Abstract is missing.
- Bayesian Optimal Control of Smoothly Parameterized SystemsYasin Abbasi-Yadkori, Csaba Szepesvári. 1-11
- Optimal expert elicitation to reduce interval uncertaintyNadia Ben Abdallah, Sébastien Destercke. 12-21
- Stochastic Integration via Error-Correcting CodesDimitris Achlioptas, Pei Jiang 0001. 22-31
- Learning the Structure of Sum-Product Networks via an SVD-based AlgorithmTameem Adel, David Balduzzi, Ali Ghodsi. 32-41
- Robust reconstruction of causal graphical models based on conditional 2-point and 3-point informationSéverine Affeldt, Hervé Isambert. 42-51
- Are You Doing What I Think You Are Doing? Criticising Uncertain Agent ModelsStefano V. Albrecht, Subramanian Ramamoorthy. 52-61
- Disciplined Convex Stochastic Programming: A New Framework for Stochastic OptimizationAlnur Ali, J. Zico Kolter, Steven Diamond, Stephen Boyd. 62-71
- Intelligent Affect: Rational Decision Making for Socially Aligned AgentsNabiha Asghar, Jesse Hoey. 72-81
- Representation Learning for Clustering: A Statistical FrameworkHassan Ashtiani, Shai Ben-David. 82-91
- Adversarial Cost-Sensitive ClassificationKaiser Asif, Wei Xing, Sima Behpour, Brian D. Ziebart. 92-101
- Geometric Network ComparisonsDena Marie Asta, Cosma Rohilla Shalizi. 102-110
- Learning and Planning with Timing Information in Markov Decision ProcessesPierre-Luc Bacon, Borja Balle, Doina Precup. 111-120
- Parameterizing the Distance Distribution of Undirected NetworksChristian Bauckhage, Kristian Kersting, Fabian Hadiji. 121-130
- New Limits for Knowledge Compilation and Applications to Exact Model CountingPaul Beame, Vincent Liew. 131-140
- Hashing-Based Approximate Probabilistic Inference in Hybrid DomainsVaishak Belle, Guy Van den Broeck, Andrea Passerini. 141-150
- Bayesian Network Learning with Discrete Case-Control DataGiorgos Borboudakis, Ioannis Tsamardinos. 151-160
- Efficient Algorithms for Bayesian Network Parameter Learning from Incomplete DataGuy Van den Broeck, Karthika Mohan, Arthur Choi, Adnan Darwiche, Judea Pearl. 161-170
- Bayes Optimal Feature Selection for Supervised Learning with General Performance MeasuresC. G. Saneem Ahmed, Harikrishna Narasimhan, Shivani Agarwal 0001. 171-180
- Visual Causal Feature LearningKrzysztof Chalupka, Pietro Perona, Frederick Eberhardt. 181-190
- Large-Margin Determinantal Point ProcessesWei-Lun Chao, Boqing Gong, Kristen Grauman, Fei Sha. 191-200
- Fast Relative-Error Approximation Algorithm for Ridge RegressionShouyuan Chen, Yang Liu, Michael R. Lyu, Irwin King, Shengyu Zhang. 201-210
- Selective Greedy Equivalence Search: Finding Optimal Bayesian Networks Using a Polynomial Number of Score EvaluationsDavid Maxwell Chickering, Christopher Meek. 211-219
- Stable Spectral Learning Based on Schur DecompositionNicolò Colombo, Nikos Vlassis. 220-227
- Semi-described and semi-supervised learning with Gaussian processesAndreas C. Damianou, Neil D. Lawrence. 228-237
- Budget Constraints in Prediction MarketsNikhil R. Devanur, Miroslav Dudík, Zhiyi Huang 0002, David M. Pennock. 238-247
- A Probabilistic Logic for Reasoning about Uncertain Temporal InformationDragan Doder, Zoran Ognjanovic. 248-257
- Training generative neural networks via Maximum Mean Discrepancy optimizationGintare Karolina Dziugaite, Daniel M. Roy, Zoubin Ghahramani. 258-267
- Incremental Region Selection for Mini-bucket Elimination BoundsSholeh Forouzan, Alexander T. Ihler. 268-277
- Estimating Mutual Information by Local Gaussian ApproximationShuyang Gao, Greg Ver Steeg, Aram Galstyan. 278-285
- Psychophysical Detection Testing with Bayesian Active LearningJacob R. Gardner, Xinyu Song, Kilian Q. Weinberger, Dennis L. Barbour, John P. Cunningham. 286-295
- Locally Conditioned Belief PropagationThomas Geier, Felix Richter, Susanne Biundo. 296-305
- Discriminative Switching Linear Dynamical Systems applied to Physiological Condition MonitoringKonstantinos Georgatzis, Christopher K. I. Williams. 306-315
