The 30th Uncertainty in Artificial Intelligence Conference: Preface

Nevin L. Zhang, Jin Tian; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:1-6

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Sequential Bayesian Optimisation for Spatial-Temporal Monitoring

Roman Marchant, Fabio Ramos, Scott Sanner; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:7-16

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Annealing Paths for the Evaluation of Topic Models

James Foulds, Padhraic Smyth; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:17-26

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Constraint-based Causal Discovery: Conflict Resolution with Answer Set Programming

Antti Hyttinen California Institute of Technology, Frederick Eberhardt Caltech, Matti Järvisalo HIIT/University of Helsinki; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:27-36

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Learning from Point Sets with Observational Bias

Liang Xiong Carnegie Mellon University, Jeff Schneider Carnegie Mellon University; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:37-45

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Bayesian Optimization with Unknown Constraints

Michael Gelbart Harvard University, Jasper Snoek Harvard University, Ryan Adams Harvard; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:46-55

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Universal Convexification via Risk-Aversion

Krishnamurthy Dvijotham, Maryam Fazel, Emanuel Todorov; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:56-65

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Collaborative Multi-output Gaussian Processes

Trung Nguyen, Edwin Bonilla National ICT Australia; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:66-75

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Matroid Bandits: Fast Combinatorial Optimization with Learning

Branislav Kveton Technicolor Labs, Zheng Wen, Azin Ashkan, Hoda Eydgahi, Brian Eriksson; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:76-85

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Tightness Results for Local Consistency Relaxations in Continuous MRFs

Yoav Wald, Amir Globerson; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:86-95

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Inferring latent structures via information inequalities

Rafael Chaves, Lukas Luft, Thiago Maciel Federal University of Minas Gerais, David Gross, Dominik Janzing, Bernhard Schölkopf; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:96-105

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AND/OR Search for Marginal MAP

Radu Marinescu, Rina Dechter, Alexander Ihler; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:106-115

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A Permutation-Based Kernel Conditional Independence Test

Gary Doran Case Western Reserve University, Krikamol Muandet MPI for Intelligent Systems, Kun Zhang MPI for Intelligent Systems, Bernhard Schölkopf; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:116-125

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Optimal Resource Allocation with Semi-Bandit Feedback

Tor Lattimore, Koby Crammer, Csaba Szepesvari; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:126-135

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Constructing Separators and Adjustment Sets in Ancestral Graphs

Benito van der Zander, Maciej Liskiewicz, Johannes Textor; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:136-145

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Lifted Message Passing as Reparametrization of Graphical Models

Martin Mladenov, Kristian Kersting, Amir Globerson; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:146-155

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Near-optimal Adaptive Pool-based Active Learning with General Loss

Nguyen Viet Cuong NUS, Wee Sun Lee NUS, Nan Ye NUS; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:156-165

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Market Making with Decreasing Utility for Information

Miroslav Dudik, Rafael Frongillo, Jennifer Wortman Vaughan; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:166-175

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k-NN Regression on Functional Data with Incomplete Observations

Sashank J. Reddi Carnegie Mellon University, Barnabas Poczos Carnegie Mellon Univeristy; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:176-185

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There IS a Free Lunch: Constraints for Learning Bayesian Networks

Xiannian Fan Graduate Center CUNY, Brandon Malone "Helsinki Institute for Information Technology Finland", Changhe Yuan City University of New York; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:186-195

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Firefly Monte Carlo: Exact MCMC with Subsets of Data

Dougal Maclaurin Harvard University, Ryan Adams Harvard; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:196-205

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First-Order Open-Universe POMDPs: Formulation and Algorithms

Siddharth Srivastava, Paul Ruan, Xiang Cheng, Stuart Russell; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:206-215

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Fast Newton methods for the group fused lasso

Matt Wytock Carnegie Mellon University, J. Zico Kolter Carnegie Mellon University, Suvrit Sra Carnegie Mellon University; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:216-225

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Estimating Accuracy from Unlabeled Data

Emmanouil Antonios Platanios Carnegie Mellon University, Avrim Blum Carnegie Mellon University, Tom Mitchell Carnegie Mellon University; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:226-235

