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Invited Talk
Tue 9:00 Reliable Predictions? Counterfactual Predictions? Equitable Treatment? Some Recent Progress in Predictive Inference
Emmanuel Candes
Oral
Tue 11:00 Towards a Theoretical Understanding of the Robustness of Variational Autoencoders
Alexander Camuto · Matthew Willetts · Stephen Roberts · Chris Holmes · Tom Rainforth
Oral
Tue 12:15 GANs with Conditional Independence Graphs: On Subadditivity of Probability Divergences
Mucong Ding · Constantinos Daskalakis · Soheil Feizi
Poster
Tue 14:00 Fundamental Limits of Ridge-Regularized Empirical Risk Minimization in High Dimensions
Hossein Taheri · Ramtin Pedarsani · Christos Thrampoulidis
Poster
Tue 14:00 List Learning with Attribute Noise
Mahdi Cheraghchi · Elena Grigorescu · Brendan Juba · Karl Wimmer · Ning Xie
Poster
Tue 14:00 An Efficient Algorithm For Generalized Linear Bandit: Online Stochastic Gradient Descent and Thompson Sampling
QIN DING · Cho-Jui Hsieh · James Sharpnack
Poster
Tue 14:00 The Sample Complexity of Meta Sparse Regression
Zhanyu Wang · Jean Honorio
Poster
Tue 14:00 Designing Transportable Experiments Under S-admissability
My Phan · David Arbour · Drew Dimmery · Anup Rao
Poster
Tue 14:00 Matérn Gaussian Processes on Graphs
Viacheslav Borovitskiy · Iskander Azangulov · Alexander Terenin · Peter Mostowsky · Marc Deisenroth · Nicolas Durrande
Poster
Tue 14:00 Variational Selective Autoencoder: Learning from Partially-Observed Heterogeneous Data
Yu Gong · Hossein Hajimirsadeghi · Jiawei He · Thibaut Durand · Greg Mori
Poster
Tue 14:00 The Minecraft Kernel: Modelling correlated Gaussian Processes in the Fourier domain
Fergus Simpson · Alexis Boukouvalas · Vaclav Cadek · Elvijs Sarkans · Nicolas Durrande
Poster
Tue 14:00 Counterfactual Representation Learning with Balancing Weights
Serge Assaad · Shuxi Zeng · Chenyang Tao · Shounak Datta · Nikhil Mehta · Ricardo Henao · Fan Li · Lawrence Carin Duke