonathan E. Taylor. 1324-1332 [doi]
- Discriminative Robust Transformation LearningJiaji Huang, Qiang Qiu, Guillermo Sapiro, A. Robert Calderbank. 1333-1341 [doi]
- Bandits with Unobserved Confounders: A Causal ApproachElias Bareinboim, Andrew Forney, Judea Pearl. 1342-1350 [doi]
- Scalable Semi-Supervised Aggregation of ClassifiersAkshay Balsubramani, Yoav Freund. 1351-1359 [doi]
- Online Learning with Gaussian Payoffs and Side ObservationsYifan Wu, András György, Csaba Szepesvári. 1360-1368 [doi]
- Private Graphon Estimation for Sparse GraphsChristian Borgs, Jennifer T. Chayes, Adam D. Smith. 1369-1377 [doi]
- SubmodBoxes: Near-Optimal Search for a Set of Diverse Object ProposalsQing Sun, Dhruv Batra. 1378-1386 [doi]
- Fast Second Order Stochastic Backpropagation for Variational InferenceKai Fan, Ziteng Wang, Jeffrey M. Beck, James T. Kwok, Katherine A. Heller. 1387-1395 [doi]
- Randomized Block Krylov Methods for Stronger and Faster Approximate Singular Value DecompositionCameron Musco, Christopher Musco. 1396-1404 [doi]
- Cross-Domain Matching for Bag-of-Words Data via Kernel Embeddings of Latent DistributionsYuya Yoshikawa, Tomoharu Iwata, Hiroshi Sawada, Takeshi Yamada. 1405-1413 [doi]
- Scalable Inference for Gaussian Process Models with Black-Box LikelihoodsAmir Dezfouli, Edwin V. Bonilla. 1414-1422 [doi]
- Fast Bidirectional Probability Estimation in Markov ModelsSiddhartha Banerjee, Peter Lofgren. 1423-1431 [doi]
- Probabilistic Variational Bounds for Graphical ModelsQiang Liu, John W. Fisher III, Alexander T. Ihler. 1432-1440 [doi]
- Linear Response Methods for Accurate Covariance Estimates from Mean Field Variational BayesRyan Giordano, Tamara Broderick, Michael I. Jordan. 1441-1449 [doi]
- Combinatorial Cascading BanditsBranislav Kveton, Zheng Wen, Azin Ashkan, Csaba Szepesvári. 1450-1458 [doi]
- Mixing Time Estimation in Reversible Markov Chains from a Single Sample PathDaniel J. Hsu, Aryeh Kontorovich, Csaba Szepesvári. 1459-1467 [doi]
- Policy Gradient for Coherent Risk MeasuresAviv Tamar, Yinlam Chow, Mohammad Ghavamzadeh, Shie Mannor. 1468-1476 [doi]
- Fast Rates for Exp-concave Empirical Risk MinimizationTomer Koren, Kfir Y. Levy. 1477-1485 [doi]
- Deep Generative Image Models using a Laplacian Pyramid of Adversarial NetworksEmily L. Denton, Soumith Chintala, Arthur Szlam, Rob Fergus. 1486-1494 [doi]
- Decoupled Deep Neural Network for Semi-supervised Semantic SegmentationSeunghoon Hong, Hyeonwoo Noh, Bohyung Han. 1495-1503 [doi]
- Equilibrated adaptive learning rates for non-convex optimizationYann Dauphin, Harm de Vries, Yoshua Bengio. 1504-1512 [doi]
- BACKSHIFT: Learning causal cyclic graphs from unknown shift interventionsDominik Rothenhäusler, Christina Heinze, Jonas Peters, Nicolai Meinshausen. 1513-1521 [doi]
- Risk-Sensitive and Robust Decision-Making: a CVaR Optimization ApproachYinlam Chow, Aviv Tamar, Shie Mannor, Marco Pavone. 1522-1530 [doi]
- Asynchronous stochastic convex optimization: the noise is in the noise and SGD don't careSorathan Chaturapruek, John C. Duchi, Christopher Ré. 1531-1539 [doi]
