UAI 2022

230 papers

Forget-me-not! Contrastive critics for mitigating posterior collapse

Sachit Menon, David Blei, Carl Vondrick

Multistate analysis with infinite mixtures of Markov chains

Lucas Maystre, Tiffany Wu, Roberto Sanchis-Ojeda, Tony Jebara

Case-based off-policy evaluation using prototype learning

Anton Matsson, Fredrik D. Johansson

A causal bandit approach to learning good atomic interventions in presence of unobserved confounders

Aurghya Maiti, Vineet Nair, Gaurav Sinha

Perturbation type categorization for multiple adversarial perturbation robustness

Pratyush Maini, Xinyun Chen, Bo Li, Dawn Song

Low-precision arithmetic for fast Gaussian processes

Wesley J. Maddox, Andres Potapcynski, Andrew Gordon Wilson

Data sampling affects the complexity of online SGD over dependent data

Shaocong Ma, Ziyi Chen, Yi Zhou, Kaiyi Ji, Yingbin Liang

Local calibration: metrics and recalibration

Rachel Luo, Aadyot Bhatnagar, Yu Bai, Shengjia Zhao, Huan Wang

Nonparametric exponential family graph embeddings for multiple representation learning

Chien Lu, Jaakko Peltonen, Timo Nummenmaa, Jyrki Nummenmaa

Data poisoning attacks on off-policy policy evaluation methods

Elita Lobo, Harvineet Singh, Marek Petrik, Cynthia Rudin, Himabindu Lakkaraju

Offline policy optimization with eligible actions

Yao Liu, Yannis Flet-Berliac, Emma Brunskill

SASH: Efficient secure aggregation based on SHPRG for federated learning

Zizhen Liu, Si Chen, Jing Ye, Junfeng Fan, Huawei Li

PathFlow: A normalizing flow generator that finds transition paths

Tianyi Liu, Weihao Gao, Zhirui Wang, Chong Wang

Federated online clustering of bandits

Xutong Liu, Haoru Zhao, Tong Yu, Shuai Li, John C.S. Lui

Dimension reduction for high-dimensional small counts with KL divergence

Yurong Ling, Jing-Hao Xue

Laplace approximated Gaussian process state-space models

Jakob Lindinger, Barbara Rakitsch, Christoph Lippert

AdaCat: Adaptive categorical discretization for autoregressive models

Qiyang Li, Ajay Jain, Pieter Abbeel

ℓ_∞-Bounds of the MLE in the BTL Model under General Comparison Graphs

Wanshan Li, Shamindra Shrotriya, Alessandro Rinaldo

A label efficient two-sample test

Weizhi Li, Gautam Dasarathy, Karthikeyan Natesan Ramamurthy, Visar Berisha

Efficient resource allocation with fairness constraints in restless multi-armed bandits

Dexun. Li, Pradeep Varakantham

Proportional allocation of indivisible resources under ordinal and uncertain preferences.

Zihao Li, Xiaohui Bei, Zhenzhen Yan

Deep Dirichlet process mixture models

Naiqi Li, Wenjie Li, Yong Jiang, Shu-Tao Xia

Accelerating training of batch normalization: A manifold perspective

Mingyang Yi

PDQ-Net: Deep probabilistic dual quaternion network for absolute pose regression on $SE(3)$

Wenjie Li, Wasif Naeem, Jia Liu, Dequan Zheng, Wei Hao

Solving structured hierarchical games using differential backward induction

Zun Li, Feiran Jia, Aditya Mate, Shahin Jabbari, Mithun Chakraborty

Recursive Monte Carlo and variational inference with auxiliary variables

Alexander K. Lew, Marco Cusumano-Towner, Vikash K. Mansinghka

Fixing the Bethe approximation: How structural modifications in a graph improve belief propagation

Harald Leisenberger, Franz Pernkopf, Christian Knoll

Systematized event-aware learning for multi-object tracking

Hyemin Lee, Daijin Kim

Interpolating between sampling and variational inference with infinite stochastic mixtures

Richard D. Lange, Ari S. Benjamin, Ralf M. Haefner, Xaq Pitkow

Greedy relaxations of the sparsest permutation algorithm

Wai-Yin Lam, Bryan Andrews, Joseph Ramsey

Calibrated ensembles can mitigate accuracy tradeoffs under distribution shift

Ananya Kumar, Tengyu Ma, Percy Liang, Aditi Raghunathan

Hitting times for continuous-time imprecise-Markov chains

Thomas Krak

Revisiting the general identifiability problem

Yaroslav Kivva, Ehsan Mokhtarian, Jalal Etesami, Negar Kiyavash

On the effectiveness of adversarial training against common corruptions

Klim Kireev, Maksym Andriushchenko, Nicolas Flammarion

Combinatorial Bayesian optimization with random mapping functions to convex polytopes

