The 32nd Uncertainty in Artificial Intelligence Conference: Preface

Alexander Ihler, Dominik Janzing; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:1-7

[abs][Download PDF]

Characterizing Tightness of LP Relaxations by Forbidding Signed Minors

Adrian Weller; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:8-17

[abs][Download PDF]

Correlated Tag Learning in Topic Model

Shuangyin Li, Rong Pan Sun Yat-sen University, Yu Zhang, Qiang Yang Hong Kong University of Science and Technology; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:18-27

[abs][Download PDF]

Lighter-Communication Distributed Machine Learning via Sufficient Factor Broadcasting

Pengtao Xie Carnegie Mellon University, Jin Kyu Kim Carnegie Mellon University, Yi Zhou Syracuse University, Qirong Ho, Abhimanu Kumar Groupon Inc., Yaoliang Yu, Eric Xing Carnegie Mellon University; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:28-37

[abs][Download PDF]

Unsupervised Discovery of El Nino Using Causal Feature Learning on Microlevel Climate Data

Krzysztof Chalupka Caltech, Tobias Bischoff Caltech, Frederick Eberhardt, Pietro Perona Caltech; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:38-47

[abs][Download PDF]

Online Bayesian Multiple Kernel Bipartite Ranking

Changying Du, Changde Du, Guoping Long, Qing He, Yucheng Li; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:48-57

[abs][Download PDF]

Alternative Markov and Causal Properties for Acyclic Directed Mixed Graphs

Jose M. Peña; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:58-67

[abs][Download PDF]

Overdispersed Black-Box Variational Inference

Francisco Ruiz Columbia University, Michalis Titsias Athens University of Economics Business, david Blei Columbia and University; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:68-77

[abs][Download PDF]

Dantzig Selector with an Approximately Optimal Denoising Matrix and its Application in Sparse Reinforcement Learning

Bo Liu Auburn University, Luwan Zhang, Ji Liu; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:78-87

[abs][Download PDF]

Thompson Sampling is Asymptotically Optimal in General Environments

Jan Leike, Tor Lattimore, Laurent Orseau, Marcus Hutter; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:88-97

[abs][Download PDF]

Bounded Rational Decision-Making in Feedforward Neural Networks

Felix Leibfried, Daniel Braun; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:98-107

[abs][Download PDF]

Efficient Multi-Class Selective Sampling on Graphs

Peng Yang, Peilin Zhao, Zhen Hai, Wei Liu, Steven C.H. Hoi, Xiao-Li Li; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:108-117

[abs][Download PDF]

On the Theory and Practice of Privacy-Preserving Bayesian Data Analysis

James Foulds, Joseph Geumlek, Max Welling, Kamalika Chaudhuri; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:118-127

[abs][Download PDF]

A Characterization of Markov Equivalence Classes of Relational Causal Models under Path Semantics

Sanghack Lee Penn State University, Vasant Honavar Penn State University; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:128-137

[abs][Download PDF]

Political Dimensionality Estimation Using a Probabilistic Graphical Model

Yoad Lewenberg, Yoram Bachrach, Lucas Bordeaux, Pushmeet Kohli; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:138-147

[abs][Download PDF]

Hierarchical learning of grids of microtopics

Nebojsa Jojic, Alessandro Perina, Dongwoo Kim; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:148-157

[abs][Download PDF]

Pruning Rules for Learning Parsimonious Context Trees

Ralf Eggeling, Mikko Koivisto; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:158-167

[abs][Download PDF]

Improving Imprecise Compressive Sensing Models

Dongeun Lee UNIST, Rafael de Lima, Jaesik Choi; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:168-177

[abs][Download PDF]

Safely Interruptible Agents

Laurent Orseau, Stuart Armstrong Future of Humanity Institute; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:178-187

[abs][Download PDF]

Merging Strategies for Sum-Product Networks: From Trees to Graphs

Tahrima Rahman, Vibhav Gogate; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:188-197

[abs][Download PDF]

Bayesian Hyperparameter Optimization for Ensemble Learning

Julien-Charles Levesque, Christian Gagne, Robert Sabourin Ecole de Technologie Superieure; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:198-207

[abs][Download PDF]

Interpretable Policies for Dynamic Product Recommendations

Marek Petrik, Ronny Luss; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:208-217

[abs][Download PDF]

Convergence Rates for Greedy Kaczmarz Algorithms, and Randomized Kaczmarz Rules Using the Orthogonality Graph