- Revisiting Non-Progressive Influence Models: Scalable Influence Maximization in Social NetworksGolshan Golnari, Amir Asiaee T., Arindam Banerjee, Zhi-Li Zhang. 316-325
- Scalable Recommendation with Hierarchical Poisson FactorizationPrem Gopalan, Jake M. Hofman, David M. Blei. 326-335
- State Sequence Analysis in Hidden Markov ModelsYuri Grinberg, Theodore J. Perkins. 336-344
- Multitasking: Optimal Planning for Bandit SuperprocessesDylan Hadfield-Menell, Stuart J. Russell. 345-354
- Importance Sampling over Sets: A New Probabilistic Inference SchemeStefan Hadjis, Stefano Ermon. 355-364
- Progressive Abstraction Refinement for Sparse SamplingJesse Hostetler, Alan Fern, Thomas G. Dietterich. 365-374
- Zero-Truncated Poisson Tensor Factorization for Massive Binary TensorsChangwei Hu, Piyush Rai, Lawrence Carin. 375-384
- Computing Optimal Bayesian Decisions for Rank Aggregation via MCMC SamplingDavid Hughes, Kevin Hwang, Lirong Xia. 385-394
- Do-calculus when the True Graph Is UnknownAntti Hyttinen, Frederick Eberhardt, Matti Järvisalo. 395-404
- Kernel-Based Just-In-Time Learning for Passing Expectation Propagation MessagesWittawat Jitkrittum, Arthur Gretton, Nicolas Heess, S. M. Ali Eslami, Balaji Lakshminarayanan, Dino Sejdinovic, Zoltán Szabó 0001. 405-414
- Averaging of Decomposable Graphs by Dynamic Programming and SamplingKustaa Kangas, Teppo Mikael Niinimäki, Mikko Koivisto. 415-424
- Novel Bernstein-like Concentration Inequalities for the Missing MassBahman Yari Saeed Khanloo, Gholamreza Haffari. 425-434
- Minimizing Expected Losses in Perturbation Models with Multidimensional Parametric Min-cutsAdrian Kim, Kyomin Jung, Yongsub Lim, Daniel Tarlow, Pushmeet Kohli. 435-443
- Population Empirical BayesAlp Kucukelbir, David M. Blei. 444-453
- Encoding Markov logic networks in Possibilistic LogicOndrej Kuzelka, Jesse Davis, Steven Schockaert. 454-463
- On the Computability of AIXIJan Leike, Marcus Hutter. 464-473
- Tracking with ranked signalsTianyang Li, Harsh H. Pareek, Pradeep D. Ravikumar, Dhruv Balwada, Kevin Speer. 474-483
- Classification of Sparse and Irregularly Sampled Time Series with Mixtures of Expected Gaussian Kernels and Random FeaturesSteven Cheng-Xian Li, Benjamin Marlin. 484-493
- Complexity of the Exact Solution to the Test Sequencing ProblemWenhao Liu, Ross D. Shachter. 494-503
- Finite-Sample Analysis of Proximal Gradient TD AlgorithmsBo Liu, Ji Liu 0002, Mohammad Ghavamzadeh, Sridhar Mahadevan, Marek Petrik. 504-513
- Estimating the Partition Function by Discriminance SamplingQiang Liu, Jian Peng, Alexander T. Ihler, John W. Fisher III. 514-522
- A Finite Population Likelihood Ratio Test of the Sharp Null Hypothesis for CompliersWen Wei Loh, Thomas S. Richardson. 523-532
- Structure Learning Constrained by Node-Specific Degree DistributionJianzhu Ma, Feng Zhao, Jinbo Xu. 533-541
- Active Search and Bandits on Graphs using Sigma-OptimalityYifei Ma, Tzu-Kuo Huang, Jeff G. Schneider. 542-551
- Off-policy learning based on weighted importance sampling with linear computational complexityAshique Rupam Mahmood, Richard S. Sutton. 552-561
- Impact of Learning Strategies on the Quality of Bayesian Networks: An Empirical EvaluationBrandon Malone, Matti Järvisalo, Petri Myllymäki. 562-571
- Learning the Structure of Causal Models with Relational and Temporal DependenceKaterina Marazopoulou, Marc E. Maier, David D. Jensen. 572-581
- Hamiltonian ABCEdward Meeds, Robert Leenders, Max Welling. 582-591
- (Nearly) Optimal Differentially Private Stochastic Multi-Arm BanditsNikita Mishra, Abhradeep Thakurta. 592-601
- Equitable Partitions of Concave Free EnergiesMartin Mladenov, Kristian Kersting. 602-611
- Non-parametric Revenue Optimization for Generalized Second Price auctions.Mehryar Mohri, Andres Muñoz Medina. 612-621
- Polynomial-time algorithm for learning optimal tree-augmented dynamic Bayesian networksJosé L. Monteiro, Susana Vinga, Alexandra M. Carvalho. 622-631
- Learning and Inference in Tractable Probabilistic Knowledge BasesMathias Niepert, Pedro M. Domingos. 632-641
