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Thu 5:00 Nonstochastic Contextual Combinatorial Bandits
Lukas Zierahn · Dirk van der Hoeven · Nicolò Cesa-Bianchi · Gergely Neu
Thu 5:00 Sampling From a Schrödinger Bridge
Austin J. Stromme
Wed 7:30 Generalization in Graph Neural Networks: Improved PAC-Bayesian Bounds on Graph Diffusion
Haotian Ju · Dongyue Li · Aneesh Sharma · Hongyang Zhang
Wed 7:30 Algorithm for Constrained Markov Decision Process with Linear Convergence
Egor Gladin · Maksim Lavrik-Karmazin · Karina Zainullina · Varvara Rudenko · Alexander Gasnikov · Martin Takac
Thu 5:00 Adversarial robustness of VAEs through the lens of local geometry
Asif Khan · Amos Storkey
Thu 5:00 Recurrent Neural Networks and Universal Approximation of Bayesian Filters
Adrian N. Bishop · Edwin V. Bonilla
Tue 7:00 Implications of sparsity and high triangle density for graph representation learning
Hannah Sansford · Alexander Modell · Nick Whiteley · Patrick Rubin-Delanchy
Thu 2:15 Federated Learning under Distributed Concept Drift
Ellango Jothimurugesan · Kevin Hsieh · Jianyu Wang · Gauri Joshi · Phillip B Gibbons
Test Of Time
Wed 5:00 Deep Gaussian Processes
Neil Lawrence · Andreas Damianou
Invited Talk
Thu 0:00 An Automatic Finite-Sample Robustness Check: Can Dropping a Little Data Change Conclusions?
Tamara Broderick
Invited Talk
Tue 0:00 Causal Effect Estimation with Context and Confounders
Arthur Gretton
Tue 7:30 Fixing by Mixing: A Recipe for Optimal Byzantine ML under Heterogeneity
Youssef Allouah · Sadegh Farhadkhani · Rachid Guerraoui · Nirupam Gupta · Rafael Pinot · John Stephan