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20172022
most citedTwo Time-scale Off-Policy TD Learning: Non-asymptotic Analysis over Markovian Samples

42 citations · 268 across the 20 of their papers we have counts for

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5 papers · 1 filter

stat.ML20191 cited

Distributed SGD Generalizes Well Under Asynchrony

Jayanth Regatti, Gaurav Tendolkar, Yi Zhou +2

The performance of fully synchronized distributed systems has faced a bottleneck due to the big data trend, under which asynchronous distributed systems are becoming a major popula…

stat.ML2018

Generalization Error Bounds with Probabilistic Guarantee for SGD in Nonconvex Optimization

Yi Zhou, Yingbin Liang, Huishuai Zhang

The success of deep learning has led to a rising interest in the generalization property of the stochastic gradient descent (SGD) method, and stability is one popular approach to s…

stat.ML2018

Guaranteed Recovery of One-Hidden-Layer Neural Networks via Cross Entropy

Haoyu Fu, Yuejie Chi, Yingbin Liang

We study model recovery for data classification, where the training labels are generated from a one-hidden-layer neural network with sigmoid activations, also known as a single-lay…

stat.ML201730 cited

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…

stat.ML201726 cited

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…