2 citations · 3 across the 3 of their papers we have counts for
4 papers
Learning to Augment via Implicit Differentiation for Domain Generalization
Tingwei Wang, Da Li, Kaiyang Zhou +2
Machine learning models are intrinsically vulnerable to domain shift between training and testing data, resulting in poor performance in novel domains. Domain generalization (DG) a…
DivAug: Plug-in Automated Data Augmentation with Explicit Diversity Maximization
Zirui Liu, Haifeng Jin, Ting-Hsiang Wang +2
Human-designed data augmentation strategies have been replaced by automatically learned augmentation policy in the past two years. Specifically, recent work has empirically shown t…
Towards Interaction Detection Using Topological Analysis on Neural Networks
Zirui Liu, Qingquan Song, Kaixiong Zhou +3
Detecting statistical interactions between input features is a crucial and challenging task. Recent advances demonstrate that it is possible to extract learned interactions from tr…
AutoRec: An Automated Recommender System
Ting-Hsiang Wang, Qingquan Song, Xiaotian Han +3
Realistic recommender systems are often required to adapt to ever-changing data and tasks or to explore different models systematically. To address the need, we present AutoRec, an…