UAI 2022
230 papers
A Competitive Analysis of Online Failure-Aware Assignment
Mengjing Chen, Pingzhong Tang, Zihe Wang, Shenke Xiao, Xiwang Yang A Label Efficient Two-Sample Test
Weizhi Li, Gautam Dasarathy, Karthikeyan Natesan Ramamurthy, Visar Berisha Active Learning with Label Comparisons
Gal Yona, Shay Moran, Gal Elidan, Amir Globerson An Explore-Then-Commit Algorithm for Submodular Maximization Under Full-Bandit Feedback
Guanyu Nie, Mridul Agarwal, Abhishek Kumar Umrawal, Vaneet Aggarwal, Christopher John Quinn Attribution of Predictive Uncertainties in Classification Models
Iker Perez, Piotr Skalski, Alec Barns-Graham, Jason Wong, David Sutton Balancing Utility and Scalability in Metric Differential Privacy
Jacob Imola, Shiva Kasiviswanathan, Stephen White, Abhinav Aggarwal, Nathanael Teissier Bayesian Quantile and Expectile Optimisation
Victor Picheny, Henry Moss, Léonard Torossian, Nicolas Durrande Bayesian Structure Learning with Generative Flow Networks
Tristan Deleu, António Góis, Chris Emezue, Mansi Rankawat, Simon Lacoste-Julien, Stefan Bauer, Yoshua Bengio Bias Aware Probabilistic Boolean Matrix Factorization
Changlin Wan, Pengtao Dang, Tong Zhao, Yong Zang, Chi Zhang, Sha Cao Causal Forecasting: Generalization Bounds for Autoregressive Models
Leena Chennuru Vankadara, Philipp Michael Faller, Michaela Hardt, Lenon Minorics, Debarghya Ghoshdastidar, Dominik Janzing Conditional Simulation Using Diffusion Schrödinger Bridges
Yuyang Shi, Valentin De Bortoli, George Deligiannidis, Arnaud Doucet Counterfactual Inference of Second Opinions
Nina L. Corvelo Benz, Manuel Gomez Rodriguez Data Augmentation in Bayesian Neural Networks and the Cold Posterior Effect
Seth Nabarro, Stoil Ganev, Adrià Garriga-Alonso, Vincent Fortuin, Mark Wilk, Laurence Aitchison Data Dependent Randomized Smoothing
Motasem Alfarra, Adel Bibi, Philip H. S. Torr, Bernard Ghanem Data Poisoning Attacks on Off-Policy Policy Evaluation Methods
Elita Lobo, Harvineet Singh, Marek Petrik, Cynthia Rudin, Himabindu Lakkaraju Decision-Theoretic Planning with Communication in Open Multiagent Systems
Anirudh Kakarlapudi, Gayathri Anil, Adam Eck, Prashant Doshi, Leen-Kiat Soh Deep Dirichlet Process Mixture Models
Naiqi Li, Wenjie Li, Yong Jiang, Shu-Tao Xia Deterministic Policy Gradient: Convergence Analysis
Huaqing. Xiong, Tengyu Xu, Lin Zhao, Yingbin Liang, Wei Zhang Differentially Private Multi-Party Data Release for Linear Regression
Ruihan Wu, Xin Yang, Yuanshun Yao, Jiankai Sun, Tianyi Liu, Q. Kilian Weinberger, Chong Wang Differentially Private SGDA for Minimax Problems
Zhenhuan Yang, Shu Hu, Yunwen Lei, Kush R Vashney, Siwei Lyu, Yiming Ying Distributed Adversarial Training to Robustify Deep Neural Networks at Scale
Gaoyuan Zhang, Songtao Lu, Yihua Zhang, Xiangyi Chen, Pin-Yu Chen, Quanfu Fan, Lee Martie, Lior Horesh, Mingyi Hong, Sijia Liu Enhanced Adaptive Optics Control with Image to Image Translation
Jeffrey Smith, Jesse Cranney, Charles Gretton, Damien Gratadour Equilibrium Aggregation: Encoding Sets via Optimization
Sergey Bartunov, Fabian B. Fuchs, Timothy P. Lillicrap Estimating Transfer Entropy Under Long Ranged Dependencies
Sahil Garg, Umang Gupta, Yu Chen, Syamantak Datta Gupta, Yeshaya Adler, Anderson Schneider, Yuriy Nevmyvaka Evaluating High-Order Predictive Distributions in Deep Learning
Ian Osband, Zheng Wen, Seyed Mohammad Asghari, Vikranth Dwaracherla, Xiuyuan Lu, Benjamin Van Roy Fast Inference and Transfer of Compositional Task Structures for Few-Shot Task Generalization
Sungryull Sohn, Hyunjae Woo, Jongwook Choi, Lyubing Qiang, Izzeddin Gur, Aleksandra Faust, Honglak Lee Faster Non-Convex Federated Learning via Global and Local Momentum
Rudrajit Das, Anish Acharya, Abolfazl Hashemi, Sujay Sanghavi, Inderjit S. Dhillon, Ufuk Topcu Federated Online Clustering of Bandits
Xutong Liu, Haoru Zhao, Tong Yu, Shuai Li, John C.S. Lui Finite-Horizon Equilibria for Neuro-Symbolic Concurrent Stochastic Games
Rui Yan, Gabriel Santos, Xiaoming Duan, David Parker, Marta Kwiatkowska Future Gradient Descent for Adapting the Temporal Shifting Data Distribution in Online Recommendation Systems
Mao Ye, Ruichen Jiang, Haoxiang Wang, Dhruv Choudhary, Xiaocong Du, Bhargav Bhushanam, Aryan Mokhtari, Arun Kejariwal, Qiang Liu Greedy Modality Selection via Approximate Submodular Maximization
Runxiang Cheng, Gargi Balasubramaniam, Yifei He, Yao-Hung Hubert Tsai, Han Zhao How Unfair Is Private Learning?