Jungtaek Kim, Seungjin Choi, Minsu Cho

Restless and uncertain: Robust policies for restless bandits via deep multi-agent reinforcement learning

Jackson A. Killian, Lily Xu, Arpita Biswas, Milind Tambe

Dynamic relocation in ridesharing via fixpoint construction

Ian A. Kash, Zhongkai Wen, Lenore D. Zuck

Improved feature importance computation for tree models based on the Banzhaf value

Adam Karczmarz, Tomasz Michalak, Anish Mukherjee, Piotr Sankowski, Piotr Wygocki

Test for non-negligible adverse shifts

Vathy M Kamulete

Optimal control of partially observable Markov decision processes with finite linear temporal logic constraints

Krishna C. Kalagarla, Kartik Dhruva, Dongming Shen, Rahul Jain, Ashutosh Nayyar

Decision-theoretic planning with communication in open multiagent systems

Anirudh Kakarlapudi, Gayathri Anil, Adam Eck, Prashant Doshi, Leen-Kiat Soh

If you’ve trained one you’ve trained them all: inter-architecture similarity increases with robustness

Haydn T. Jones, Jacob M. Springer, Garrett T. Kenyon, Juston S. Moore

Orthogonal Gromov-Wasserstein discrepancy with efficient lower bound

Hongwei Jin, Zishun Yu, Xinhua Zhang

Fedvarp: Tackling the variance due to partial client participation in federated learning

Divyansh Jhunjhunwala, PRANAY SHARMA, Aushim Nagarkatti, Gauri Joshi

Towards painless policy optimization for constrained MDPs

Arushi Jain, Sharan Vaswani, Reza Babanezhad, Csaba Szepesvári, Doina Precup

Balancing utility and scalability in metric differential privacy

Jacob Imola, Shiva Kasiviswanathan, Stephen White, Abhinav Aggarwal, Nathanael Teissier

Binary independent component analysis: a non-stationarity-based approach

Antti Hyttinen, Vitória Barin Pacela, Aapo Hyvärinen

A mutually exciting latent space Hawkes process model for continuous-time networks

Zhipeng Huang, Hadeel Soliman, Subhadeep Paul, Kevin S. Xu

Uncertainty-aware pseudo-labeling for quantum calculations

Kexin Huang, Vishnu Sresht, Brajesh Rai, Mykola Bordyuh

Near-optimal Thompson sampling-based algorithms for differentially private stochastic bandits

Bingshan Hu, Nidhi Hegde

CIGMO: Categorical invariant representations in a deep generative framework

Haruo Hosoya

Fast predictive uncertainty for classification with Bayesian deep networks

Marius Hobbhahn, Agustinus Kristiadi, Philipp Hennig

Quadratic metric elicitation for fairness and beyond

Gaurush Hiranandani, Jatin Mathur, Harikrishna Narasimhan, Oluwasanmi Koyejo

Learning sparse representations of preferences within Choquet expected utility theory

Margot Herin, Patrice Perny, Nataliya Sokolovska

Variational multiple shooting for Bayesian ODEs with Gaussian processes

Pashupati Hegde, Çağatay Yıldız, Harri Lahdesmaki, Samuel Kaski, Markus Heinonen

Reinforcement learning in many-agent settings under partial observability

Keyang He, Prashant Doshi, Bikramjit Banerjee

Generalizing off-policy learning under sample selection bias

Tobias Hatt, Daniel Tschernutter, Stefan Feuerriegel

Modeling extremes with d-max-decreasing neural networks

Ali Hasan, Khalil Elkhalil, Yuting Ng, João M. Pereira, Sina Farsiu

Learning a neural Pareto manifold extractor with constraints

Soumyajit Gupta, Gurpreet Singh, Raghu Bollapragada, \Matthew Lease

Efficient and transferable adversarial examples from bayesian neural networks

Martin Gubri, Maxime Cordy, Mike Papadakis, Yves Le Traon, Koushik Sen

Robust expected information gain for optimal Bayesian experimental design using ambiguity sets

Jinwoo Go, Tobin Isaac

Do Bayesian variational autoencoders know what they don’t know?

Misha Glazunov, Apostolis Zarras

Neural-progressive hedging: Enforcing constraints in reinforcement learning with stochastic programming

Supriyo Ghosh, Laura Wynter, Shiau Hong Lim, Duc Thien Nguyen

Mitigating statistical bias within differentially private synthetic data

Sahra Ghalebikesabi, Harry Wilde, Jack Jewson, Arnaud Doucet, Sebastian Vollmer

Estimating transfer entropy under long ranged dependencies

Sahil Garg, Umang Gupta, Yu Chen, Syamantak Datta Gupta, Yeshaya Adler

Sequential algorithmic modification with test data reuse

Jean Feng, Gene Pennllo, Nicholas Petrick, Berkman Sahiner, Romain Pirracchio

Self-distribution distillation: efficient uncertainty estimation

Yassir Fathullah, Mark J. F. Gales

Implicit kernel meta-learning using kernel integral forms

John Isak Texas Falk, Carlo Cilibert, Massimiliano Pontil

Temporal abstractions-augmented temporally contrastive learning: An alternative to the Laplacian in RL

