Oral Session

Wed 10:30

Optimization / Learning Theory / Generalization

Oral

Thu 15:15

A constrained risk inequality for general losses
John Duchi · Feng Ruan

Poster

Tue 14:00

A constrained risk inequality for general losses
John Duchi · Feng Ruan

Poster

Wed 6:00

Nonparametric Estimation of Heterogeneous Treatment Effects: From Theory to Learning Algorithms
Alicia Curth · Mihaela van der Schaar

Poster

Wed 12:45

On the Minimax Optimality of the EM Algorithm for Learning Two-Component Mixed Linear Regression
Jeongyeol Kwon · Nhat Ho · Constantine Caramanis

Poster

Wed 12:45

Direct Loss Minimization for Sparse Gaussian Processes
Yadi Wei · Rishit Sheth · Roni Khardon

Poster

Tue 14:00

Sharp Analysis of a Simple Model for Random Forests
Jason Klusowski

Poster

Wed 12:45

Learning Prediction Intervals for Regression: Generalization and Calibration
Haoxian Chen · Ziyi Huang · Henry Lam · Huajie Qian · Haofeng Zhang

Poster

Thu 7:30

Instance-Wise Minimax-Optimal Algorithms for Logistic Bandits
Marc Abeille · Louis Faury · Clement Calauzenes

Poster

Thu 7:30

Hadamard Wirtinger Flow for Sparse Phase Retrieval
Fan Wu · Patrick Rebeschini

Poster

Tue 14:00

Minimax Optimal Regression over Sobolev Spaces via Laplacian Regularization on Neighborhood Graphs
Alden Green · Sivaraman Balakrishnan · Ryan Tibshirani

Poster

Wed 12:45

Efficient Designs Of SLOPE Penalty Sequences In Finite Dimension
Yiliang Zhang · Zhiqi Bu