| 2016 | A Characterization of Markov Equivalence Classes of Relational Causal Models under Path Semantics. Sanghack Lee, Vasant G. Honavar |
| 2016 | A Correlated Worker Model for Grouped, Imbalanced and Multitask Data. An T. Nguyen, Byron C. Wallace, Matthew Lease |
| 2016 | A Formal Solution to the Grain of Truth Problem. Jan Leike, Jessica Taylor, Benya Fallenstein |
| 2016 | A General Statistical Framework for Designing Strategy-proof Assignment Mechanisms. Harikrishna Narasimhan, David C. Parkes |
| 2016 | A Generative Block-Diagonal Model for Clustering. Junxiang Chen, Jennifer G. Dy |
| 2016 | A Kernel Test for Three-Variable Interactions with Random Processes. Paul K. Rubenstein, Kacper Chwialkowski, Arthur Gretton |
| 2016 | Accelerated Stochastic Block Coordinate Gradient Descent for Sparsity Constrained Nonconvex Optimization. Jinghui Chen, Quanquan Gu |
| 2016 | Active Uncertainty Calibration in Bayesian ODE Solvers. Hans Kersting, Philipp Hennig |
| 2016 | Adaptive Algorithms and Data-Dependent Guarantees for Bandit Convex Optimization. Scott Yang, Mehryar Mohri |
| 2016 | Adversarial Inverse Optimal Control for General Imitation Learning Losses and Embodiment Transfer. Xiangli Chen, Mathew Monfort, Brian D. Ziebart, Peter Carr |
| 2016 | Alternative Markov and Causal Properties for Acyclic Directed Mixed Graphs. José M. Peña |
| 2016 | Analysis of Nyström method with sequential ridge leverage scores. Daniele Calandriello, Alessandro Lazaric, Michal Valko |
| 2016 | Bayesian Estimators As Voting Rules. Lirong Xia |
| 2016 | Bayesian Hyperparameter Optimization for Ensemble Learning. Julien-Charles Levesque, Christian Gagné, Robert Sabourin |
| 2016 | Bayesian Learning of Kernel Embeddings. Seth R. Flaxman, Dino Sejdinovic, John P. Cunningham, Sarah Filippi |
| 2016 | Bounded Rational Decision-Making in Feedforward Neural Networks. Felix Leibfried, Daniel A. Braun |
| 2016 | Bounded Rationality in Wagering Mechanisms. David M. Pennock, Vasilis Syrgkanis, Jennifer Wortman Vaughan |
| 2016 | Bridging Heterogeneous Domains With Parallel Transport For Vision and Multimedia Applications. Raghuraman Gopalan |
| 2016 | Budget Allocation using Weakly Coupled, Constrained Markov Decision Processes. Craig Boutilier, Tyler Lu |
| 2016 | Budgeted Semi-supervised Support Vector Machine . Trung Le, Phuong Duong, Mi Dinh, Tu Dinh Nguyen, Vu Nguyen, Dinh Q. Phung |
| 2016 | Cascading Bandits for Large-Scale Recommendation Problems. Shi Zong, Hao Ni, Kenny Sung, Nan Rosemary Ke, Zheng Wen, Branislav Kveton |
| 2016 | Characterizing Tightness of LP Relaxations by Forbidding Signed Minors. Adrian Weller |
| 2016 | Conjugate Conformal Prediction for Online Binary Classification. Mustafa Anil Koçak, Dennis E. Shasha, Elza Erkip |
| 2016 | Content-based Modeling of Reciprocal Relationships using Hawkes and Gaussian Processes. Xi Tan, Syed A. Z. Naqvi, Yuan (Alan) Qi, Katherine A. Heller, Vinayak A. Rao |
| 2016 | Context-dependent feature analysis with random forests. Antonio Sutera, Gilles Louppe, Vân Anh Huynh-Thu, Louis Wehenkel, Pierre Geurts |
| 2016 | Convergence Rates for Greedy Kaczmarz Algorithms, and Randomized Kaczmarz Rules Using the Orthogonality Graph. Julie Nutini, Behrooz Sepehry, Issam H. Laradji, Mark Schmidt, Hoyt A. Koepke, Alim Virani |
| 2016 | Convex Relaxation Regression: Black-Box Optimization of Smooth Functions by Learning Their Convex Envelopes. Mohammad Gheshlaghi Azar, Eva L. Dyer, Konrad P. Körding |
| 2016 | Correlated Tag Learning in Topic Model. Shuangyin Li, Rong Pan, Yu Zhang, Qiang Yang |
