51 citations · 72 across the 5 of their papers we have counts for
5 papers
Improving Textual Network Embedding with Global Attention via Optimal Transport
Liqun Chen, Guoyin Wang, Chenyang Tao +6
Constituting highly informative network embeddings is an important tool for network analysis. It encodes network topology, along with other useful side information, into low-dimens…
On Norm-Agnostic Robustness of Adversarial Training
Bai Li, Changyou Chen, Wenlin Wang +1
Adversarial examples are carefully perturbed in-puts for fooling machine learning models. A well-acknowledged defense method against such examples is adversarial training, where ad…
InverseNet: Solving Inverse Problems with Splitting Networks
Kai Fan, Qi Wei, Wenlin Wang +2
We propose a new method that uses deep learning techniques to solve the inverse problems. The inverse problem is cast in the form of learning an end-to-end mapping from observed da…
Zero-Shot Learning via Class-Conditioned Deep Generative Models
Wenlin Wang, Yunchen Pu, Vinay Kumar Verma +5
We present a deep generative model for learning to predict classes not seen at training time. Unlike most existing methods for this problem, that represent each class as a point (v…
A Convergence Analysis for A Class of Practical Variance-Reduction Stochastic Gradient MCMC
Changyou Chen, Wenlin Wang, Yizhe Zhang +2
Stochastic gradient Markov Chain Monte Carlo (SG-MCMC) has been developed as a flexible family of scalable Bayesian sampling algorithms. However, there has been little theoretical…