Amartya Sanyal, Yaxi Hu, Fanny Yang Implicit Kernel Meta-Learning Using Kernel Integral Forms
John Isak Texas Falk, Carlo Cilibert, Massimiliano Pontil Improving Sign-Random-Projection via Count Sketch
Punit Pankaj Dubey, Bhisham Dev Verma, Rameshwar Pratap, Keegan Kang Individual Fairness in Feature-Based Pricing for Monopoly Markets
Shantanu Das, Swapnil Dhamal, Ganesh Ghalme, Shweta Jain, Sujit Gujar Inductive Synthesis of Finite-State Controllers for POMDPs
Roman Andriushchenko, Milan Češka, Sebastian Junges, Joost-Pieter Katoen Intervention Target Estimation in the Presence of Latent Variables
Burak Varici, Karthikeyan Shanmugam, Prasanna Sattigeri, Ali Tajer Learning a Neural Pareto Manifold Extractor with Constraints
Soumyajit Gupta, Gurpreet Singh, Raghu Bollapragada, \Matthew Lease Learning Binary Multi-Scale Games on Networks
Sixie Yu, P. Jeffrey Brantingham, Matthew Valasik, Yevgeniy Vorobeychik Learning Functions on Multiple Sets Using Multi-Set Transformers
Kira A. Selby, Ahmad Rashid, Ivan Kobyzev, Mehdi Rezagholizadeh, Pascal Poupart Learning Linear Non-Gaussian Polytree Models
Daniele Tramontano, Anthea Monod, Mathias Drton Lifting in Multi-Agent Systems Under Uncertainty
Tanya Braun, Marcel Gehrke, Florian Lau, Ralf Möller Linearizing Contextual Bandits with Latent State Dynamics
Elliot Nelson, Debarun Bhattacharjya, Tian Gao, Miao Liu, Djallel Bouneffouf, Pascal Poupart Local Calibration: Metrics and Recalibration
Rachel Luo, Aadyot Bhatnagar, Yu Bai, Shengjia Zhao, Huan Wang, Caiming Xiong, Silvio Savarese, Stefano Ermon, Edward Schmerling, Marco Pavone Low-Precision Arithmetic for Fast Gaussian Processes
Wesley J. Maddox, Andres Potapcynski, Andrew Gordon Wilson Meta-Learning Without Data via Wasserstein Distributionally-Robust Model Fusion
Zhenyi Wang, Xiaoyang Wang, Li Shen, Qiuling Suo, Kaiqiang Song, Dong Yu, Yan Shen, Mingchen Gao Mitigating Statistical Bias Within Differentially Private Synthetic Data
Sahra Ghalebikesabi, Harry Wilde, Jack Jewson, Arnaud Doucet, Sebastian Vollmer, Chris Holmes Modeling Extremes with $d$-Max-Decreasing Neural Networks
Ali Hasan, Khalil Elkhalil, Yuting Ng, João M. Pereira, Sina Farsiu, Jose Blanchet, Vahid Tarokh Multiclass Classification for Hawkes Processes
Christophe Denis, Charlotte Dion-Blanc, Laure Sansonnet Multistate Analysis with Infinite Mixtures of Markov Chains
Lucas Maystre, Tiffany Wu, Roberto Sanchis-Ojeda, Tony Jebara Neural Ensemble Search via Bayesian Sampling
Yao Shu, Yizhou Chen, Zhongxiang Dai, Bryan Kian Hsiang Low Neuro-Symbolic Entropy Regularization
Kareem Ahmed, Eric Wang, Kai-Wei Chang, Guy Broeck Non-Parametric Inference of Relational Dependence
Ragib Ahsan, Zahra Fatemi, David Arbour, Elena Zheleva On Early Extinction and the Effect of Travelling in the SIR Model
Petra Berenbrink, Colin Cooper, Cristina Gava, David Kohan Marzagão, Frederik Mallmann-Trenn, Tomasz Radzik On Provably Robust Meta-Bayesian Optimization
Zhongxiang Dai, Yizhou Chen, Haibin Yu, Bryan Kian Hsiang Low, Patrick Jaillet On-the-Fly Adaptation of Patrolling Strategies in Changing Environments
Tomáš Brázdil, David Klaška, Antonı́n Kučera, Vı́t Musil, Petr Novotný, Vojtěch Řehák PAC-Bayesian Domain Adaptation Bounds for Multiclass Learners
Anthony Sicilia, Katherine Atwell, Malihe Alikhani, Seong Jae Hwang Physics Guided Neural Networks for Spatio-Temporal Super-Resolution of Turbulent Flows
Tianshu Bao, Shengyu Chen, Taylor T Johnson, Peyman Givi, Shervin Sammak, Xiaowei Jia Predictive Whittle Networks for Time Series