| 2016 | Dantzig Selector with an Approximately Optimal Denoising Matrix and its Application in Sparse Reinforcement Learning. Bo Liu, Luwan Zhang, Ji Liu |
| 2016 | Degrees of Freedom in Deep Neural Networks. Tianxiang Gao, Vladimir Jojic |
| 2016 | Efficient Feature Group Sequencing for Anytime Linear Prediction. Hanzhang Hu, Alexander Grubb, J. Andrew Bagnell, Martial Hebert |
| 2016 | Efficient Multi-Class Selective Sampling on Graphs. Peng Yang, Peilin Zhao, Zhen Hai, Wei Liu, Steven C. H. Hoi, Xiaoli Li |
| 2016 | Efficient Observation Selection in Probabilistic Graphical Models Using Bayesian Lower Bounds. Dilin Wang, John W. Fisher III, Qiang Liu |
| 2016 | Elliptical Slice Sampling with Expectation Propagation. Francois Fagan, Jalaj Bhandari, John P. Cunningham |
| 2016 | Faster Stochastic Variational Inference using Proximal-Gradient Methods with General Divergence Functions. Mohammad Emtiyaz Khan, Reza Babanezhad, Wu Lin, Mark Schmidt, Masashi Sugiyama |
| 2016 | Finite Sample Complexity of Rare Pattern Anomaly Detection. Md Amran Siddiqui, Alan Fern, Thomas G. Dietterich, Shubhomoy Das |
| 2016 | Forward Backward Greedy Algorithms for Multi-Task Learning with Faster Rates. Lu Tian, Pan Xu, Quanquan Gu |
| 2016 | Gradient Methods for Stackelberg Games. Kareem Amin, Michael P. Wellman, Satinder Singh |
| 2016 | Hierarchical learning of grids of microtopics. Nebojsa Jojic, Alessandro Perina, Dongwoo Kim |
| 2016 | Importance Weighted Consensus Monte Carlo for Distributed Bayesian Inference. Qiang Liu |
| 2016 | Improving Imprecise Compressive Sensing Models. Dongeun Lee, Rafael Lima, Jaesik Choi |
| 2016 | Incremental Preference Elicitation for Decision Making Under Risk with the Rank-Dependent Utility Model. Patrice Perny, Paolo Viappiani, Abdellah Boukhatem |
| 2016 | Individual Planning in Open and Typed Agent Systems. Muthukumaran Chandrasekaran, Adam Eck, Prashant Doshi, Leenkiat Soh |
| 2016 | Inferring Causal Direction from Relational Data. David T. Arbour, Katerina Marazopoulou, David D. Jensen |
| 2016 | Interpretable Policies for Dynamic Product Recommendations. Marek Petrik, Ronny Luss |
| 2016 | Large-scale Submodular Greedy Exemplar Selection with Structured Similarity Matrices. Dmitry Malioutov, Abhishek Kumar, Ian En-Hsu Yen |
| 2016 | Learning Network of Multivariate Hawkes Processes: A Time Series Approach. Jalal Etesami, Negar Kiyavash, Kun Zhang, Kushagra Singhal |
| 2016 | Learning to Smooth with Bidirectional Predictive State Inference Machines. Wen Sun, Roberto Capobianco, Geoffrey J. Gordon, J. Andrew Bagnell, Byron Boots |
| 2016 | Lighter-Communication Distributed Machine Learning via Sufficient Factor Broadcasting. Pengtao Xie, Jin Kyu Kim, Yi Zhou, Qirong Ho, Abhimanu Kumar, Yaoliang Yu, Eric P. Xing |
| 2016 | MDPs with Unawareness in Robotics. Nan Rong, Joseph Y. Halpern, Ashutosh Saxena |
| 2016 | Markov Beta Processes for Time Evolving Dictionary Learning. Amar Shah, Zoubin Ghahramani |
| 2016 | Merging Strategies for Sum-Product Networks: From Trees to Graphs. Tahrima Rahman, Vibhav Gogate |
| 2016 | Model-Free Reinforcement Learning with Skew-Symmetric Bilinear Utilities. Hugo Gilbert, Bruno Zanuttini, Paul Weng, Paolo Viappiani, Esther Nicart |
| 2016 | Modeling Transitivity in Complex Networks. Morteza Haghir Chehreghani, Mostafa Haghir Chehreghani |
| 2016 | Non-parametric Domain Approximation for Scalable Gibbs Sampling in MLNs. Deepak Venugopal, Somdeb Sarkhel, Kyle Cherry |
| 2016 | On Hyper-Parameter Estimation In Empirical Bayes: A Revisit of The MacKay Algorithm. Chune Li, Yongyi Mao, Richong Zhang, Jinpeng Huai |
