Table of Contents

• Bayesian learning of joint distributions of objectsAnjishnu Banerjee, Jared Murray, David B. Dunson. 1-9 [doi]
• Permutation estimation and minimax rates of identifiabilityOlivier Collier, Arnak S. Dalalyan. 10-19 [doi]
• A unifying representation for a class of dependent random measuresNicholas J. Foti, Joseph D. Futoma, Daniel N. Rockmore, Sinead Williamson. 20-28 [doi]
• Diagonal Orthant Multinomial Probit ModelsJames Johndrow, David B. Dunson, Kristian Lum. 29-38 [doi]
• Distributed Learning of Gaussian Graphical Models via Marginal LikelihoodsZhaoshi Meng, Dennis Wei, Ami Wiesel, Alfred O. Hero III. 39-47 [doi]
• Sparse Principal Component Analysis for High Dimensional Multivariate Time SeriesZhaoran Wang, Fang Han, Han Liu. 48-56 [doi]
• A Competitive Test for Uniformity of Monotone DistributionsJayadev Acharya, Ashkan Jafarpour, Alon Orlitsky, Ananda Theertha Suresh. 57-65 [doi]
• Clustering OligarchiesMargareta Ackerman, Shai Ben-David, David Loker, Sivan Sabato. 66-74 [doi]
• Reconstructing ecological networks with hierarchical Bayesian regression and Mondrian processesAndrej Aderhold, Dirk Husmeier, V. Anne Smith. 75-84 [doi]
• Nystrom Approximation for Large-Scale Determinantal ProcessesRaja Hafiz Affandi, Alex Kulesza, Emily B. Fox, Ben Taskar. 85-98 [doi]
• Further Optimal Regret Bounds for Thompson SamplingShipra Agrawal, Navin Goyal. 99-107 [doi]
• Distributed and Adaptive Darting Monte Carlo through RegenerationsSungjin Ahn, Yutian Chen, Max Welling. 108-116 [doi]
• Consensus Ranking with Signed PermutationsRaman Arora, Marina Meila. 117-125 [doi]
• Ultrahigh Dimensional Feature Screening via RKHS EmbeddingsKrishnakumar Balasubramanian, Bharath K. Sriperumbudur, Guy Lebanon. 126-134 [doi]
• Meta-Transportability of Causal Effects: A Formal ApproachElias Bareinboim, Judea Pearl. 135-143 [doi]
• Convex Collective Matrix FactorizationGuillaume Bouchard, Dawei Yin, Shengbo Guo. 144-152 [doi]
• Efficiently Sampling Probabilistic Programs via Program AnalysisArun Chaganty, Aditya V. Nori, Sriram K. Rajamani. 153-160 [doi]
• Computing the M Most Probable Modes of a Graphical ModelChao Chen, Vladimir Kolmogorov, Yan Zhu, Dimitris N. Metaxas, Christoph H. Lampert. 161-169 [doi]
• A simple criterion for controlling selection biasEunice Yuh-Jie Chen, Judea Pearl. 170-177 [doi]
• Evidence Estimation for Bayesian Partially Observed MRFsYutian Chen, Max Welling. 178-186 [doi]
• Why Steiner-tree type algorithms work for community detectionMung Chiang, Henry Lam, Zhenming Liu, H. Vincent Poor. 187-195 [doi]
• A simple sketching algorithm for entropy estimation over streaming dataPeter Clifford, Ioana Cosma. 196-206 [doi]
• Deep Gaussian ProcessesAndreas C. Damianou, Neil D. Lawrence. 207-215 [doi]
• ODE parameter inference using adaptive gradient matching with Gaussian processesFrank Dondelinger, Dirk Husmeier, Simon Rogers, Maurizio Filippone. 216-228 [doi]
• Uncover Topic-Sensitive Information Diffusion NetworksNan Du, Le Song, Hyenkyun Woo, Hongyuan Zha. 229-237 [doi]
• Stochastic blockmodeling of relational event dynamicsChristopher DuBois, Carter T. Butts, Padhraic Smyth. 238-246 [doi]
• Dynamic Copula Networks for Modeling Real-valued Time SeriesElad Eban, Gideon Rothschild, Adi Mizrahi, Israel Nelken, Gal Elidan. 247-255 [doi]
• Data-driven covariate selection for nonparametric estimation of causal effectsDoris Entner, Patrik O. Hoyer, Peter Spirtes. 256-264 [doi]
• Learning to Top-K Search using Pairwise ComparisonsBrian Eriksson. 265-273 [doi]
• Predictive Correlation Screening: Application to Two-stage Predictor Design in High DimensionHamed Firouzi, Bala Rajaratnam, Alfred O. Hero III. 274-288 [doi]
• Mixed LICORS: A Nonparametric Algorithm for Predictive State ReconstructionGeorg M. Goerg, Cosma Rohilla Shalizi. 289-297 [doi]
• Unsupervised Link Selection in NetworksQuanquan Gu, Charu C. Aggarwal, Jiawei Han. 298-306 [doi]
• Clustered Support Vector MachinesQuanquan Gu, Jiawei Han. 307-315 [doi]
• DivMCuts: Faster Training of Structural SVMs with Diverse M-Best Cutting-PlanesAbner Guzmán-Rivera, Pushmeet Kohli, Dhruv Batra. 316-324 [doi]
• Recursive Karcher Expectation Estimators And Geometric Law of Large NumbersJeffrey Ho, Guang Cheng 0002, Hesamoddin Salehian, Baba C. Vemuri. 325-332 [doi]
