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Poster
Tue 7:00 Confidence Sets and Hypothesis Testing in a Likelihood-Free Inference Setting
Niccolo Dalmasso · Rafael Izbicki · Ann Lee
Poster
Tue 7:00 Efficient nonparametric statistical inference on population feature importance using Shapley values
Brian Williamson · Jean Feng
Poster
Tue 7:00 Data Amplification: Instance-Optimal Property Estimation
Yi Hao · Alon Orlitsky
Poster
Tue 7:00 NGBoost: Natural Gradient Boosting for Probabilistic Prediction
Tony Duan · Anand Avati · Daisy Ding · Khanh K. Thai · Sanjay Basu · Andrew Ng · Alejandro Schuler
Poster
Tue 10:00 Optimal Robust Learning of Discrete Distributions from Batches
Ayush Jain · Alon Orlitsky
Poster
Tue 10:00 When are Non-Parametric Methods Robust?
Robi Bhattacharjee · Kamalika Chaudhuri
Poster
Tue 10:00 Harmonic Decompositions of Convolutional Networks
Meyer Scetbon · Zaid Harchaoui
Poster
Tue 10:00 On the Theoretical Properties of the Network Jackknife
Qiaohui Lin · Robert Lunde · Purnamrita Sarkar
Poster
Tue 11:00 Consistent Structured Prediction with Max-Min Margin Markov Networks
Alex Nowak · Francis Bach · Alessandro Rudi
Poster
Tue 11:00 Learning Deep Kernels for Non-Parametric Two-Sample Tests
Feng Liu · Wenkai Xu · Jie Lu · Guangquan Zhang · Arthur Gretton · D.J. Sutherland
Poster
Tue 13:00 Distinguishing Cause from Effect Using Quantiles: Bivariate Quantile Causal Discovery
Natasa Tagasovska · ValĂ©rie Chavez-Demoulin · Thibault Vatter
Poster
Tue 14:00 Decentralised Learning with Random Features and Distributed Gradient Descent
Dominic Richards · Patrick Rebeschini · Lorenzo Rosasco