- Lifelong Learning with Non-i.i.d. TasksAnastasia Pentina, Christoph H. Lampert. 1540-1548 [doi]
- Optimal Linear Estimation under Unknown Nonlinear TransformXinyang Yi, Zhaoran Wang, Constantine Caramanis, Han Liu. 1549-1557 [doi]
- Learning with Group Invariant Features: A Kernel PerspectiveYoussef Mroueh, Stephen Voinea, Tomaso A. Poggio. 1558-1566 [doi]
- Regularized EM Algorithms: A Unified Framework and Statistical GuaranteesXinyang Yi, Constantine Caramanis. 1567-1575 [doi]
- Distributionally Robust Logistic RegressionSoroosh Shafieezadeh-Abadeh, Peyman Mohajerin Esfahani, Daniel Kuhn. 1576-1584 [doi]
- Adaptive Stochastic Optimization: From Sets to PathsZhan Wei Lim, David Hsu, Wee Sun Lee. 1585-1593 [doi]
- Beyond Convexity: Stochastic Quasi-Convex OptimizationElad Hazan, Kfir Y. Levy, Shai Shalev-Shwartz. 1594-1602 [doi]
- A Tractable Approximation to Optimal Point Process Filtering: Application to Neural EncodingYuval Harel, Ron Meir, Manfred Opper. 1603-1611 [doi]
- Sum-of-Squares Lower Bounds for Sparse PCATengyu Ma, Avi Wigderson. 1612-1620 [doi]
- Max-Margin Majority Voting for Learning from CrowdsTian Tian 0001, Jun Zhu. 1621-1629 [doi]
- Learning with Incremental Iterative RegularizationLorenzo Rosasco, Silvia Villa. 1630-1638 [doi]
- Halting in Random Walk KernelsMahito Sugiyama, Karsten M. Borgwardt. 1639-1647 [doi]
- MCMC for Variationally Sparse Gaussian ProcessesJames Hensman, Alexander G. de G. Matthews, Maurizio Filippone, Zoubin Ghahramani. 1648-1656 [doi]
- Less is More: Nyström Computational RegularizationAlessandro Rudi, Raffaello Camoriano, Lorenzo Rosasco. 1657-1665 [doi]
- Infinite Factorial Dynamical ModelIsabel Valera, Francisco J. R. Ruiz, Lennart Svensson, Fernando Pérez-Cruz. 1666-1674 [doi]
- Regularization Path of Cross-Validation Error Lower BoundsAtsushi Shibagaki, Yoshiki Suzuki, Masayuki Karasuyama, Ichiro Takeuchi. 1675-1683 [doi]
- Attractor Network Dynamics Enable Preplay and Rapid Path Planning in Maze-like EnvironmentsDane S. Corneil, Wulfram Gerstner. 1684-1692 [doi]
- Teaching Machines to Read and ComprehendKarl Moritz Hermann, Tomás Kociský, Edward Grefenstette, Lasse Espeholt, Will Kay, Mustafa Suleyman, Phil Blunsom. 1693-1701 [doi]
- Principal Differences Analysis: Interpretable Characterization of Differences between DistributionsJonas Mueller, Tommi S. Jaakkola. 1702-1710 [doi]
- When are Kalman-Filter Restless Bandits Indexable?Christopher R. Dance, Tomi Silander. 1711-1719 [doi]
- Segregated Graphs and Marginals of Chain Graph ModelsIlya Shpitser. 1720-1728 [doi]
- Efficient Non-greedy Optimization of Decision TreesMohammad Norouzi 0002, Maxwell D. Collins, Matthew A. Johnson, David J. Fleet, Pushmeet Kohli. 1729-1737 [doi]
- Probabilistic Curve Learning: Coulomb Repulsion and the Electrostatic Gaussian ProcessYe Wang, David B. Dunson. 1738-1746 [doi]
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- Spectral Representations for Convolutional Neural NetworksOren Rippel, Jasper Snoek, Ryan P. Adams. 2449-2457 [doi]