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Electing the Most Probable Without Eliminating the Irrational: Voting Over Intransitive Domains

Edith Elkind, Nisarg Shah Carnegie Mellon University; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:236-245

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On Convergence and Optimality of Best-Response Learning with Policy Types in Multiagent Systems

Stefano Albrecht, Subramanian Ramamoorthy; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:246-255

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Efficient Inference of Gaussian-Process-Modulated Renewal Processes with Application to Medical Event Data

Thomas Lasko Vanderbilt School of Medicine; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:256-263

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Approximating the Bethe Partition Function

Adrian Weller Columbia University, Tony Jebara Columbia University; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:264-273

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Understanding the Bethe approximation: when and how can it go wrong?

Adrian Weller Columbia University, Kui Tang Columbia University, Tony Jebara Columbia University, David Sontag New York University; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:274-283

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Min-$d$-Occur: Ensuring Future Occurrences in Streaming Sets

Vidit Jain Yahoo Labs, Sainyam Galhotra; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:284-293

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Instance Label Prediction by Dirichlet Process Multiple Instance Learning

Melih Kandemir Heidelberg University HCI/IWR, Fred Hamprecht Heidelberg University HCI/IWR; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:294-303

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Transformation Based Probabilistic Clustering using Supervision

Siddharth Gopal Carnegie Mellon University, Yiming Yang Carnegie Mellon University; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:304-313

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Belief-Kinematics Jeffrey’s Rules in the Theory of Evidence

Chunlai Zhou Renmin University of China, Mingyue Wang Syracuse University, Biao Qin Renmin University of China; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:314-323

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Inference Complexity in Continuous Time Bayesian Networks

Liessman Sturlaugson Montana State University, John Sheppard Montana State University; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:324-331

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Bisimulation Metrics are Optimal Value Functions

Norm Ferns École Normale Supérieure, Doina Precup; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:332-341

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Learning to Predict from Crowdsourced Data

Wei Bi, Liwei Wang UIUC, James Kwok, Zhuowen Tu UCSD; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:342-351

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Optimal amortized regret in every interval

Rina Panigrahy, Preyas Popat; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:352-360

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Saturated Conditional Independence with Fixed and Undetermined Sets of Incomplete Random Variables

Henning Koehler Massey University, Sebastian Link; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:361-370

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Latent Kullback Leibler Control for Continuous-State Systems using Probabilistic Graphical Models

Takamitsu Matsubara NAIST, Vicenç Gómez Radboud University Nijmegen, Hilbert Kappen Radboud University; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:371-380

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HELM: Highly Efficient Learning of Mixed copula networks

Yaniv Tenzer Huji, Gal Elidan; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:381-390

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Lifted Tree-Reweighted Variational Inference

Hung Bui Nuance, Tuyen Huynh Jon von Neumann Institute Vietnam National University Ho Chi Minh City, David Sontag New York University; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:391-400

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Generating structure of latent variable models for nested data

Masakazu Ishihata NTT Communication Science Labo, Tomoharu Iwata NTT Communication Science Laboratories; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:401-410

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Batch-Mode Active Learning via Error Bound Minimization

Quanquan Gu CS UIUC, Tong Zhang Rutgers University, Jiawei Han CS UIUC; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:411-420

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Recursive Best-First AND/OR Search for Graphical Models

Akihiro Kishimoto, Radu Marinescu; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:421-430

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A Unified Approach to Fast Algorithms for Submodular Optimization based on Continuous Relaxations and Rounding

Rishabh Iyer, Stefanie Jegelka, Jeffrey Bilmes; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:431-440

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Efficient Sparse Recovery via Adaptive Non-Convex Regularizers with Oracle Property

Ming Lin Tsinghua University, Rong Jin Michigan State University, Changshui Zhang Tsinghua University; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:441-450

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Can(Plan)+: Extending the Operational Semantics for the BDI architecture to deal with Uncertain Information

Kim Bauters Queen’s University Belfast, Weiru Liu Queen’s University Belfast, Jun Hong Queen’s University Belfast, Carles Sierra IIIA CSIC, Lluis Godo Artificial Intelligence Research Institute; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:451-460

