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Invited Talk
Tue 9:00 Reliable Predictions? Counterfactual Predictions? Equitable Treatment? Some Recent Progress in Predictive Inference
Emmanuel Candes
Tue 11:00 Towards a Theoretical Understanding of the Robustness of Variational Autoencoders
Alexander Camuto · Matthew Willetts · Stephen Roberts · Chris Holmes · Tom Rainforth
Tue 12:15 GANs with Conditional Independence Graphs: On Subadditivity of Probability Divergences
Mucong Ding · Constantinos Daskalakis · Soheil Feizi
Tue 14:00 Fast Adaptation with Linearized Neural Networks
Wesley Maddox · Shuai Tang · Pablo Moreno · Andrew Gordon Wilson · Andreas Damianou
Tue 14:00 Matérn Gaussian Processes on Graphs
Viacheslav Borovitskiy · Iskander Azangulov · Alexander Terenin · Peter Mostowsky · Marc Deisenroth · Nicolas Durrande
Tue 14:00 Variational Selective Autoencoder: Learning from Partially-Observed Heterogeneous Data
Yu Gong · Hossein Hajimirsadeghi · Jiawei He · Thibaut Durand · Greg Mori
Tue 14:00 On the Linear Convergence of Policy Gradient Methods for Finite MDPs
Jalaj Bhandari · Daniel Russo
Tue 14:00 Simultaneously Reconciled Quantile Forecasting of Hierarchically Related Time Series
Xing Han · Sambarta Dasgupta · Joydeep Ghosh
Tue 14:00 An Optimal Reduction of TV-Denoising to Adaptive Online Learning
Dheeraj Baby · Xuandong Zhao · Yu-Xiang Wang
Tue 14:00 Cluster Trellis: Data Structures & Algorithms for Exact Inference in Hierarchical Clustering
Sebastian Macaluso · Craig Greenberg · Nicholas Monath · Ji Ah Lee · Patrick Flaherty · Kyle Cranmer · Andrew McGregor · Andrew McCallum
Tue 14:00 The Minecraft Kernel: Modelling correlated Gaussian Processes in the Fourier domain
Fergus Simpson · Alexis Boukouvalas · Vaclav Cadek · Elvijs Sarkans · Nicolas Durrande
Tue 14:00 Does Invariant Risk Minimization Capture Invariance?
Pritish Kamath · Akilesh Tangella · Danica Sutherland · Nathan Srebro