UAI 2015

110 papers

(Nearly) Optimal Differentially Private Stochastic Multi-Arm Bandits Nikita Mishra, Abhradeep Thakurta

A Complete Generalized Adjustment Criterion Emilija Perkovic, Johannes Textor, Markus Kalisch, Marloes H. Maathuis

A Finite Population Likelihood Ratio Test of the Sharp Null Hypothesis for Compliers Wen Wei Loh, Thomas S. Richardson

A Markov Game Model for Valuing Player Actions in Ice Hockey Kurt Routley, Oliver Schulte

A Probabilistic Logic for Reasoning About Uncertain Temporal Information Dragan Doder, Zoran Ognjanovic

A Smart-Dumb/Dumb-Smart Algorithm for Efficient Split-Merge MCMC Wei Wang, Stuart Russell

Active Search and Bandits on Graphs Using Sigma-Optimality Yifei Ma, Tzu-Kuo Huang, Jeff G. Schneider

Adversarial Cost-Sensitive Classification Kaiser Asif, Wei Xing, Sima Behpour, Brian D. Ziebart

An Empirical Study of the Simplest Causal Prediction Algorithm Jerome Cremers, Joris M. Mooij

An IRT-Based Parameterization for Conditional Probability Tables Russell G. Almond

An Upper Bound on the Global Optimum in Parameter Estimation Khaled S. Refaat, Adnan Darwiche

Annealed Gradient Descent for Deep Learning Hengyue Pan, Hui Jiang

Are You Doing What I Think You Are Doing? Criticising Uncertain Agent Models Stefano V. Albrecht, Subramanian Ramamoorthy

Auxiliary Gibbs Sampling for Inference in Piecewise-Constant Conditional Intensity Models Zhen Qin, Christian R. Shelton

Averaging of Decomposable Graphs by Dynamic Programming and Sampling Kustaa Kangas, Teppo Mikael Niinimäki, Mikko Koivisto

Bayes Optimal Feature Selection for Supervised Learning with General Performance Measures C. G. Saneem Ahmed, Harikrishna Narasimhan, Shivani Agarwal

Bayesian Network Learning with Discrete Case-Control Data Giorgos Borboudakis, Ioannis Tsamardinos

Bayesian Network Models for Adaptive Testing Martin Plajner, Jirí Vomlel

Bayesian Optimal Control of Smoothly Parameterized Systems Yasin Abbasi-Yadkori, Csaba Szepesvári

Bayesian Optimisation of Gated Bayesian Networks for Algorithmic Trading Marcus Bendtsen

Bayesian Predictive Modelling: Application to Aircraft Short-Term Conflict Alert System Vitaly Schetinin, Livia Jakaite, Wojtek J. Krzanowski

Bayesian Structure Learning for Stationary Time Series Alex Tank, Nicholas J. Foti, Emily B. Fox

Bethe and Related Pairwise Entropy Approximations Adrian Weller

Bethe Projections for Non-Local Inference Luke Vilnis, David Belanger, Daniel Sheldon, Andrew McCallum

Budget Constraints in Prediction Markets Nikhil R. Devanur, Miroslav Dudík, Zhiyi Huang, David M. Pennock

Budgeted Online Collective Inference Jay Pujara, Ben London, Lise Getoor

Causal Reasoning for Events in Continuous Time: A Decision - Theoretic Approach Vanessa Didelez

Classification of Sparse and Irregularly Sampled Time Series with Mixtures of Expected Gaussian Kernels and Random Features Steven Cheng-Xian Li, Benjamin M. Marlin

Clustered Sparse Bayesian Learning Yu Wang, David P. Wipf, Jeong-Min Yun, Wei Chen, Ian J. Wassell

Communication Efficient Coresets for Empirical Loss Minimization Sashank J. Reddi, Barnabás Póczos, Alexander J. Smola

Complexity of the Exact Solution to the Test Sequencing Problem Wenhao Liu, Ross D. Shachter

Computer Adaptive Testing Using the Same-Decision Probability Suming Jeremiah Chen, Arthur Choi, Adnan Darwiche

Computing Optimal Bayesian Decisions for Rank Aggregation via MCMC Sampling David Hughes, Kevin Hwang, Lirong Xia

Disciplined Convex Stochastic Programming: A New Framework for Stochastic Optimization Alnur Ali, J. Zico Kolter, Steven Diamond, Stephen P. Boyd

Discriminative Switching Linear Dynamical Systems Applied to Physiological Condition Monitoring Konstantinos Georgatzis, Christopher K. I. Williams

Do-Calculus When the True Graph Is Unknown Antti Hyttinen, Frederick Eberhardt, Matti Järvisalo

Effcient Transition Probability Computation for Continuous-Time Branching Processes via Compressed Sensing Jason Xu, Vladimir N. Minin

