|
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 · Valérie Chavez-Demoulin · Thibault Vatter |
|
|
Poster
|
Tue 14:00 |
Decentralised Learning with Random Features and Distributed Gradient Descent Dominic Richards · Patrick Rebeschini · Lorenzo Rosasco |