Akram Erraqabi, Marlos C. Machado, Mingde Zhao, Sainbayar Sukhbaatar, Alessandro Lazaric

SENTINEL: taming uncertainty with ensemble based distributional reinforcement learning

Hannes Eriksson, Debabrota Basu, Mina Alibeigi, Christos Dimitrakakis

Learning explainable templated graphical models

Varun Embar, Sriram Srinivasa, Lise Getoor

ResIST: Layer-wise decomposition of ResNets for distributed training

Chen Dun, Cameron R. Wolfe, Christopher M. Jermaine, Anastasios Kyrillidis

Improving sign-random-projection via count sketch

Punit Pankaj Dubey, Bhisham Dev Verma, Rameshwar Pratap, Keegan Kang

X-MEN: guaranteed XOR-maximum entropy constrained inverse reinforcement learning

Fan Ding, Yexiang Xue

Revisiting DP-Means: fast scalable algorithms via parallelism and delayed cluster creation

Or Dinari, Oren Freifeld

Variational- and metric-based deep latent space for out-of-distribution detection

Or Dinari, Oren Freifeld

Balancing adaptability and non-exploitability in repeated games

Anthony DiGiovanni, Ambuj Tewari

Quantification of Credal Uncertainty in Machine Learning: A Critical Analysis and Empirical Comparison

Eyke Hüllermeier, Sébastien Destercke, Mohammad Hossein Shaker

Multiclass classification for Hawkes processes

Christophe Denis, Charlotte Dion-Blanc, Laure Sansonnet

Bayesian spillover graphs for dynamic networks

Grace Deng, David S. Matteson

Bayesian structure learning with generative flow networks

Tristan Deleu, António Góis, Chris Emezue, Mansi Rankawat, Simon Lacoste-Julien

Multi-objective Bayesian optimization over high-dimensional search spaces

Samuel Daulton, David Eriksson, Maximilian Balandat, Eytan Bakshy

Faster non-convex federated learning via global and local momentum

Rudrajit Das, Anish Acharya, Abolfazl Hashemi, Sujay Sanghavi, Inderjit S. Dhillon

Individual fairness in feature-based pricing for monopoly markets

Shantanu Das, Swapnil Dhamal, Ganesh Ghalme, Shweta Jain, Sujit Gujar

On provably robust meta-Bayesian optimization

Zhongxiang Dai, Yizhou Chen, Haibin YU, Bryan Kian Hsiang Low, Patrick Jaillet

Variational message passing neural network for Maximum-A-Posteriori (MAP) inference

Zijun Cui, Hanjing Wang, Tian Gao, Kartik Talamadupula, Qiang Ji

Counterfactual inference of second Opinions

Nina L. Corvelo Benz, Manuel Gomez Rodriguez

Greedy equivalence search in the presence of latent confounders

Tom Claassen, Ioan G. Bucur

Cyclic test time augmentation with entropy weight method

Sewhan Chun, Jae Young Lee, Junmo Kim

A geometric method for improved uncertainty estimation in real-time

Gabriella Chouraqui, Liron Cohen, Gil Einziger, Liel Leman

Combating the instability of mutual information-based losses via regularization

Kwanghee Choi, Siyeong Lee

Feature selection for discovering distributional treatment effect modifiers

Yoichi Chikahara, Makoto Yamada, Hisashi Kashima

Greedy modality selection via approximate submodular maximization

Runxiang Cheng, Gargi Balasubramaniam, Yifei He, Yao-Hung Hubert Tsai, Han Zhao

Offline reinforcement learning under value and density-ratio realizability: The power of gaps

Jinglin Chen, Nan Jiang

On the definition and computation of causal treewidth

Yizuo Chen, Adnan Darwiche

Shoring up the foundations: fusing model embeddings and weak supervision

Mayee F. Chen, Daniel Y. Fu, Dyah Adila, Michael Zhang, Frederic Sala

Sublinear time algorithms for greedy selection in high dimensions

Qi Chen, Kai Liu, Ruilong Yao, Hu Ding

Knowledge representation combining quaternion path integration and depth-wise atrous circular convolution

Xinyuan Chen, Zhongmei Zhou, Meichun Gao, Daya Shi, Mohd N. Husen

Stackmix: a complementary mix algorithm

John Chen, Samarth Sinha, Anastasios Kyrillidis

A competitive analysis of online failure-aware assignment

Mengjing Chen, Pingzhong Tang, Zihe Wang, Shenke Xiao, Xiwang Yang