Julie Nutini, Behrooz Sepehry, Issam Laradji, Mark Schmidt, Hoyt Koepke Dato, Alim Virani; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:218-227

[abs][Download PDF]

Structured Prediction: From Gaussian Perturbations to Linear-Time Principled Algorithms

Jean Honorio Purdue University, Tommi Jaakkola; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:228-235

[abs][Download PDF]

Efficient Observation Selection in Probabilistic Graphical Models Using Bayesian Lower Bounds

Dilin Wang Dartmouth College, John Fisher III, Qiang Liu Dartmouth College; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:236-245

[abs][Download PDF]

Efficient Feature Group Sequencing for Anytime Linear Prediction

Hanzhang Hu Carnegie Mellon University, Alexander Grubb, J. Andrew Bagnell, Martial Hebert; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:246-255

[abs][Download PDF]

A Formal Solution to the Grain of Truth Problem

Jan Leike, Jessica Taylor Machine Intelligence Research Institute, Benya Fallenstein Machine Intelligence Research Institute; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:256-265

[abs][Download PDF]

Convex Relaxation Regression: Black-Box Optimization of Smooth Functions by Learning Their Convex Envelopes

Mohamm Gheshlaghi Azar Northwestern University, Eva Dyer Northwestern University, Konrad Kording Northwestern University; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:266-275

[abs][Download PDF]

Model-Free Reinforcement Learning with Skew-Symmetric Bilinear Utilities

Hugo Gilbert LIP6-UPMC, Bruno Zanuttini, Paul Weng SYSU-CMU JIE, Paolo Viappiani Lip6 Paris, Esther Nicart Cordon Electronics DS2i; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:276-285

[abs][Download PDF]

Cascading Bandits for Large-Scale Recommendation Problems

Shi Zong, Hao Ni, Kenny Sung, Rosemary Ke, Zheng Wen Adobe Research, Branislav Kveton Adobe Research; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:286-295

[abs][Download PDF]

Training Neural Nets to Aggregate Crowdsourced Responses

Alex Gaunt, Diana Borsa UCL, Yoram Bachrach; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:296-305

[abs][Download PDF]

Quasi-Newton Hamiltonian Monte Carlo

Tianfan Fu Shanghai Jiao Tong University, Luo Luo Shanghai Jiao Tong University, Zhihua Zhang Shanghai Jiao Tong University; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:306-315

[abs][Download PDF]

Utilize Old Coordinates: Faster Doubly Stochastic Gradients for Kernel Methods

Chun-Liang Li Carnegie Mellon University, Barnabas Poczos Carnegie Mellon University; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:316-325

[abs][Download PDF]

Adversarial Inverse Optimal Control for General Imitation Learning Losses and Embodiment Transfer

Xiangli Chen UIC, Mathew Monfort, Brian Ziebart, Peter Carr; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:326-335

[abs][Download PDF]

Budgeted Semi-supervised Support Vector Machine

Trung Le, Phuong Duong, Mi Dinh, Tu Dinh Nguyen, Vu Nguyen, Dinh Phung; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:336-345

[abs][Download PDF]

Online Forest Density Estimation

Frederic Koriche CRIL; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:346-355

[abs][Download PDF]

Markov Beta Processes for Time Evolving Dictionary Learning

Amar Shah, Zoubin Ghahramani; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:356-365

[abs][Download PDF]

Content-based Modeling of Reciprocal Relationships using Hawkes and Gaussian Processes

Xi Tan, Syed A. Z. Naqvi, Yuan Qi, Katherine Heller, Vinayak Rao; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:366-374

[abs][Download PDF]

Forward Backward Greedy Algorithms for Multi-Task Learning with Faster Rates

Lu Tian, Pan Xu, Quanquan Gu; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:375-384

[abs][Download PDF]

Learning to Smooth with Bidirectional Predictive State Inference Machines

Wen Sun Carnegie Mellon University, Roberto Capobianco Sapienza University of Rome, Geoffrey J. Gordon Carnegie Mellon University, J. Andrew Bagnell, Byron Boots Georgia Institute of Technology; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:385-394

[abs][Download PDF]

Adaptive Algorithms and Data-Dependent Guarantees for Bandit Convex Optimization

Scott Yang Courant Institute of Mathemati, Mehryar Mohri Courant Institute of Mathematical Sciences; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:395-404

[abs][Download PDF]

