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The 35th Uncertainty in Artificial Intelligence Conference: Preface
; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:1-17
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Personalized Peer Truth Serum for Eliciting Multi-Attribute Personal Data
Naman Goel, Boi Faltings; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:18-27
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Conditional Expectation Propagation
Zheng Wang, Shandian Zhe; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:28-37
A Sparse Representation-Based Approach to Linear Regression with Partially Shuffled Labels
Martin Slawski, Mostafa Rahmani, Ping Li; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:38-48
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On Fast Convergence of Proximal Algorithms for SQRT-Lasso Optimization: Don’t Worry About its Nonsmooth Loss Function
Xinguo Li, Haoming Jiang, Jarvis Haupt, Raman Arora, Han Liu, Mingyi Hong, Tuo Zhao; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:49-59
Correlated Learning for Aggregation Systems
Tanvi Verma, Pradeep Varakantham; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:60-70
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Causal Calculus in the Presence of Cycles, Latent Confounders and Selection Bias
Patrick Forré, Joris M. Mooij; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:71-80
Variational Regret Bounds for Reinforcement Learning
Ronald Ortner, Pratik Gajane, Peter Auer; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:81-90
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Recommendation from Raw Data with Adaptive Compound Poisson Factorization
Olivier Gouvert, Thomas Oberlin, Cédric Févotte; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:91-101
One-Shot Marginal MAP Inference in Markov Random Fields
Hao Xiong, Yuanzhen Guo, Yibo Yang, Nicholas Ruozzi; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:102-112
Truly Proximal Policy Optimization
Yuhui Wang, Hao He, Xiaoyang Tan; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:113-122
Learning Factored Markov Decision Processes with Unawareness
Craig Innes, Alex Lascarides; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:123-133
Expressive Priors in Bayesian Neural Networks: Kernel Combinations and Periodic Functions
Tim Pearce, Russell Tsuchida, Mohamed Zaki, Alexandra Brintrup, Andy Neely; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:134-144
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Countdown Regression: Sharp and Calibrated Survival Predictions
Anand Avati, Tony Duan, Sharon Zhou, Kenneth Jung, Nigam H. Shah, Andrew Y. Ng; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:145-155
Reducing Exploration of Dying Arms in Mortal Bandits
Stefano Tracà, Cynthia Rudin, Weiyu Yan; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:156-163
Comparing EM with GD in Mixture Models of Two Components
Guojun Zhang, Pascal Poupart, George Trimponias; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:164-174
Efficient Search-Based Weighted Model Integration
Zhe Zeng, Guy Van den Broeck; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:175-185
Causal Discovery with General Non-Linear Relationships using Non-Linear ICA
Ricardo Pio Monti, Kun Zhang, Aapo Hyvärinen; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:186-195
BubbleRank: Safe Online Learning to Re-Rank via Implicit Click Feedback
Chang Li, Branislav Kveton, Tor Lattimore, Ilya Markov, Maarten de Rijke, Csaba Szepesvári, Masrour Zoghi; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:196-206
Coordinating Users of Shared Facilities via Data-driven Predictive Assistants and Game Theory
Philipp Geiger, Michel Besserve, Justus Winkelmann, Claudius Proissl, Bernhard Schölkopf; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:207-216
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The Incomplete Rosetta Stone problem: Identifiability results for Multi-view Nonlinear ICA
Luigi Gresele, Paul K. Rubenstein, Arash Mehrjou, Francesco Locatello, Bernhard Schölkopf; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:217-227
Random Clique Covers for Graphs with Local Density and Global Sparsity
Sinead A. Williamson, Mauricio Tec; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:228-238
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Randomized Iterative Algorithms for Fisher Discriminant Analysis
Agniva Chowdhury, Jiasen Yang, Petros Drineas; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:239-249
Dynamic Trip-Vehicle Dispatch with Scheduled and On-Demand Requests
Taoan Huang, Bohui Fang, Xiaohui Bei, Fei Fang; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:250-260