• DYNACARE: Dynamic Cardiac Arrest Risk EstimationJoyce Ho, Yubin Park, Carlos Carvalho, Joydeep Ghosh. 333-341 [doi]
• Active Learning for Interactive VisualizationTomoharu Iwata, Neil Houlsby, Zoubin Ghahramani. 342-350 [doi]
• A Parallel, Block Greedy Method for Sparse Inverse Covariance Estimation for Ultra-high DimensionsPrabhanjan Kambadur, Aurelie C. Lozano. 351-359 [doi]
• Beyond Sentiment: The Manifold of Human EmotionsSeungyeon Kim, Fuxin Li, Guy Lebanon, Irfan A. Essa. 360-369 [doi]
• Exact Learning of Bounded Tree-width Bayesian NetworksJanne Korhonen, Pekka Parviainen. 370-378 [doi]
• Structural Expectation Propagation (SEP): Bayesian structure learning for networks with latent variablesNevena Lazic, Christopher M. Bishop, John M. Winn. 379-387 [doi]
• Structure Learning of Mixed Graphical ModelsJason D. Lee, Trevor Hastie. 388-396 [doi]
• Dynamic Scaled Sampling for Deterministic ConstraintsLei Li, Bharath Ramsundar, Stuart J. Russell. 397-405 [doi]
• Learning Markov Networks With Arithmetic CircuitsDaniel Lowd, Amirmohammad Rooshenas. 406-414 [doi]
• Texture Modeling with Convolutional Spike-and-Slab RBMs and Deep ExtensionsHeng Luo, Pierre Luc Carrier, Aaron C. Courville, Yoshua Bengio. 415-423 [doi]
• Fast Near-GRID Gaussian Process RegressionYuancheng Luo, Ramani Duraiswami. 424-432 [doi]
• Estimating the Partition Function of Graphical Models Using Langevin Importance SamplingJianzhu Ma, Jian Peng 0001, Sheng Wang, Jinbo Xu. 433-441 [doi]
• Thompson Sampling in Switching Environments with Bayesian Online Change DetectionJoseph Mellor, Jonathan Shapiro. 442-450 [doi]
• A Last-Step Regression Algorithm for Non-Stationary Online LearningEdward Moroshko, Koby Crammer. 451-462 [doi]
• Competing with an Infinite Set of Models in Reinforcement LearningPhuong Nguyen, Odalric-Ambrym Maillard, Daniil Ryabko, Ronald Ortner. 463-471 [doi]
• Efficient Variational Inference for Gaussian Process Regression NetworksTrung Nguyen, Edwin V. Bonilla. 472-480 [doi]
• High-dimensional Inference via Lipschitz Sparsity-Yielding RegularizersZheng Pan, Changshui Zhang. 481-488 [doi]
• Bayesian Structure Learning for Functional NeuroimagingMijung Park, Oluwasanmi Koyejo, Joydeep Ghosh, Russell A. Poldrack, Jonathan W. Pillow. 489-497 [doi]
• Random Projections for Support Vector MachinesSaurabh Paul, Christos Boutsidis, Malik Magdon-Ismail, Petros Drineas. 498-506 [doi]
• Distribution-Free Distribution RegressionBarnabás Póczos, Aarti Singh, Alessandro Rinaldo, Larry A. Wasserman. 507-515 [doi]
• Localization and Adaptation in Online LearningAlexander Rakhlin, Ohad Shamir, Karthik Sridharan. 516-526 [doi]
• A recursive estimate for the predictive likelihood in a topic modelJames Scott, Jason Baldridge. 527-535 [doi]
• Detecting Activations over Graphs using Spanning Tree Wavelet BasesJames Sharpnack, Aarti Singh, Akshay Krishnamurthy. 536-544 [doi]
• Changepoint Detection over Graphs with the Spectral Scan StatisticJames Sharpnack, Aarti Singh, Alessandro Rinaldo. 545-553 [doi]
• Central Limit Theorems for Conditional Markov ChainsMathieu Sinn, Bei Chen. 554-562 [doi]
• Statistical Tests for Contagion in Observational Social Network StudiesGreg Ver Steeg, Aram Galstyan. 563-571 [doi]
• Completeness Results for Lifted Variable EliminationNima Taghipour, Daan Fierens, Guy Van den Broeck, Jesse Davis, Hendrik Blockeel. 572-580 [doi]
• Supervised Sequential Classification Under Budget ConstraintsKirill Trapeznikov, Venkatesh Saligrama. 581-589 [doi]
• On the Asymptotic Optimality of Maximum Margin Bayesian NetworksSebastian Tschiatschek, Franz Pernkopf. 590-598 [doi]
• Collapsed Variational Bayesian Inference for Hidden Markov ModelsPengyu Wang, Phil Blunsom. 599-607 [doi]
• Block Regularized Lasso for Multivariate Multi-Response Linear RegressionWeiguang Wang, Yingbin Liang, Eric P. Xing. 608-617 [doi]
• Bethe Bounds and Approximating the Global OptimumAdrian Weller, Tony Jebara. 618-631 [doi]
• Dual Decomposition for Joint Discrete-Continuous OptimizationChristopher Zach. 632-640 [doi]
• Learning Social Infectivity in Sparse Low-rank Networks Using Multi-dimensional Hawkes ProcessesKe Zhou, Hongyuan Zha, Le Song. 641-649 [doi]
• Greedy Bilateral Sketch, Completion & SmoothingTianyi Zhou, Dacheng Tao. 650-658 [doi]
• Scoring anomalies: a M-estimation formulationStéphan Clémençon, Jérémie Jakubowicz. 659-667 [doi]