61 citations · 750 across the 66 of their papers we have counts for
8 papers · 1 filter
Nonparametric Composite Hypothesis Testing in an Asymptotic Regime
Qunwei Li, Tiexing Wang, Donald J. Bucci +3
We investigate the nonparametric, composite hypothesis testing problem for arbitrary unknown distributions in the asymptotic regime where both the sample size and the number of hyp…
Data-Driven Nonparametric Existence and Association Problems
Yixian Liu, Yingbin Liang, Shuguang Cui
We investigate two closely related nonparametric hypothesis testing problems. In the first problem (i.e., the existence problem), we test whether a testing data stream is generated…
Critical Points of Neural Networks: Analytical Forms and Landscape Properties
Yi Zhou, Yingbin Liang
Due to the success of deep learning to solving a variety of challenging machine learning tasks, there is a rising interest in understanding loss functions for training neural netwo…
Characterization of Gradient Dominance and Regularity Conditions for Neural Networks
Yi Zhou, Yingbin Liang
The past decade has witnessed a successful application of deep learning to solving many challenging problems in machine learning and artificial intelligence. However, the loss func…
Nonconvex Low-Rank Matrix Recovery with Arbitrary Outliers via Median-Truncated Gradient Descent
Yuanxin Li, Yuejie Chi, Huishuai Zhang +1
Recent work has demonstrated the effectiveness of gradient descent for directly recovering the factors of low-rank matrices from random linear measurements in a globally convergent…
Convergence Analysis of Proximal Gradient with Momentum for Nonconvex Optimization
Qunwei Li, Yi Zhou, Yingbin Liang +1
In many modern machine learning applications, structures of underlying mathematical models often yield nonconvex optimization problems. Due to the intractability of nonconvexity, t…