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Oral
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Tue 7:00 |
Implications of sparsity and high triangle density for graph representation learning Hannah Sansford · Alexander Modell · Nick Whiteley · Patrick Rubin-Delanchy |
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Oral
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Thu 2:15 |
Federated Learning under Distributed Concept Drift Ellango Jothimurugesan · Kevin Hsieh · Jianyu Wang · Gauri Joshi · Phillip B Gibbons |
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Test Of Time
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Wed 5:00 |
Deep Gaussian Processes Neil Lawrence · Andreas Damianou |
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Invited Talk
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Thu 0:00 |
An Automatic Finite-Sample Robustness Check: Can Dropping a Little Data Change Conclusions? Tamara Broderick |
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Invited Talk
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Tue 0:00 |
Causal Effect Estimation with Context and Confounders Arthur Gretton |
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Poster
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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 |
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Poster
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Thu 5:00 |
Federated Averaging Langevin Dynamics: Toward a unified theory and new algorithms Vincent Plassier · Eric Moulines · Alain Durmus |
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Poster
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Thu 5:00 |
NODAGS-Flow: Nonlinear Cyclic Causal Structure Learning Muralikrishnna Guruswamy Sethuraman · Romain Lopez · Rahul Mohan · Faramarz Fekri · Tommaso Biancalani · Jan-Christian Huetter |
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Poster
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Tue 7:30 |
The ELBO of Variational Autoencoders Converges to a Sum of Entropies Simon Damm · Dennis Forster · Dmytro Velychko · Zhenwen Dai · Asja Fischer · Jörg Lücke |
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Poster
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Wed 7:30 |
Sparsity-Inducing Categorical Prior Improves Robustness of the Information Bottleneck Anirban Samaddar · Sandeep Madireddy · Prasanna Balaprakash · Tapabrata Maiti · Gustavo de los Campos · Ian Fischer |
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Poster
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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 |
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Poster
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Thu 5:00 |
Actually Sparse Variational Gaussian Processes Jake Cunningham · Daniel Augusto de Souza · So Takao · Mark van der Wilk · Marc Deisenroth |