17 citations · 18 across the 5 of their papers we have counts for
6 papers
Deep Semi-supervised Learning with Double-Contrast of Features and Semantics
Quan Feng, Jiayu Yao, Zhison Pan +1
In recent years, the field of intelligent transportation systems (ITS) has achieved remarkable success, which is mainly due to the large amount of available annotation data. Howeve…
A Convergence Analysis of Nesterov's Accelerated Gradient Method in Training Deep Linear Neural Networks
Xin Liu, Wei Tao, Zhisong Pan
Momentum methods, including heavy-ball~(HB) and Nesterov's accelerated gradient~(NAG), are widely used in training neural networks for their fast convergence. However, there is a l…
Gradient Descent Averaging and Primal-dual Averaging for Strongly Convex Optimization
Wei Tao, Wei Li, Zhisong Pan +1
Averaging scheme has attracted extensive attention in deep learning as well as traditional machine learning. It achieves theoretically optimal convergence and also improves the emp…
Weakness Analysis of Cyberspace Configuration Based on Reinforcement Learning
Lei Zhang, Wei Bai, Shize Guo +3
In this work, we present a learning-based approach to analysis cyberspace configuration. Unlike prior methods, our approach has the ability to learn from past experience and improv…
The Strength of Nesterov's Extrapolation in the Individual Convergence of Nonsmooth Optimization
W. Tao, Z. Pan, G. Wu +1
The extrapolation strategy raised by Nesterov, which can accelerate the convergence rate of gradient descent methods by orders of magnitude when dealing with smooth convex objectiv…
MODA: MOdule Differential Analysis for weighted gene co-expression network
Dong Li, James B. Brown, Luisa Orsini +3
Gene co-expression network differential analysis is designed to help biologists understand gene expression patterns under different condition. By comparing different gene co-expres…