Efficient Algorithms for Bayesian Network Parameter Learning from Incomplete Data Guy Van den Broeck, Karthika Mohan, Arthur Choi, Adnan Darwiche, Judea Pearl

Encoding Markov Logic Networks in Possibilistic Logic Ondrej Kuzelka, Jesse Davis, Steven Schockaert

Equitable Partitions of Concave Free Energies Martin Mladenov, Kristian Kersting

Estimating Mutual Information by Local Gaussian Approximation Shuyang Gao, Greg Ver Steeg, Aram Galstyan

Estimating the Partition Function by Discriminance Sampling Qiang Liu, Jian Peng, Alexander Ihler, John W. Fisher Iii

Extend Transferable Belief Models with Probabilistic Priors Chunlai Zhou, Yuan Feng

Fast Algorithms for Learning with Long N-Grams via Suffix Tree Based Matrix Multiplication Hristo S. Paskov, John C. Mitchell, Trevor J. Hastie

Fast Relative-Error Approximation Algorithm for Ridge Regression Shouyuan Chen, Yang Liu, Michael R. Lyu, Irwin King, Shengyu Zhang

Finite-Sample Analysis of Proximal Gradient TD Algorithms Bo Liu, Ji Liu, Mohammad Ghavamzadeh, Sridhar Mahadevan, Marek Petrik

Generalization Bounds for Transfer Learning Under Model Shift Xuezhi Wang, Jeff G. Schneider

Geometric Network Comparisons Dena Marie Asta, Cosma Rohilla Shalizi

Hamiltonian ABC Edward Meeds, Robert Leenders, Max Welling

Hashing-Based Approximate Probabilistic Inference in Hybrid Domains Vaishak Belle, Guy Van den Broeck, Andrea Passerini

How Matroids Occur in the Context of Learning Bayesian Network Structure Milan Studený

Impact of Learning Strategies on the Quality of Bayesian Networks: An Empirical Evaluation Brandon M. Malone, Matti Järvisalo, Petri Myllymäki

Importance Sampling over Sets: A New Probabilistic Inference Scheme Stefan Hadjis, Stefano Ermon

Improved Asymmetric Locality Sensitive Hashing (ALSH) for Maximum Inner Product Search (MIPS) Anshumali Shrivastava, Ping Li

Incremental Region Selection for Mini-Bucket Elimination Bounds Sholeh Forouzan, Alexander Ihler

Influence Diagrams for the Optimization of a Vehicle Speed Profile Václav Kratochvíl, Jirí Vomlel

Intelligent Affect: Rational Decision Making for Socially Aligned Agents Nabiha Asghar, Jesse Hoey

Kernel-Based Just-in-Time Learning for Passing Expectation Propagation Messages Wittawat Jitkrittum, Arthur Gretton, Nicolas Heess, S. M. Ali Eslami, Balaji Lakshminarayanan, Dino Sejdinovic, Zoltán Szabó

Large-Margin Determinantal Point Processes Wei-Lun Chao, Boqing Gong, Kristen Grauman, Fei Sha

Large-Scale Randomized-Coordinate Descent Methods with Non-Separable Linear Constraints Sashank J. Reddi, Ahmed Hefny, Carlton Downey, Avinava Dubey, Suvrit Sra

Learning and Inference in Tractable Probabilistic Knowledge Bases Mathias Niepert, Pedro M. Domingos

Learning and Planning with Timing Information in Markov Decision Processes Pierre-Luc Bacon, Borja Balle, Doina Precup

Learning from Pairwise Marginal Independencies Johannes Textor, Alexander Idelberger, Maciej Liskiewicz

Learning Latent Variable Models by Improving Spectral Solutions with Exterior Point Method Amirreza Shaban, Mehrdad Farajtabar, Bo Xie, Le Song, Byron Boots

Learning Optimal Chain Graphs with Answer Set Programming Dag Sonntag, Matti Järvisalo, José M. Peña, Antti Hyttinen

Learning the Structure of Causal Models with Relational and Temporal Dependence Katerina Marazopoulou, Marc E. Maier, David D. Jensen

Learning the Structure of Sum-Product Networks via an SVD-Based Algorithm Tameem Adel, David Balduzzi, Ali Ghodsi

Lifted Representation of Relational Causal Models Revisited: Implications for Reasoning and Structure Learning Sanghack Lee, Vasant G. Honavar

Locally Conditioned Belief Propagation Thomas Geier, Felix Richter, Susanne Biundo

Max-Product Belief Propagation for Linear Programming: Applications to Combinatorial Optimization Sejun Park, Jinwoo Shin

Memory-Effcient Symbolic Online Planning for Factored MDPs Aswin Raghavan, Roni Khardon, Prasad Tadepalli, Alan Fern

Mesochronal Structure Learning Sergey M. Plis, David Danks, Jianyu Yang

Minimizing Expected Losses in Perturbation Models with Multidimensional Parametric Min-Cuts Adrian Kim, Kyomin Jung, Yongsub Lim, Daniel Tarlow, Pushmeet Kohli