Fall of Empires: Breaking Byzantine-tolerant SGD by Inner Product Manipulation
Cong Xie, Oluwasanmi Koyejo, Indranil Gupta; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:261-270
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Adaptive Hashing for Model Counting
Jonathan Kuck, Tri Dao, Shengjia Zhao, Burak Bartan, Ashish Sabharwal, Stefano Ermon; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:271-280
Towards a Better Understanding and Regularization of GAN Training Dynamics
Weili Nie, Ankit B. Patel; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:281-291
Domain Generalization via Multidomain Discriminant Analysis
Shoubo Hu, Kun Zhang, Zhitang Chen, Laiwan Chan; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:292-302
Efficient Planning Under Uncertainty with Incremental Refinement
Juan Carlos Saborío, Joachim Hertzberg; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:303-312
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Cubic Regularization with Momentum for Nonconvex Optimization
Zhe Wang, Yi Zhou, Yingbin Liang, Guanghui Lan; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:313-322
Stability of Linear Structural Equation Models of Causal Inference
Karthik Abhinav Sankararaman, Anand Louis, Navin Goyal; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:323-333
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Random Sum-Product Networks: A Simple and Effective Approach to Probabilistic Deep Learning
Robert Peharz, Antonio Vergari, Karl Stelzner, Alejandro Molina, Xiaoting Shao, Martin Trapp, Kristian Kersting, Zoubin Ghahramani; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:334-344
Towards Robust Relational Causal Discovery
Sanghack Lee, Vasant Honavar; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:345-355
The Role of Memory in Stochastic Optimization
Antonio Orvieto, Jonas Kohler, Aurelien Lucchi; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:356-366
Random Search and Reproducibility for Neural Architecture Search
Liam Li, Ameet Talwalkar; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:367-377
Joint Nonparametric Precision Matrix Estimation with Confounding
Sinong Geng, Mladen Kolar, Oluwasanmi Koyejo; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:378-388
General Identifiability with Arbitrary Surrogate Experiments
Sanghack Lee, Juan D. Correa, Elias Bareinboim; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:389-398
Differentiable Probabilistic Models of Scientific Imaging with the Fourier Slice Theorem
Karen Ullrich, Rianne van den Berg, Marcus Brubaker, David Fleet, Max Welling; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:399-411
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Approximate Inference in Structured Instances with Noisy Categorical Observations
Alireza Heidari, Ihab F. Ilyas, Theodoros Rekatsinas; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:412-421
Randomized Value Functions via Multiplicative Normalizing Flows
Ahmed Touati, Harsh Satija, Joshua Romoff, Joelle Pineau, Pascal Vincent; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:422-432
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A Fast Proximal Point Method for Computing Exact Wasserstein Distance
Yujia Xie, Xiangfeng Wang, Ruijia Wang, Hongyuan Zha; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:433-453
Neural Dynamics Discovery via Gaussian Process Recurrent Neural Networks
Qi She, Anqi Wu; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:454-464
Fisher-Bures Adversary Graph Convolutional Networks
Ke Sun, Piotr Koniusz, Zhen Wang; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:465-475
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Epsilon-BMC: A Bayesian Ensemble Approach to Epsilon-Greedy Exploration in Model-Free Reinforcement Learning
Michael Gimelfarb, Scott Sanner, Chi-Guhn Lee; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:476-485
Periodic Kernel Approximation by Index Set Fourier Series Features
Anthony Tompkins, Fabio Ramos; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:486-496
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Efficient Neural Network Verification with Exactness Characterization
Krishnamurthy (Dj) Dvijotham, Robert Stanforth, Sven Gowal, Chongli Qin, Soham De, Pushmeet Kohli; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:497-507
Augmenting and Tuning Knowledge Graph Embeddings
Robert Bamler, Farnood Salehi, Stephan Mandt; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:508-518
A Tighter Analysis of Randomised Policy Iteration
Meet Taraviya, Shivaram Kalyanakrishnan; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:519-529
Perturbed-History Exploration in Stochastic Linear Bandits
