185 citations · 617 across the 26 of their papers we have counts for
10 papers · 1 filter
Graph-Driven Generative Models for Heterogeneous Multi-Task Learning
Wenlin Wang, Hongteng Xu, Zhe Gan +6
We propose a novel graph-driven generative model, that unifies multiple heterogeneous learning tasks into the same framework. The proposed model is based on the fact that heterogen…
Zero-Shot Recognition via Optimal Transport
Wenlin Wang, Hongteng Xu, Guoyin Wang +2
We propose an optimal transport (OT) framework for generalized zero-shot learning (GZSL), seeking to distinguish samples for both seen and unseen classes, with the assist of auxili…
Improving Textual Network Learning with Variational Homophilic Embeddings
Wenlin Wang, Chenyang Tao, Zhe Gan +7
The performance of many network learning applications crucially hinges on the success of network embedding algorithms, which aim to encode rich network information into low-dimensi…
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…
Distilled Wasserstein Learning for Word Embedding and Topic Modeling
Hongteng Xu, Wenlin Wang, Wei Liu +1
We propose a novel Wasserstein method with a distillation mechanism, yielding joint learning of word embeddings and topics. The proposed method is based on the fact that the Euclid…
Certified Adversarial Robustness with Additive Noise
Bai Li, Changyou Chen, Wenlin Wang +1
The existence of adversarial data examples has drawn significant attention in the deep-learning community; such data are seemingly minimally perturbed relative to the original data…