Missing Data as a Causal and Probabilistic Problem Ilya Shpitser, Karthika Mohan, Judea Pearl

Multi-Context Models for Reasoning Under Partial Knowledge: Generative Process and Inference Grammar Ardavan Salehi Nobandegani, Ioannis N. Psaromiligkos

Multitasking: Optimal Planning for Bandit Superprocesses Dylan Hadfield-Menell, Stuart Russell

New Limits for Knowledge Compilation and Applications to Exact Model Counting Paul Beame, Vincent Liew

Non-Parametric Revenue Optimization for Generalized Second Price Auctions Mehryar Mohri, Andres Muñoz Medina

Novel Bernstein-like Concentration Inequalities for the Missing Mass Bahman Yari Saeed Khanloo, Gholamreza Haffari

Off-Policy Learning Based on Weighted Importance Sampling with Linear Computational Complexity Ashique Rupam Mahmood, Richard S. Sutton

On the Computability of AIXI Jan Leike, Marcus Hutter

On the Error of Random Fourier Features Danica J. Sutherland, Jeff G. Schneider

Online Bellman Residual Algorithms with Predictive Error Guarantees Wen Sun, J. Andrew Bagnell

Optimal Expert Elicitation to Reduce Interval Uncertainty Nadia Ben Abdallah, Sébastien Destercke

Optimal Threshold Control for Energy Arbitrage with Degradable Battery Storage Marek Petrik, Xiaojian Wu

Parameterizing the Distance Distribution of Undirected Networks Christian Bauckhage, Kristian Kersting, Fabian Hadiji

Planning Under Uncertainty with Weighted State Scenarios Erwin Walraven, Matthijs T. J. Spaan

Polynomial-Time Algorithm for Learning Optimal Tree-Augmented Dynamic Bayesian Networks José L. Monteiro, Susana Vinga, Alexandra M. Carvalho

Population Empirical Bayes Alp Kucukelbir, David M. Blei

Probabilistic Graphical Models Parameter Learning with Transferred Prior and Constraints Yun Zhou, Norman E. Fenton, Timothy M. Hospedales, Martin Neil

Progressive Abstraction Refinement for Sparse Sampling Jesse Hostetler, Alan Fern, Thomas G. Dietterich

Psychophysical Detection Testing with Bayesian Active Learning Jacob R. Gardner, Xinyu Song, Kilian Q. Weinberger, Dennis L. Barbour, John P. Cunningham

Query-Answer Causality in Databases: Abductive Diagnosis and View Updates Babak Salimi, Leopoldo E. Bertossi

Recovering from Selection Bias Using Marginal Structure in Discrete Models Robin J. Evans, Vanessa Didelez

Representation Learning for Clustering: A Statistical Framework Hassan Ashtiani, Shai Ben-David

Revisiting Non-Progressive Influence Models: Scalable Influence Maximization in Social Networks Golshan Golnari, Amir Asiaee Tabatabaei, Arindam Banerjee, Zhi-Li Zhang

Robust Reconstruction of Causal Graphical Models Based on Conditional 2-Point and 3-Point Information Séverine Affeldt, Hervé Isambert

Scalable Recommendation with Hierarchical Poisson Factorization Prem Gopalan, Jake M. Hofman, David M. Blei

Selective Greedy Equivalence Search: Finding Optimal Bayesian Networks Using a Polynomial Number of Score Evaluations David Maxwell Chickering, Christopher Meek

Semi-Described and Semi-Supervised Learning with Gaussian Processes Andreas C. Damianou, Neil D. Lawrence

Stable Spectral Learning Based on Schur Decomposition Nicolò Colombo, Nikos Vlassis

State Sequence Analysis in Hidden Markov Models Yuri Grinberg, Theodore J. Perkins

Stochastic Integration via Error-Correcting Codes Dimitris Achlioptas, Pei Jiang

Structure Learning Constrained by Node-Specific Degree Distribution Jianzhu Ma, Feng Zhao, Jinbo Xu

The Long-Run Behavior of Continuous Time Bayesian Networks Liessman Sturlaugson, John W. Sheppard

The Survival Filter: Joint Survival Analysis with a Latent Time Series Rajesh Ranganath, Adler J. Perotte, Noémie Elhadad, David M. Blei

Tracking with Ranked Signals Tianyang Li, Harsh H. Pareek, Pradeep Ravikumar, Dhruv Balwada, Kevin Speer

Training Generative Neural Networks via Maximum Mean Discrepancy Optimization Gintare Karolina Dziugaite, Daniel M. Roy, Zoubin Ghahramani

Visual Causal Feature Learning Krzysztof Chalupka, Pietro Perona, Frederick Eberhardt

Zero-Truncated Poisson Tensor Factorization for Massive Binary Tensors Changwei Hu, Piyush Rai, Lawrence Carin