Bayesian Learning of Kernel Embeddings

Seth Flaxman, Dino Sejdinovic, John Cunningham Columbia University, Sarah Filippi; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:405-414

[abs][Download PDF]

A Generative Block-Diagonal Model for Clustering

Junxiang Chen Northeastern University, Jennifer Dy; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:415-424

[abs][Download PDF]

Elliptical Slice Sampling with Expectation Propagation

Francois Fagan Columbia University, Jalaj Bhandari Columbia University, John Cunningham Columbia University; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:425-434

[abs][Download PDF]

Scalable Joint Modeling of Longitudinal and Point Process Data for Disease Trajectory Prediction and Improving Management of Chronic Kidney Disease

Joseph Futoma Duke University, Mark Sendak Duke University, Blake Cameron Duke University, Katherine Heller Duke University; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:435-444

[abs][Download PDF]

Probabilistic Size-constrained Microclustering

Arto Klami, Aditya Jitta; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:445-454

[abs][Download PDF]

Active Uncertainty Calibration in Bayesian ODE Solvers

Hans Kersting MPI for Intelligent Systems, Philipp Hennig MPI for Intelligent Systems; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:455-464

[abs][Download PDF]

Gradient Methods for Stackelberg Games

Kareem Amin, Michael Wellman, Satinder Singh; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:465-474

[abs][Download PDF]

Optimal Stochastic Strongly Convex Optimization with a Logarithmic Number of Projections

Jianhui Chen Yahoo, Tianbao Yang, Qihang Lin, Lijun Zhang Nanjing University, Yi Chang Yahoo!; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:475-484

[abs][Download PDF]

Subspace Clustering with a Twist

David Wipf, Yue Dong, Bo Xin Peking University; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:485-494

[abs][Download PDF]

Bounded Rationality in Wagering Mechanisms

David Pennock, Vasilis Syrgkanis, Jennifer Wortman Vaughan; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:495-504

[abs][Download PDF]

Bridging Heterogeneous Domains With Parallel Transport For Vision and Multimedia Applications

Raghuraman Gopalan AT&T Research; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:505-513

[abs][Download PDF]

A General Statistical Framework for Designing Strategy-proof Assignment Mechanisms

Harikrishna Narasimhan Harvard University, David Parkes Harvard University; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:514-523

[abs][Download PDF]

Accelerated Stochastic Block Coordinate Gradient Descent for Sparsity Constrained Nonconvex Optimization

Jinghui Chen, Quanquan Gu; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:524-533

[abs][Download PDF]

Incremental Preference Elicitation for Decision Making Under Risk with the Rank-Dependent Utility Model

Patrice Perny LIP6, Paolo Viappiani Lip6 Paris, abdellah Boukhatem LIP6; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:534-543

[abs][Download PDF]

Online learning with Erdos-Renyi side-observation graphs

Tomáš Kocák, Gergely Neu, Michal Valko; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:544-551

[abs][Download PDF]

Stability of Causal Inference

Leonard Schulman California Institute of Technology, Piyush Srivastava California Institute of Techno; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:552-561

[abs][Download PDF]

Inferring Causal Direction from Relational Data

David Arbour, Katerina Marazopoulou, David Jensen; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:562-571

[abs][Download PDF]

Faster Stochastic Variational Inference using Proximal-Gradient Methods with General Divergence Functions

Mohammad Emtiyaz Khan, Reza Babanezhad Harikandeh UBC, Wu Lin, Mark Schmidt, Masashi Sugiyama; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:572-581

[abs][Download PDF]

Taming the Noise in Reinforcement Learning via Soft Updates

Roy Fox HUJI, Ari Pakman Columbia University, Naftali Tishby HUJI; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:582-591

[abs][Download PDF]

Conjugate Conformal Prediction for Online Binary Classification

Mustafa Kocak NYU Tandon SoE, Dennis Shasha Courant Institute of Mathematical Sciences New York University, Elza Erkip NYU Tandon School of Engineering; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:592-601

[abs][Download PDF]

Large-scale Submodular Greedy Exemplar Selection with Structured Similarity Matrices

Dmitry Malioutov, Abhishek Kumar, Ian Yen; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:602-611

[abs][Download PDF]

Finite Sample Complexity of Rare Pattern Anomaly Detection

Md Amran Siddiqui Oregon Sate University, Alan Fern, Thomas Dietterich Oregon State University, Shubhomoy Das Oregon State University; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:612-621