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Markov Network Structure Learning via Ensemble-of-Forests Models

Eirini Arvaniti, Manfred Claassen; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:461-470

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Fast Ridge Regression with Randomized Principal Component Analysis and Gradient Descent

Yichao Lu, Dean Foster; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:471-478

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Efficient Regret Bounds for Online Bid Optimisation in Budget-Limited Sponsored Search Auctions

Long Tran-Thanh, Lampros Stavrogiannis, Victor Naroditskiy, Valentin Robu, Nicholas Jennings, Peter Key; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:479-488

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Correlated Compressive Sensing for Networked Data

Tianlin Shi Tsinghua University, Da Tang, Liwen Xu, Thomas Moscibroda; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:489-498

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Adaptive Monotone Shrinkage for Regression

Zhuang Ma, Dean Foster, Robert Stine; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:499-508

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Active Learning of Linear Embeddings for Gaussian Processes

Roman Garnett, Michael Osborne, Philipp Hennig; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:509-518

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Asymptotically Exact, Embarrassingly Parallel MCMC

Willie Neiswanger Carnegie Mellon University, Eric Xing Carnegie Mellon University, Chong Wang; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:519-528

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Position-Aware ListMLE: A Sequential Learning Process for Ranking

Yanyan Lan ICT, Yadong Zhu ICT, Jiafeng Guo ICT, Shuzi Niu ICT, Xueqi Cheng ICT; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:529-538

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Venn-Abers Predictors

Vladimir Vovk Royal Holloway, Ivan Petej; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:539-548

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Metrics for Probabilistic Geometry

Alessandra Tosi UPC, Søren Hauberg Technical University of Denmar, Alfredo Vellido UPC, Neil Lawrence; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:549-557

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A variational approach to stable principal component pursuit

Aleksandr Aravkin, Stephen Becker, Volkan Cevher, Peder Olsen; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:558-567

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Model Regularization for Stable Sample Rollouts

Erik Talvitie Franklin & Marshall College; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:568-577

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Approximate Decentralized Bayesian Inference

Trevor Campbell, Jonathan How; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:578-587

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Continuously indexed Potts models on unoriented graphs

Loic Landrieu, Guillaume Obozinski Ecole des Ponts ParisTech; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:588-597

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GPS-ABC: Gaussian Process Surrogate Approximate Bayesian Computation

Edward Meeds, Max Welling; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:598-607

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Interactive Learning from Unlabelled Instructions

Jonathan Grizou, Luis Montesano Universidad de Zaragoza, Iñaki Iturrate, Manuel Lopes; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:608-617

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SPPM: Sparse Privacy Preserving Mappings

Salman Salamatian, Nadia Fawaz Technicolor, Branislav Kveton Technicolor Labs, Nina Taft Technicolor; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:618-627

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Nonparametric Clustering with Distance Dependent Hierarchies

Soumya Ghosh Brown University, Michalis Raptis, Leonid Sigal Disney Research, Erik Sudderth Brown University; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:628-637

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Modeling Citation Networks using Latent Random Offsets

Willie Neiswanger Carnegie Mellon University, Chong Wang, Qirong Ho Carnegie Mellon University, Eric Xing Carnegie Mellon University; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:638-647

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Quantifying Nonlocal Informativeness in High-Dimensional, Loopy Gaussian Graphical Models

Daniel Levine, Jonathan How; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:648-656

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Message Passing for Soft Constraint Dual Decomposition

David Belanger, Alexandre Passos, Sebastian Riedel, Andrew McCallum; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:657-666

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Learning Partial Policies to Speedup MDP Tree Search

Jervis Pinto Oregon State University, Alan Fern Oregon State University; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:667-676

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Bayesian Filtering with Online Gaussian Process Latent Variable Models

Yali Wang, Marcus Brubaker Toyota Technological Institute at Chicago, Brahim Chaib-draa, Raquel Urtasun; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:677-685

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Improved Densification of One Permutation Hashing

Anshumali Shrivastava Cornell University, Ping Li Rutgers University; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:686-695

