UAI 2022

230 papers

The optimal noise in noise-contrastive learning is not what you think

Omar Chehab, Alexandre Gramfort, Aapo Hyvärinen

Privacy-aware compression for federated data analysis

Kamalika Chaudhuri, Chuan Guo, Mike Rabbat

Capturing actionable dynamics with structured latent ordinary differential equations

Paidamoyo Chapfuwa, Sherri Rose, Lawrence Carin, Edward Meeds, Ricardo Henao

Active approximately metric-fair learning

Yiting Cao, Chao Lan

AUTM flow: atomic unrestricted time machine for monotonic normalizing flows

Difeng Cai, Yuliang Ji, Huan He, Qiang Ye, Yuanzhe Xi

On the inductive bias of neural networks for learning read-once DNFs

Ido Bronstein, Alon Brutzkus, Amir Globerson

On-the-fly adaptation of patrolling strategies in changing environments

Tomáš Brázdil, David Klaška, Antonı́n Kučera, Vı́t Musil, Petr Novotný

Lifting in multi-agent systems under uncertainty

Tanya Braun, Marcel Gehrke, Florian Lau, Ralf Möller

Information theoretic approach to detect collusion in multi-agent games

Trevor Bonjour, Vaneet Aggarwal, Bharat Bhargava

Robustness of model predictions under extension

Tineke Blom, Joris M. Mooij

On testability of the front-door model via Verma constraints

Rohit Bhattacharya, Razieh Nabi

Offline change detection under contamination

Sujay Bhatt, Guanhua Fang, Ping Li

Identifying near-optimal decisions in linear-in-parameter bandit models with continuous decision sets

Sanjay P. Bhat, Chaitanya Amballa

Learning soft interventions in complex equilibrium systems

Michel Besserve, Bernhard Schölkopf

On early extinction and the effect of travelling in the SIR model

Petra Berenbrink, Colin Cooper, Cristina Gava, David Kohan Marzagão, Frederik Mallmann-Trenn

Empirical bayes approach to truth discovery problems

Tsviel Ben Shabat, Reshef Meir, David Azriel

Equilibrium aggregation: encoding sets via optimization

Sergey Bartunov, Fabian B. Fuchs, Timothy P. Lillicrap

Byzantine-tolerant distributed multiclass sparse linear discriminant analysis

Yajie Bao, Weidong Liu, Xiaojun Mao, Weijia Xiong

Physics guided neural networks for spatio-temporal super-resolution of turbulent flows

Tianshu Bao, Shengyu Chen, Taylor T Johnson, Peyman Givi, Shervin Sammak

Asymmetric DQN for partially observable reinforcement learning

Andrea Baisero, Brett Daley, Christopher Amato

Discovery of extended summary graphs in time series

Charles K. Assaad, Emilie Devijver, Eric Gaussier

Inductive synthesis of finite-state controllers for POMDPs

Roman Andriushchenko, Milan Ceska, Sebastian Junges, Joost-Pieter Katoen

Multi-winner approval voting goes epistemic

Tahar Allouche, Jérôme Lang, Florian Yger

Data dependent randomized smoothing

Motasem Alfarra, Adel Bibi, Philip H. S. Torr, Bernard Ghanem

Non-parametric inference of relational dependence

Ragib Ahsan, Zahra Fatemi, David Arbour, Elena Zheleva

Neuro-symbolic entropy regularization

Kareem Ahmed, Eric Wang, Kai-Wei Chang, Guy Van den Broeck

GNN2GNN: Graph neural networks to generate neural networks

Andrea Agiollo, Andrea Omicini

Regret guarantees for model-based reinforcement learning with long-term average constraints

Mridul Agarwal, Qinbo Bai, Vaneet Aggarwal

NeuroBE: Escalating neural network approximations of Bucket Elimination

Sakshi Agarwal, Kalev Kask, Alex Ihler, Rina Dechter

Mutation-driven follow the regularized leader for last-iterate convergence in zero-sum games

Kenshi Abe, Mitsuki Sakamoto, Atsushi Iwasaki