[abs][Download PDF]

Towards a Theoretical Understanding of Negative Transfer in Collective Matrix Factorization

Chao Lan, Jianxin Wang, Jun Huan; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:622-631

[abs][Download PDF]

Importance Weighted Consensus Monte Carlo for Distributed Bayesian Inference

Qiang Liu Dartmouth College; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:632-641

[abs][Download PDF]

A Correlated Worker Model for Grouped, Imbalanced and Multitask Data

An Nguyen, Byron Wallace, Matthew Lease; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:642-651

[abs][Download PDF]

The Mondrian Kernel

Matej Balog, Balaji Lakshminarayanan, Zoubin Ghahramani, Daniel Roy, Yee Whye Teh; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:652-661

[abs][Download PDF]

Learning Network of Multivariate Hawkes Processes: A Time Series Approach

Jalal Etesami, Negar Kiyavash, Kun Zhang, Kushagra Singhal; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:662-671

[abs][Download PDF]

Bayesian Estimators As Voting Rules

Lirong Xia; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:672-681

[abs][Download PDF]

Budget Allocation using Weakly Coupled, Constrained Markov Decision Processes

Craig Boutilier, Tyler Lu; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:682-691

[abs][Download PDF]

A Kernel Test for Three-Variable Interactions with Random Processes

Paul Rubenstein, Kacper Chwialkowski UCL / Gatsby Unit, Arthur Gretton Gatsby Unit; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:692-701

[abs][Download PDF]

Context-dependent feature analysis with random forests

Antonio Sutera, Gilles Louppe, Vân Anh Huynh-Thu, Louis Wehenkel, Pierre Geurts; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:702-711

[abs][Download PDF]

Analysis of Nyström method with sequential ridge leverage scores

Daniele Calandriello, Alessandro Lazaric, Michal Valko; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:712-721

[abs][Download PDF]

Degrees of Freedom in Deep Neural Networks

Tianxiang Gao, Vladimir Jojic; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:722-731

[abs][Download PDF]

Scalable Nonparametric Bayesian Multilevel Clustering

Viet Huynh, Dinh Phung, Svetha Venkatesh, XuanLong Nguyen, Matthew Hoffman, Hung Bui; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:732-741

[abs][Download PDF]

On Hyper-Parameter Estimation In Empirical Bayes: A Revisit of The MacKay Algorithm

Chune Li Beihang University, Yongyi Mao, Richong Zhang Beihang University, Jinpeng Huai Beihang University; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:742-751

[abs][Download PDF]

Modeling Transitivity in Complex Networks

Morteza Haghir Chehreghani Xerox Research Centre Europe, Mostafa Haghir Chehreghani KU Leuven; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:752-761

[abs][Download PDF]

Sparse Gaussian Processes for Bayesian Optimization

Mitchell McIntire, Daniel Ratner SLAC National Accelerator Laboratory, Stefano Ermon; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:762-771

[abs][Download PDF]

Sequential Nonparametric Testing with the Law of the Iterated Logarithm

Akshay Balsubramani, Aaditya Ramdas; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:772-781

[abs][Download PDF]

Stochastic Portfolio Theory: A Machine Learning Approach

Yves-Laurent Kom Samo, Alexander Vervuurt; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:782-790

[abs][Download PDF]

Individual Planning in Open and Typed Agent Systems

Muthukumaran Chandrasekaran, Adam Eck, Prashant Doshi, Leenkiat Soh; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:791-800

[abs][Download PDF]

Super-Sampling with a Reservoir

Brooks Paige, Dino Sejdinovic, Frank Wood; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:801-810

[abs][Download PDF]

MDPs with Unawareness in Robotics

Nan Rong Cornell University, Joseph Halpern Cornell University, Ashutosh Saxena Cornell University; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:811-820

[abs][Download PDF]

On the Identifiability and Estimation of Functional Causal Models in the Presence of Outcome-Dependent Selection

Kun Zhang, Jiji Zhang, Biwei Huang MPI, Bernhard Schoelkopf, Clark Glymour; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:821-830

[abs][Download PDF]

Non-parametric Domain Approximation for Scalable Gibbs Sampling in MLNs

Deepak Venugopal, Somdeb Sarkhel, Kyle Cherry; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:831-840

[abs][Download PDF]

The Deterministic Information Bottleneck

DJ Strouse Princeton University, david Schwab Northwestern University; Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:841-850

[abs][Download PDF]