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Parallel Markov Chain Monte Carlo for Pitman-Yor Mixture Models

Kumar Avinava Dubey, Sinead Williamson, Eric P. Xing; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:696-705

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Sequential Model-Based Ensemble Optimization

Alexandre Lacoste Laval University, Hugo Larochelle, Mario Marchand Laval University, François Laviolette Laval University; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:706-714

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Nuclear Norm Regularized Least Squares Optimization on Grassmannian Manifolds

Yuanyuan Liu CUHK, Fanhua Shang, Hong Cheng, James Cheng; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:715-724

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Bayesian Inference in Treewidth-Bounded Graphical Models Without Indegree Constraints

Daniel J. Rosenkrantz, Madhav V.Marathe Virginia Tech, S. S. Ravi, Anil K. Vullikanti Virginia Tech; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:725-734

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Structured Proportional Jump Processes

Tal El-Hay, Omer Weissbrod, Elad Eban, Maurizio Zazzi, Francesca Incardona; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:735-744

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A Spectral Algorithm for Learning Class-Based $n$-gram Models of Natural Language

Karl Stratos Columbia University, Do-kyum Kim, Daniel Hsu Columbia University, Michael Collins Columbia University; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:745-754

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A Hierarchical Switching Linear Dynamical System Applied to the Detection of Sepsis in Neonatal Condition Monitoring

Ioan Stanculescu, Christopher K.I. Williams, Yvonne Freer; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:755-764

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Efficient Bayesian Nonparametric Modelling of Structured Point Processes

Tom Gunter, Chris Lloyd, Stephen Roberts, Michael A. Osborne; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:765-774

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Learning Peptide-Spectrum Alignment Models for Tandem Mass Spectrometry

John Halloran, Jeffrey Bilmes, William Noble; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:775-784

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Stochastic Discriminative EM

Andres Masegosa; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:785-794

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Accelerating MCMC via Parallel Predictive Prefetching

Elaine Angelino Harvard University, Eddie Kohler Harvard University, Margo Seltzer Harvard University, Amos Waterland Harvard University, Ryan Adams Harvard; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:795-804

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Understanding the Complexity of Lifted Inference and Asymmetric Weighted Model Counting

Eric Gribkoff, Guy Van Den Broeck, Dan Suciu UW; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:805-814

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Scalable Binary Tensor Factorization

Beyza Ermiş Boğaziçi University, Guillaume Bouchard Xerox Research Centre Europe; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:815-822

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Closed-form Solutions to a Subclass of Continuous Stochastic Games via Symbolic Dynamic Programming

Shamin Kinathil, Scott Sanner, Nicolás Della Penna; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:823-832

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Estimating causal effects by bounding confounding

Philipp Geiger, Dominik Janzing; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:833-842

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Fast Gaussian Process Posteriors with Product Trees

David Moore, Stuart Russell; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:843-852

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MEMR: A Margin Equipped Monotone Retargeting Framework for Ranking

Sreangsu Acharyya, Joydeep Ghosh; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:853-862

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CoRE Kernels

Ping Li Rutgers University; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:863-871

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A Consistent Estimator of the Expected Gradient Outerproduct

Shubhendu Trivedi Toyota Technological Institute, Jialei Wang, Samory Kpotufe TTI-Chicago, Gregory Shakhnarovich TT-Chicago; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:872-881

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Off-policy TD($ł$) with a true online equivalence

Hado Van Hasselt, Rupam Mahmood, Rich Sutton; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:882-891

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Bayesian Interactive Decision Support for Multi-Attribute Problems with Even Swaps

Debarun Bhattacharjya, Jeffrey Kephart; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:892-901

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Multi-label Image Classification with A Probabilistic Label Enhancement Model

Xin Li Temple University, Feipeng Zhao Temple University, Yuhong Guo Temple University; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:902-911

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Combining predictions from linear models when training and test inputs differ

Thijs Van Ommen CWI Amsterdam; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:912-921

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A Bayesian Nonparametric Model for Spectral Estimation of Metastable Systems

Hao Wu Free University of Berlin; Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence, PMLR R12:922-931

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