Branislav Kveton, Csaba Szepesvári, Mohammad Ghavamzadeh, Craig Boutilier; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:530-540
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An Improved Convergence Analysis of Stochastic Variance-Reduced Policy Gradient
Pan Xu, Felicia Gao, Quanquan Gu; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:541-551
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Deep Mixture of Experts via Shallow Embedding
Xin Wang, Fisher Yu, Lisa Dunlap, Yi-An Ma, Ruth Wang, Azalia Mirhoseini, Trevor Darrell, Joseph E. Gonzalez; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:552-562
Sampling-Free Variational Inference of Bayesian Neural Networks by Variance Backpropagation
Manuel Haußmann, Fred A. Hamprecht, Melih Kandemir; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:563-573
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Sliced Score Matching: A Scalable Approach to Density and Score Estimation
Yang Song, Sahaj Garg, Jiaxin Shi, Stefano Ermon; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:574-584
Beyond Structural Causal Models: Causal Constraints Models
Tineke Blom, Stephan Bongers, Joris M. Mooij; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:585-594
Be Greedy: How Chromatic Number meets Regret Minimization in Graph Bandits
Shreyas S, Aadirupa Saha, Chiranjib Bhattacharyya; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:595-605
Approximate Causal Abstractions
Sander Beckers, Frederick Eberhardt, Joseph Y. Halpern; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:606-615
The Sensitivity of Counterfactual Fairness to Unmeasured Confounding
Niki Kilbertus, Philip J. Ball, Matt J. Kusner, Adrian Weller, Ricardo Silva; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:616-626
Belief Propagation: Accurate Marginals or Accurate Partition Function – Where is the Difference?
Christian Knoll, Franz Pernkopf; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:627-636
Finding Minimal d-separators in Linear Time and Applications
Benito van der Zander, Maciej Liśkiewicz; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:637-647
A Bayesian Approach to Robust Reinforcement Learning
Esther Derman, Daniel Mankowitz, Timothy Mann, Shie Mannor; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:648-658
Adaptivity and Optimality: A Universal Algorithm for Online Convex Optimization
Guanghui Wang, Shiyin Lu, Lijun Zhang; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:659-668
Evacuate or Not? A POMDP Model of the Decision Making of Individuals in Hurricane Evacuation Zones
Adithya Raam Sankar, Prashant Doshi, Adam Goodie; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:669-678
Probabilistic Programming for Birth-Death Models of Evolution Using an Alive Particle Filter with Delayed Sampling
Jan Kudlicka, Lawrence M. Murray, Fredrik Ronquist, Thomas B. Schön; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:679-689
Variational Sparse Coding
Francesco Tonolini, Bjørn Sand Jensen, Roderick Murray-Smith; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:690-700
Learning with Non-Convex Truncated Losses by SGD
Yi Xu, Shenghuo Zhu, Sen Yang, Chi Zhang, Rong Jin, Tianbao Yang; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:701-711
Active Multi-Information Source Bayesian Quadrature
Alexandra Gessner, Javier Gonzalez, Maren Mahsereci; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:712-721
Cascading Linear Submodular Bandits: Accounting for Position Bias and Diversity in Online Learning to Rank
Gaurush Hiranandani, Harvineet Singh, Prakhar Gupta, Iftikhar Ahamath Burhanuddin, Zheng Wen, Branislav Kveton; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:722-732
Sinkhorn AutoEncoders
Giorgio Patrini, Rianne van den Berg, Patrick Forré, Marcello Carioni, Samarth Bhargav, Max Welling, Tim Genewein, Frank Nielsen; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:733-743
How to Exploit Structure while Solving Weighted Model Integration Problems
Samuel Kolb, Pedro Zuidberg Dos Martires, Luc De Raedt; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:744-754
Multi-Class Gaussian Process Classification Made Conjugate: Efficient Inference via Data Augmentation
Théo Galy-Fajou, Florian Wenzel, Christian Donner, Manfred Opper; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:755-765
A Flexible Framework for Multi-Objective Bayesian Optimization using Random Scalarizations
Biswajit Paria, Kirthevasan Kandasamy, Barnabás Póczos; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:766-776
Efficient Multitask Feature and Relationship Learning
Han Zhao, Otilia Stretcu, Alexander J. Smola, Geoffrey J. Gordon; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:777-787
