253 citations · 745 across the 24 of their papers we have counts for
16 papers · 1 filter
On the Anomalous Generalization of GANs
Jinchen Xuan, Yunchang Yang, Ze Yang +2
Generative models, especially Generative Adversarial Networks (GANs), have received significant attention recently. However, it has been observed that in terms of some attributes,…
Hint-Based Training for Non-Autoregressive Machine Translation
Zhuohan Li, Zi Lin, Di He +4
Due to the unparallelizable nature of the autoregressive factorization, AutoRegressive Translation (ART) models have to generate tokens sequentially during decoding and thus suffer…
McDiarmid-Type Inequalities for Graph-Dependent Variables and Stability Bounds
Rui Ray Zhang, Xingwu Liu, Yuyi Wang +1
A crucial assumption in most statistical learning theory is that samples are independently and identically distributed (i.i.d.). However, for many real applications, the i.i.d. ass…
Robust Local Features for Improving the Generalization of Adversarial Training
Chuanbiao Song, Kun He, Jiadong Lin +2
Adversarial training has been demonstrated as one of the most effective methods for training robust models to defend against adversarial examples. However, adversarially trained mo…
Few-Shot Learning with Global Class Representations
Tiange Luo, Aoxue Li, Tao Xiang +2
In this paper, we propose to tackle the challenging few-shot learning (FSL) problem by learning global class representations using both base and novel class training samples. In ea…
Nesterov Accelerated Gradient and Scale Invariance for Adversarial Attacks
Jiadong Lin, Chuanbiao Song, Kun He +2
Deep learning models are vulnerable to adversarial examples crafted by applying human-imperceptible perturbations on benign inputs. However, under the black-box setting, most exist…