- Multi-Context Models for Reasoning under Partial Knowledge: Generative Process and Inference GrammarArdavan Salehi Nobandegani, Ioannis N. Psaromiligkos. 642-651
- Annealed Gradient Descent for Deep LearningHengyue Pan, Hui Jiang. 652-661
- Max-Product Belief Propagation for Linear Programming: Applications to Combinatorial OptimizationSejun Park, Jinwoo Shin. 662-671
- Fast Algorithms for Learning with Long N-grams via Suffix Tree Based Matrix MultiplicationHristo S. Paskov, John C. Mitchell, Trevor J. Hastie. 672-681
- A Complete Generalized Adjustment CriterionEmilija Perkovic, Johannes Textor, Markus Kalisch, Marloes H. Maathuis. 682-691
- Optimal Threshold Control for Energy Arbitrage with Degradable Battery StorageMarek Petrik, XiaoJian Wu. 692-701
- Mesochronal Structure LearningSergey M. Plis, David Danks, Jianyu Yang. 702-711
- Budgeted Online Collective InferenceJay Pujara, Ben London, Lise Getoor. 712-721
- Auxiliary Gibbs Sampling for Inference in Piecewise-Constant Conditional Intensity ModelsZhen Qin, Christian R. Shelton. 722-731
- Memory-Effcient Symbolic Online Planning for Factored MDPsAswin Raghavan, Roni Khardon, Prasad Tadepalli, Alan Fern. 732-741
- The Survival Filter: Joint Survival Analysis with a Latent Time SeriesRajesh Ranganath, Adler J. Perotte, Noémie Elhadad, David M. Blei. 742-751
- Communication Efficient Coresets for Empirical Loss MinimizationSashank J. Reddi, Barnabás Póczos, Alexander J. Smola. 752-761
- Large-scale randomized-coordinate descent methods with non-separable linear constraintsSashank J. Reddi, Ahmed Hefny, Carlton Downey, Avinava Dubey, Suvrit Sra. 762-771
- An Upper Bound on the Global Optimum in Parameter EstimationKhaled S. Refaat, Adnan Darwiche. 772-781
- A Markov Game Model for Valuing Player Actions in Ice HockeyKurt Routley, Oliver Schulte. 782-791
- Learning Latent Variable Models by Improving Spectral Solutions with Exterior Point MethodAmirreza Shaban, Mehrdad Farajtabar, Bo Xie 0002, Le Song, Byron Boots. 792-801
- Missing Data as a Causal and Probabilistic ProblemIlya Shpitser, Karthika Mohan, Judea Pearl. 802-811
- Improved Asymmetric Locality Sensitive Hashing (ALSH) for Maximum Inner Product Search (MIPS)Anshumali Shrivastava, Ping Li 0001. 812-821
- Learning Optimal Chain Graphs with Answer Set ProgrammingDag Sonntag, Matti Järvisalo, Jose M. Peña, Antti Hyttinen. 822-831
- How matroids occur in the context of learning Bayesian network structureMilan Studený. 832-841
- The Long-Run Behavior of Continuous Time Bayesian NetworksLiessman Sturlaugson, John W. Sheppard. 842-851
- Online Bellman Residual Algorithms with Predictive Error GuaranteesWen Sun, J. Andrew Bagnell. 852-861
- On the Error of Random Fourier FeaturesDougal J. Sutherland, Jeff G. Schneider. 862-871
- Bayesian Structure Learning for Stationary Time SeriesAlex Tank, Nicholas J. Foti, Emily B. Fox. 872-881
- Learning from Pairwise Marginal IndependenciesJohannes Textor, Alexander Idelberger, Maciej Liskiewicz. 882-891
- Bethe Projections for Non-Local InferenceLuke Vilnis, David Belanger, Daniel Sheldon, Andrew McCallum. 892-901
- A Smart-Dumb/Dumb-Smart Algorithm for Efficient Split-Merge MCMCWei Wang, Stuart J. Russell. 902-911
- Planning under Uncertainty with Weighted State ScenariosErwin Walraven, Matthijs T. J. Spaan. 912-921
- Generalization Bounds for Transfer Learning under Model ShiftXuezhi Wang, Jeff G. Schneider. 922-931
- Clustered Sparse Bayesian LearningYu Wang, David P. Wipf, Jeong-Min Yun, Wei Chen, Ian J. Wassell. 932-941
- Bethe and Related Pairwise Entropy ApproximationsAdrian Weller. 942-951
- Effcient Transition Probability Computation for Continuous-Time Branching Processes via Compressed SensingJason Xu, Vladimir N. Minin. 952-961
- Extend Transferable Belief Models with Probabilistic PriorsChunlai Zhou, Yuan Feng. 962-971
- Probabilistic Graphical Models Parameter Learning with Transferred Prior and ConstraintsYun Zhou, Norman Fenton, Timothy M. Hospedales, Martin Neil. 972-981