| 2017 | A Fast Algorithm for Matrix Eigen-decompositionn. Zhiqiang Xu, Yiping Ke, Xin Gao |
| 2017 | A Practical Method for Solving Contextual Bandit Problems Using Decision Trees. Adam N. Elmachtoub, Ryan McNellis, Sechan Oh, Marek Petrik |
| 2017 | A Probabilistic Framework for Multi-Label Learning with Unseen Labels. Abhilash Gaure, Aishwarya Gupta, Vinay Kumar Verma, Piyush Rai |
| 2017 | A Reinforcement Learning Approach to Weaning of Mechanical Ventilation in Intensive Care Units. Niranjani Prasad, Li-Fang Cheng, Corey Chivers, Michael Draugelis, Barbara E. Engelhardt |
| 2017 | A Tractable Probabilistic Model for Subset Selection. Yujia Shen, Arthur Choi, Adnan Darwiche |
| 2017 | Adversarial Sets for Regularising Neural Link Predictors. Pasquale Minervini, Thomas Demeester, Tim Rocktäschel, Sebastian Riedel |
| 2017 | Algebraic Equivalence Class Selection for Linear Structural Equation Models. Thijs van Ommen, Joris M. Mooij |
| 2017 | An Efficient Minibatch Acceptance Test for Metropolis-Hastings. Daniel Seita, Xinlei Pan, Haoyu Chen, John F. Canny |
| 2017 | Analysis of Thompson Sampling for Stochastic Sleeping Bandits. Aritra Chatterjee, Ganesh Ghalme, Shweta Jain, Rohit Vaish, Y. Narahari |
| 2017 | Approximate Evidential Reasoning Using Local Conditioning and Conditional Belief Functions. Van Nguyen |
| 2017 | Approximation Complexity of Maximum A Posteriori Inference in Sum-Product Networks. Diarmaid Conaty, Cassio P. de Campos, Denis Deratani Mauá |
| 2017 | AutoGP: Exploring the Capabilities and Limitations of Gaussian Process Models. Karl Krauth, Edwin V. Bonilla, Kurt Cutajar, Maurizio Filippone |
| 2017 | Balanced Mini-batch Sampling for SGD Using Determinantal Point Processes. Cheng Zhang, Hedvig Kjellström, Stephan Mandt |
| 2017 | Bayesian Inference of Log Determinants. Jack K. Fitzsimons, Kurt Cutajar, Maurizio Filippone, Michael A. Osborne, Stephen J. Roberts |
| 2017 | Branch and Bound for Regular Bayesian Network Structure Learing. Joe Suzuki, Jun Kawahara |
| 2017 | Causal Consistency of Structural Equation Models. Paul K. Rubenstein, Sebastian Weichwald, Stephan Bongers, Joris M. Mooij, Dominik Janzing, Moritz Grosse-Wentrup, Bernhard Schölkopf |
| 2017 | Causal Discovery from Temporally Aggregated Time Series. Mingming Gong, Kun Zhang, Bernhard Schölkopf, Clark Glymour, Dacheng Tao |
| 2017 | Communication-Efficient Distributed Primal-Dual Algorithm for Saddle Point Problem. Yaodong Yu, Sulin Liu, Sinno Jialin Pan |
| 2017 | Complexity of Solving Decision Trees with Skew-Symmetric Bilinear Utility. Hugo Gilbert, Olivier Spanjaard |
| 2017 | Composing Inference Algorithms as Program Transformations. Robert Zinkov, Chung-chieh Shan |
| 2017 | Computing Nonvacuous Generalization Bounds for Deep (Stochastic) Neural Networks with Many More Parameters than Training Data. Gintare Karolina Dziugaite, Daniel M. Roy |
| 2017 | Continuously Tempered Hamiltonian Monte Carlo. Matthew M. Graham, Amos J. Storkey |
| 2017 | Convex-constrained Sparse Additive Modeling and Its Extensions. Junming Yin, Yaoliang Yu |
| 2017 | Counting Markov Equivalence Classes by Number of Immoralities. Adityanarayanan Radhakrishnan, Liam Solus, Caroline Uhler |
| 2017 | Coupling Adaptive Batch Sizes with Learning Rates. Lukas Balles, Javier Romero, Philipp Hennig |
| 2017 | Data-Dependent Sparsity for Subspace Clustering. Bo Xin, Yizhou Wang, Wen Gao, David P. Wipf |
| 2017 | Decoupling Homophily and Reciprocity with Latent Space Network Models. Jiasen Yang, Vinayak A. Rao, Jennifer Neville |
| 2017 | Differentially Private Variational Inference for Non-conjugate Models. Joonas Jälkö, Antti Honkela, Onur Dikmen |
| 2017 | Effective sketching methods for value function approximation. Yangchen Pan, Erfan Sadeqi Azer, Martha White |