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- A Theory of Decision Making Under Dynamic ContextMichael Shvartsman, Vaibhav Srivastava, Jonathan D. Cohen. 2485-2493 [doi]
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- Deep Convolutional Inverse Graphics NetworkTejas D. Kulkarni, William F. Whitney, Pushmeet Kohli, Joshua B. Tenenbaum. 2539-2547 [doi]
- Sparse and Low-Rank Tensor DecompositionParikshit Shah, Nikhil S. Rao, Gongguo Tang. 2548-2556 [doi]
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- Matrix Completion with Noisy Side InformationKai-yang Chiang, Cho-Jui Hsieh, Inderjit S. Dhillon. 3447-3455 [doi]
- Dependent Multinomial Models Made Easy: Stick-Breaking with the Polya-gamma AugmentationScott W. Linderman, Matthew Johnson, Ryan P. Adams. 3456-3464 [doi]
- On-the-Job Learning with Bayesian Decision TheoryKeenon Werling, Arun Tejasvi Chaganty, Percy Liang, Christopher D. Manning. 3465-3473 [doi]
- Calibrated Structured PredictionVolodymyr Kuleshov, Percy Liang. 3474-3482 [doi]
- Learning Structured Output Representation using Deep Conditional Generative ModelsKihyuk Sohn, Honglak Lee, Xinchen Yan. 3483-3491 [doi]
- Time-Sensitive Recommendation From Recurrent User ActivitiesNan Du, Yichen Wang, Niao He, Jimeng Sun, Le Song. 3492-3500 [doi]
- Learning Stationary Time Series using Gaussian Processes with Nonparametric KernelsFelipe A. Tobar, Thang D. Bui, Richard E. Turner. 3501-3509 [doi]
- A Market Framework for Eliciting Private DataBo Waggoner, Rafael M. Frongillo, Jacob D. Abernethy. 3510-3518 [doi]
- Lifted Inference Rules With ConstraintsHappy Mittal, Anuj Mahajan, Vibhav Gogate, Parag Singla. 3519-3527 [doi]
- Gradient Estimation Using Stochastic Computation GraphsJohn Schulman, Nicolas Heess, Theophane Weber, Pieter Abbeel. 3528-3536 [doi]
- Model-Based Relative Entropy Stochastic SearchAbbas Abdolmaleki, Rudolf Lioutikov, Jan Peters 0001, Nuno Lau, Luís Paulo Reis, Gerhard Neumann. 3537-3545 [doi]
- Semi-supervised Learning with Ladder NetworksAntti Rasmus, Mathias Berglund, Mikko Honkala, Harri Valpola, Tapani Raiko. 3546-3554 [doi]
- Embedding Inference for Structured Multilabel PredictionFarzaneh Mirzazadeh, Siamak Ravanbakhsh, Nan Ding, Dale Schuurmans. 3555-3563 [doi]
- Copula variational inferenceDustin Tran, David M. Blei, Edoardo M. Airoldi. 3564-3572 [doi]
- Recursive Training of 2D-3D Convolutional Networks for Neuronal Boundary PredictionKisuk Lee, Aleksandar Zlateski, Ashwin Vishwanathan, H. Sebastian Seung. 3573-3581 [doi]
- A Dual Augmented Block Minimization Framework for Learning with Limited MemoryIan En-Hsu Yen, Shan-Wei Lin, Shou-de Lin. 3582-3590 [doi]
- Optimal Testing for Properties of DistributionsJayadev Acharya, Constantinos Daskalakis, Gautam Kamath. 3591-3599 [doi]
- Efficient Learning of Continuous-Time Hidden Markov Models for Disease ProgressionYu-Ying Liu, Shuang Li, Fuxin Li, Le Song, James M. Rehg. 3600-3608 [doi]
- Expectation Particle Belief PropagationThibaut Lienart, Yee Whye Teh, Arnaud Doucet. 3609-3617 [doi]
- Latent Bayesian melding for integrating individual and population modelsMingjun Zhong, Nigel H. Goddard, Charles A. Sutton. 3618-3626 [doi]