16 citations · 51 across the 13 of their papers we have counts for
4 papers · 1 filter
Rectified Pessimistic-Optimistic Learning for Stochastic Continuum-armed Bandit with Constraints
Hengquan Guo, Qi Zhu, Xin Liu
This paper studies the problem of stochastic continuum-armed bandit with constraints (SCBwC), where we optimize a black-box reward function subject to a black-box constraint…
Adversarial and Random Transformations for Robust Domain Adaptation and Generalization
Liang Xiao, Jiaolong Xu, Dawei Zhao +3
Data augmentation has been widely used to improve generalization in training deep neural networks. Recent works show that using worst-case transformations or adversarial augmentati…
Look Closer to Supervise Better: One-Shot Font Generation via Component-Based Discriminator
Yuxin Kong, Canjie Luo, Weihong Ma +4
Automatic font generation remains a challenging research issue due to the large amounts of characters with complicated structures. Typically, only a few samples can serve as the st…
Semi-supervised Semantics-guided Adversarial Training for Trajectory Prediction
Ruochen Jiao, Xiangguo Liu, Takami Sato +2
Predicting the trajectories of surrounding objects is a critical task for self-driving vehicles and many other autonomous systems. Recent works demonstrate that adversarial attacks…