| 2017 | Efficient Online Learning for Optimizing Value of Information: Theory and Application to Interactive Troubleshooting. Yuxin Chen, Jean-Michel Renders, Morteza Haghir Chehreghani, Andreas Krause |
| 2017 | Efficient solutions for Stochastic Shortest Path Problems with Dead Ends. Felipe W. Trevizan, Florent Teichteil-Königsbuch, Sylvie Thiébaux |
| 2017 | Embedding Senses via Dictionary Bootstrapping. Byungkon Kang, Kyung-Ah Sohn |
| 2017 | Exact Inference for Relational Graphical Models with Interpreted Functions: Lifted Probabilistic Inference Modulo Theories. Rodrigo de Salvo Braz, Ciaran O'Reilly |
| 2017 | FROSH: FasteR Online Sketching Hashing. Xixian Chen, Irwin King, Michael R. Lyu |
| 2017 | Fair Optimal Stopping Policy for Matching with Mediator. Yang Liu |
| 2017 | Fast Amortized Inference and Learning in Log-linear Models with Randomly Perturbed Nearest Neighbor Search. Stephen Mussmann, Daniel Levy, Stefano Ermon |
| 2017 | Feature-to-Feature Regression for a Two-Step Conditional Independence Test. Qinyi Zhang, Sarah Filippi, Seth R. Flaxman, Dino Sejdinovic |
| 2017 | Green Generative Modeling: Recycling Dirty Data using Recurrent Variational Autoencoders. Yu Wang, Bin Dai, Gang Hua, John A. D. Aston, David P. Wipf |
| 2017 | Holographic Feature Representations of Deep Networks. Martin A. Zinkevich, Alex Davies, Dale Schuurmans |
| 2017 | How Good Are My Predictions? Efficiently Approximating Precision-Recall Curves for Massive Datasets. Ashish Sabharwal, Hanie Sedghi |
| 2017 | Hybrid Deep Discriminative/Generative Models for Semi-Supervised Learning. Volodymyr Kuleshov, Stefano Ermon |
| 2017 | Importance Sampled Stochastic Optimization for Variational Inference. Joseph Sakaya, Arto Klami |
| 2017 | Importance Sampling for Fair Policy Selection. Shayan Doroudi, Philip S. Thomas, Emma Brunskill |
| 2017 | Improving Optimization-Based Approximate Inference by Clamping Variables. Junyao Zhao, Josip Djolonga, Sebastian Tschiatschek, Andreas Krause |
| 2017 | Intelligent Robots in an Uncertain World. Leslie Pack Kaelbling |
| 2017 | Interpreting Lion Behaviour as Probabilistic Programs. Neil Dhir, Matthijs Vákár, Matthew Wijers, Andrew Markham, Frank D. Wood |
| 2017 | Interpreting and Using CPDAGs With Background Knowledge. Emilija Perkovic, Markus Kalisch, Marloes H. Maathuis |
| 2017 | Inverse Reinforcement Learning via Deep Gaussian Process. Ming Jin, Andreas C. Damianou, Pieter Abbeel, Costas J. Spanos |
| 2017 | Iterative Decomposition Guided Variable Neighborhood Search for Graphical Model Energy Minimization. Abdelkader Ouali, David Allouche, Simon de Givry, Samir Loudni, Yahia Lebbah, Lakhdar Loukil |
| 2017 | Learning Approximately Objective Priors. Eric T. Nalisnick, Padhraic Smyth |
| 2017 | Learning Treatment-Response Models from Multivariate Longitudinal Data. Hossein Soleimani, Adarsh Subbaswamy, Suchi Saria |
| 2017 | Learning and Inference with Expectations. Amir Globerson |
| 2017 | Learning the Structure of Probabilistic Sentential Decision Diagrams. Yitao Liang, Jessa Bekker, Guy Van den Broeck |
| 2017 | Learning to Acquire Information. Yewen Pu, Leslie Pack Kaelbling, Armando Solar-Lezama |
| 2017 | Learning to Draw Samples with Amortized Stein Variational Gradient Descent. Yihao Feng, Dilin Wang, Qiang Liu |
| 2017 | Learning with Confident Examples: Rank Pruning for Robust Classification with Noisy Labels. Curtis G. Northcutt, Tailin Wu, Isaac L. Chuang |
| 2017 | Machine Learning for Healthcare Data. Katherine A. Heller |
| 2017 | Monte-Carlo Tree Search using Batch Value of Perfect Information. Shahaf S. Shperberg, Solomon Eyal Shimony, Ariel Felner |
| 2017 | Multi-dueling Bandits with Dependent Arms. Yanan Sui, Vincent Zhuang, Joel W. Burdick, Yisong Yue |
| 2017 | Near-Optimal Interdiction of Factored MDPs. Swetasudha Panda, Yevgeniy Vorobeychik |
