4 papers
Reward Selection with Noisy Observations
Kamyar Azizzadenesheli, Trung Dang, Aranyak Mehta +2
We study a fundamental problem in optimization under uncertainty. There are boxes; each box contains a hidden reward . Rewards are drawn i.i.d. from an unknown distrib…
Universal Rates for Multiclass Learning
Steve Hanneke, Shay Moran, Qian Zhang
We study universal rates for multiclass classification, establishing the optimal rates (up to log factors) for all hypothesis classes. This generalizes previous results on binary c…
Matrix optimization based Euclidean embedding with outliers
Qian Zhang, Xinyuan Zhao, Chao Ding
Euclidean embedding from noisy observations containing outlier errors is an important and challenging problem in statistics and machine learning. Many existing methods would strugg…
Meta Learning for Support Recovery in High-dimensional Precision Matrix Estimation
Qian Zhang, Yilin Zheng, Jean Honorio
In this paper, we study meta learning for support (i.e., the set of non-zero entries) recovery in high-dimensional precision matrix estimation where we reduce the sufficient sample…