Zhongjie Yu, Fabrizio Ventola, Nils Thoma, Devendra Singh Dhami, Martin Mundt, Kristian Kersting Principle of Relevant Information for Graph Sparsification
Shujian Yu, Francesco Alesiani, Wenzhe Yin, Robert Jenssen, Jose C. Principe Probabilistic Spatial Transformer Networks
Pola Schwöbel, Frederik Rahbæk Warburg, Martin Jørgensen, Kristoffer Hougaard Madsen, Søren Hauberg Probabilistic Surrogate Networks for Simulators with Unbounded Randomness
Andreas Munk, Berend Zwartsenberg, Adam Ścibior, Atılım Güneş G. Baydin, Andrew Stewart, Goran Fernlund, Anoush Poursartip, Frank Wood Quadratic Metric Elicitation for Fairness and Beyond
Gaurush Hiranandani, Jatin Mathur, Harikrishna Narasimhan, Oluwasanmi Koyejo Reframed GES with a Neural Conditional Dependence Measure
Xinwei Shen, Shengyu Zhu, Jiji Zhang, Shoubo Hu, Zhitang Chen ResIST: Layer-Wise Decomposition of ResNets for Distributed Training
Chen Dun, Cameron R. Wolfe, Christopher M. Jermaine, Anastasios Kyrillidis Resolving Label Uncertainty with Implicit Posterior Models
Esther Rolf, Nikolay Malkin, Alexandros Graikos, Ana Jojic, Caleb Robinson, Nebojsa Jojic Revisiting the General Identifiability Problem
Yaroslav Kivva, Ehsan Mokhtarian, Jalal Etesami, Negar Kiyavash Robust Bayesian Recourse
Tuan-Duy H. Nguyen, Ngoc Bui, Duy Nguyen, Man-Chung Yue, Viet Anh Nguyen Self-Supervised Representations for Multi-View Reinforcement Learning
Huanhuan Yang, Dianxi Shi, Guojun Xie, Yingxuan Peng, Yi Zhang, Yantai Yang, Shaowu Yang Sequential Algorithmic Modification with Test Data Reuse
Jean Feng, Gene Pennllo, Nicholas Petrick, Berkman Sahiner, Romain Pirracchio, Alexej Gossmann Shoring up the Foundations: Fusing Model Embeddings and Weak Supervision
Mayee F. Chen, Daniel Y. Fu, Dyah Adila, Michael Zhang, Frederic Sala, Kayvon Fatahalian, Christopher Ré SMT-Based Weighted Model Integration with Structure Awareness
Giuseppe Spallitta, Gabriele Masina, Paolo Morettin, Andrea Passerini, Roberto Sebastiani Solving Structured Hierarchical Games Using Differential Backward Induction
Zun Li, Feiran Jia, Aditya Mate, Shahin Jabbari, Mithun Chakraborty, Milind Tambe, Yevgeniy Vorobeychik Stability of SGD: Tightness Analysis and Improved Bounds
Yikai Zhang, Wenjia Zhang, Sammy Bald, Vamsi Pingali, Chao Chen, Mayank Goswami Stackmix: A Complementary Mix Algorithm
John Chen, Samarth Sinha, Anastasios Kyrillidis Temporal Abstractions-Augmented Temporally Contrastive Learning: An Alternative to the Laplacian in RL
Akram Erraqabi, Marlos C. Machado, Mingde Zhao, Sainbayar Sukhbaatar, Alessandro Lazaric, Denoyer Ludovic, Yoshua Bengio Towards Painless Policy Optimization for Constrained MDPs
Arushi Jain, Sharan Vaswani, Reza Babanezhad, Csaba Szepesvári, Doina Precup Towards Unsupervised Open World Semantic Segmentation
Svenja Uhlemeyer, Matthias Rottmann, Hanno Gottschalk Understanding and Mitigating the Limitations of Prioritized Experience Replay
Yangchen Pan, Jincheng Mei, Amir-massoud Farahmand, Martha White, Hengshuai Yao, Mohsen Rohani, Jun Luo Variational Multiple Shooting for Bayesian ODEs with Gaussian Processes
Pashupati Hegde, Çağatay Yıldız, Harri Lähdesmäki, Samuel Kaski, Markus Heinonen Voronoi Density Estimator for High-Dimensional Data: Computation, Compactification and Convergence
Vladislav Polianskii, Giovanni Luca Marchetti, Alexander Kravberg, Anastasiia Varava, Florian T. Pokorny, Danica Kragic VQ-Flows: Vector Quantized Local Normalizing Flows
Sahil Sidheekh, Chris B. Dock, Tushar Jain, Radu Balan, Maneesh K. Singh