| 2017 | Near-Orthogonality Regularization in Kernel Methods. Pengtao Xie, Barnabás Póczos, Eric P. Xing |
| 2017 | Neighborhood Regularized l^1-Graph. Yingzhen Yang, Jiashi Feng, Jiahui Yu, Jianchao Yang, Thomas S. Huang |
| 2017 | On Loopy Belief Propagation - Local Stability Analysis for Non-Vanishing Fields. Christian Knoll, Franz Pernkopf |
| 2017 | On the Complexity of Nash Equilibrium Reoptimization. Andrea Celli, Alberto Marchesi, Nicola Gatti |
| 2017 | Online Constrained Model-based Reinforcement Learning. Benjamin van Niekerk, Andreas C. Damianou, Benjamin Rosman |
| 2017 | Probabilistic Program Abstractions. Steven Holtzen, Todd D. Millstein, Guy Van den Broeck |
| 2017 | Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, UAI 2017, Sydney, Australia, August 11-15, 2017 Gal Elidan, Kristian Kersting, Alexander Ihler |
| 2017 | Provable Inductive Robust PCA via Iterative Hard Thresholding. U. N. Niranjan, Arun Rajkumar, Theja Tulabandhula |
| 2017 | Real-Time Resource Allocation for Tracking Systems. Yash Satsangi, Shimon Whiteson, Frans A. Oliehoek, Henri Bouma |
| 2017 | Regret Minimization Algorithms for the Followers Behaviour Identification in Leadership Games. Lorenzo Bisi, Giuseppe De Nittis, Francesco Trovò, Marcello Restelli, Nicola Gatti |
| 2017 | Robust Model Equivalence using Stochastic Bisimulation for N-Agent Interactive DIDs. Muthukumaran Chandrasekaran, Junhuan Zhang, Prashant Doshi, Yifeng Zeng |
| 2017 | SAT-Based Causal Discovery under Weaker Assumptions. Zhalama, Jiji Zhang, Frederick Eberhardt, Wolfgang Mayer |
| 2017 | Safe Semi-Supervised Learning of Sum-Product Networks. Martin Trapp, Tamas Madl, Robert Peharz, Franz Pernkopf, Robert Trappl |
| 2017 | Self-Discrepancy Conditional Independence Test. Sanghack Lee, Vasant G. Honavar |
| 2017 | Shortest Path under Uncertainty: Exploration versus Exploitation. Zhan Wei Lim, David Hsu, Wee Sun Lee |
| 2017 | Snorkel: Beyond Hand-labeled Data. Christopher Ré |
| 2017 | Stein Variational Adaptive Importance Sampling. Jun Han, Qiang Liu |
| 2017 | Stein Variational Policy Gradient. Yang Liu, Prajit Ramachandran, Qiang Liu, Jian Peng |
| 2017 | Stochastic Bandit Models for Delayed Conversions. Claire Vernade, Olivier Cappé, Vianney Perchet |
| 2017 | Stochastic L-BFGS Revisited: Improved Convergence Rates and Practical Acceleration Strategies. Renbo Zhao, William B. Haskell, Vincent Y. F. Tan |
| 2017 | Stochastic Segmentation Trees for Multiple Ground Truths. Jake Snell, Richard S. Zemel |
| 2017 | Structure Learning of Linear Gaussian Structural Equation Models with Weak Edges. Marco Eigenmann, Preetam Nandy, Marloes H. Maathuis |
| 2017 | Submodular Variational Inference for Network Reconstruction. Lin Chen, Forrest W. Crawford, Amin Karbasi |
| 2017 | Supervised Restricted Boltzmann Machines. Tu Dinh Nguyen, Dinh Q. Phung, Viet Huynh, Trung Le |
| 2017 | Synthesis of Strategies in Influence Diagrams. Manuel Luque, Manuel Arias, Francisco Javier Díez |
| 2017 | The Binomial Block Bootstrap Estimator for Evaluating Loss on Dependent Clusters. Matt Barnes, Artur Dubrawski |
| 2017 | The Total Belief Theorem. Chunlai Zhou, Fabio Cuzzolin |
| 2017 | Towards Conditional Independence Test for Relational Data. Sanghack Lee, Vasant G. Honavar |
| 2017 | Triply Stochastic Gradients on Multiple Kernel Learning. Xiang Li, Bin Gu, Shuang Ao, Huaimin Wang, Charles X. Ling |
| 2017 | Two current analysis challenges: Single Cell Omics and Nanopore Long-read Sequence Data. Terry Speed |
| 2017 | Value Directed Exploration in Multi-Armed Bandits with Structured Priors. Bence Cserna, Marek Petrik, Reazul Hasan Russel, Wheeler Ruml |
| 2017 | Weighted Model Counting With Function Symbols. Vaishak Belle |
| 2017 | Why Rules are Complex: Real-Valued Probabilistic Logic Programs are not Fully Expressive. David Buchman, David Poole |