| 2016 | On the Identifiability and Estimation of Functional Causal Models in the Presence of Outcome-Dependent Selection. Kun Zhang, Jiji Zhang, Biwei Huang, Bernhard Schölkopf, Clark Glymour |
| 2016 | On the Theory and Practice of Privacy-Preserving Bayesian Data Analysis. James R. Foulds, Joseph Geumlek, Max Welling, Kamalika Chaudhuri |
| 2016 | Online Bayesian Multiple Kernel Bipartite Ranking. Changying Du, Changde Du, Guoping Long, Qing He, Yucheng Li |
| 2016 | Online Forest Density Estimation. Frédéric Koriche |
| 2016 | Online learning with Erdos-Renyi side-observation graphs. Tomás Kocák, Gergely Neu, Michal Valko |
| 2016 | Optimal Stochastic Strongly Convex Optimization with a Logarithmic Number of Projections. Jianhui Chen, Tianbao Yang, Qihang Lin, Lijun Zhang, Yi Chang |
| 2016 | Overdispersed Black-Box Variational Inference. Francisco J. R. Ruiz, Michalis K. Titsias, David M. Blei |
| 2016 | Political Dimensionality Estimation Using a Probabilistic Graphical Model. Yoad Lewenberg, Yoram Bachrach, Lucas Bordeaux, Pushmeet Kohli |
| 2016 | Probabilistic Size-constrained Microclustering. Arto Klami, Aditya Jitta |
| 2016 | Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, UAI 2016, June 25-29, 2016, New York City, NY, USA Alexander Ihler, Dominik Janzing |
| 2016 | Pruning Rules for Learning Parsimonious Context Trees. Ralf Eggeling, Mikko Koivisto |
| 2016 | Quasi-Newton Hamiltonian Monte Carlo. Tianfan Fu, Luo Luo, Zhihua Zhang |
| 2016 | Safely Interruptible Agents. Laurent Orseau, Stuart Armstrong |
| 2016 | Scalable Joint Modeling of Longitudinal and Point Process Data for Disease Trajectory Prediction and Improving Management of Chronic Kidney Disease. Joseph Futoma, Mark P. Sendak, Blake Cameron, Katherine A. Heller |
| 2016 | Scalable Nonparametric Bayesian Multilevel Clustering. Viet Huynh, Dinh Q. Phung, Svetha Venkatesh, XuanLong Nguyen, Matthew D. Hoffman, Hung Hai Bui |
| 2016 | Sequential Nonparametric Testing with the Law of the Iterated Logarithm. Akshay Balsubramani, Aaditya Ramdas |
| 2016 | Sparse Gaussian Processes for Bayesian Optimization. Mitchell McIntire, Daniel Ratner, Stefano Ermon |
| 2016 | Stability of Causal Inference. Leonard J. Schulman, Piyush Srivastava |
| 2016 | Stochastic Portfolio Theory: A Machine Learning Approach. Yves-Laurent Kom Samo, Alexander Vervuurt |
| 2016 | Structured Prediction: From Gaussian Perturbations to Linear-Time Principled Algorithms. Jean Honorio, Tommi S. Jaakkola |
| 2016 | Subspace Clustering with a Twist. David P. Wipf, Yue Dong, Bo Xin |
| 2016 | Super-Sampling with a Reservoir. Brooks Paige, Dino Sejdinovic, Frank D. Wood |
| 2016 | Taming the Noise in Reinforcement Learning via Soft Updates. Roy Fox, Ari Pakman, Naftali Tishby |
| 2016 | The Deterministic Information Bottleneck. DJ Strouse, David J. Schwab |
| 2016 | The Mondrian Kernel. Matej Balog, Balaji Lakshminarayanan, Zoubin Ghahramani, Daniel M. Roy, Yee Whye Teh |
| 2016 | Thompson Sampling is Asymptotically Optimal in General Environments. Jan Leike, Tor Lattimore, Laurent Orseau, Marcus Hutter |
| 2016 | Towards a Theoretical Understanding of Negative Transfer in Collective Matrix Factorization. Chao Lan, Jianxin Wang, Jun Huan |
| 2016 | Training Neural Nets to Aggregate Crowdsourced Responses. Alex Gaunt, Diana Borsa, Yoram Bachrach |
| 2016 | Unsupervised Discovery of El Nino Using Causal Feature Learning on Microlevel Climate Data. Krzysztof Chalupka, Tobias Bischoff, Frederick Eberhardt, Pietro Perona |
| 2016 | Utilize Old Coordinates: Faster Doubly Stochastic Gradients for Kernel Methods. Chun-Liang Li, Barnabás Póczos |