Practical Multi-fidelity Bayesian Optimization for Hyperparameter Tuning
Jian Wu, Saul Toscano-Palmerin, Peter I. Frazier, Andrew Gordon Wilson; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:788-798
Adaptively Truncating Backpropagation Through Time to Control Gradient Bias
Christopher Aicher, Nicholas J. Foti, Emily B. Fox; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:799-808
Sampling-free Uncertainty Estimation in Gated Recurrent Units with Applications to Normative Modeling in Neuroimaging
Seong Jae Hwang, Ronak R. Mehta, Hyunwoo J. Kim, Sterling C. Johnson, Vikas Singh; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:809-819
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Online Factorization and Partition of Complex Networks by Random Walk
Lin Yang, Zheng Yu, Vladimir Braverman, Tuo Zhao, Mengdi Wang; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:820-830
On Densification for Minwise Hashing
Tung Mai, Anup Rao, Matt Kapilevich, Ryan Rossi, Yasin Abbasi-Yadkori, Ritwik Sinha; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:831-840
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N-GCN: Multi-scale Graph Convolution for Semi-supervised Node Classification
Sami Abu-El-Haija, Amol Kapoor, Bryan Perozzi, Joonseok Lee; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:841-851
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Problem-dependent Regret Bounds for Online Learning with Feedback Graphs
Bingshan Hu, Nishant A. Mehta, Jianping Pan; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:852-861
Wasserstein Fair Classification
Ray Jiang, Aldo Pacchiano, Tom Stepleton, Heinrich Jiang, Silvia Chiappa; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:862-872
Variational Training for Large-Scale Noisy-OR Bayesian Networks
Geng Ji, Dehua Cheng, Huazhong Ning, Changhe Yuan, Hanning Zhou, Liang Xiong, Erik B. Sudderth; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:873-882
Guaranteed Scalable Learning of Latent Tree Models
Furong Huang, Niranjan Uma Naresh, Ioakeim Perros, Robert Chen, Jimeng Sun, Anima Anandkumar; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:883-893
On First-Order Bounds, Variance and Gap-Dependent Bounds for Adversarial Bandits
Roman Pogodin, Tor Lattimore; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:894-904
Noise Contrastive Priors for Functional Uncertainty
Danijar Hafner, Dustin Tran, Timothy Lillicrap, Alex Irpan, James Davidson; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:905-914
Fake It Till You Make It: Learning-Compatible Performance Support
Jonathan Bragg, Emma Brunskill; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:915-924
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Literal or Pedagogic Human? Analyzing Human Model Misspecification in Objective Learning
Smitha Milli, Anca D. Dragan; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:925-934
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Convergence Analysis of Gradient-Based Learning in Continuous Games
Benjamin Chasnov, Lillian Ratliff, Eric Mazumdar, Samuel Burden; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:935-944
End-to-end Training of Deep Probabilistic CCA on Paired Biomedical Observations
Gregory Gundersen, Bianca Dumitrascu, Jordan T. Ash, Barbara E. Engelhardt; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:945-955
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Approximate Relative Value Learning for Average-reward Continuous State MDPs
Hiteshi Sharma, Mehdi Jafarnia-Jahromi, Rahul Jain; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:956-964
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Exact Sampling of Directed Acyclic Graphs from Modular Distributions
Topi Talvitie, Aleksis Vuoksenmaa, Mikko Koivisto; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:965-974
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Intervening on Network Ties
Eli Sherman, Ilya Shpitser; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:975-984
Generating and Sampling Orbits for Lifted Probabilistic Inference
Steven Holtzen, Todd Millstein, Guy Van den Broeck; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:985-994
Real-Time Robotic Search using Structural Spatial Point Processes
Olov Andersson, Per Sidén, Johan Dahlin, Patrick Doherty, Mattias Villani; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:995-1005
Social Reinforcement Learning to Combat Fake News Spread
Mahak Goindani, Jennifer Neville; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:1006-1016
P3O: Policy-on Policy-off Policy Optimization
Rasool Fakoor, Pratik Chaudhari, Alexander J. Smola; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:1017-1027
Causal Inference Under Interference And Network Uncertainty
Rohit Bhattacharya, Daniel Malinsky, Ilya Shpitser; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:1028-1038
Revisiting Reweighted Wake-Sleep for Models with Stochastic Control Flow
Tuan Anh Le, Adam R. Kosiorek, N. Siddharth, Yee Whye Teh, Frank Wood; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:1039-1049
Learnability for the Information Bottleneck
Tailin Wu, Ian Fischer, Isaac L. Chuang, Max Tegmark; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:1050-1060
Learning Belief Representations for Imitation Learning in POMDPs
Tanmay Gangwani, Joel Lehman, Qiang Liu, Jian Peng; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:1061-1071
Object Conditioning for Causal Inference
David Jensen, Javier Burroni, Matthew Rattigan; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:1072-1082
CCMI : Classifier based Conditional Mutual Information Estimation
Sudipto Mukherjee, Himanshu Asnani, Sreeram Kannan; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:1083-1093
Empirical Mechanism Design: Designing Mechanisms from Data
Enrique Areyan Viqueira, Cyrus Cousins, Yasser Mohammad, Amy Greenwald; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:1094-1104
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On the Relationship Between Satisfiability and Markov Decision Processes
Ricardo Salmon, Pascal Poupart; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:1105-1115
Interpretable Almost Matching Exactly With Instrumental Variables
M. Usaid Awan, Yameng Liu, Marco Morucci, Sudeepa Roy, Cynthia Rudin, Alexander Volfovsky; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:1116-1126
Low Frequency Adversarial Perturbation
Chuan Guo, Jared S. Frank, Kilian Q. Weinberger; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:1127-1137
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Markov Logic Networks for Knowledge Base Completion: A Theoretical Analysis Under the MCAR Assumption
Ondřej Kuželka, Jesse Davis; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:1138-1148
Identification In Missing Data Models Represented By Directed Acyclic Graphs
Rohit Bhattacharya, Razieh Nabi, Ilya Shpitser, James M. Robins; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:1149-1158
A Weighted Mini-Bucket Bound for Solving Influence Diagram
Junkyu Lee, Radu Marinescu, Alexander Ihler, Rina Dechter; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:1159-1168
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Subspace Inference for Bayesian Deep Learning
Pavel Izmailov, Wesley J. Maddox, Polina Kirichenko, Timur Garipov, Dmitry Vetrov, Andrew Gordon Wilson; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:1169-1179
Off-Policy Policy Gradient with Stationary Distribution Correction
Yao Liu, Adith Swaminathan, Alekh Agarwal, Emma Brunskill; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:1180-1190
Co-training for Policy Learning
Jialin Song, Ravi Lanka, Yisong Yue, Masahiro Ono; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:1191-1201
Variational Inference of Penalized Regression with Submodular Functions
Koh Takeuchi, Yuichi Yoshida, Yoshinobu Kawahara; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:1202-1211
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Probability Distillation: A Caveat and Alternatives
Chin-Wei Huang, Faruk Ahmed, Kundan Kumar, Alexandre Lacoste, Aaron Courville; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:1212-1221
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Bayesian Optimization with Binary Auxiliary Information
Yehong Zhang, Zhongxiang Dai, Bryan Kian Hsiang Low; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:1222-1232
On Open-Universe Causal Reasoning
Duligur Ibeling, Thomas Icard; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:1233-1243
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Embarrassingly Parallel MCMC using Deep Invertible Transformations
Diego Mesquita, Paul Blomstedt, Samuel Kaski; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:1244-1252
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Fast Proximal Gradient Descent for A Class of Non-convex and Non-smooth Sparse Learning Problems
Yingzhen Yang, Jiahui Yu; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:1253-1262
Block Neural Autoregressive Flow
Nicola De Cao, Wilker Aziz, Ivan Titov; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:1263-1273
Exclusivity Graph Approach to Instrumental Inequalities
Davide Poderini, Rafael Chaves, Iris Agresti, Gonzalo Carvacho, Fabio Sciarrino; Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, PMLR 115:1274-1283
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