activity
20172021
most citedMUSE: Multi-Scale Temporal Features Evolution for Knowledge Tracing

2 citations · 3 across the 3 of their papers we have counts for

collaborators

5 papers

cs.LG20211 cited

Energy Attack: On Transferring Adversarial Examples

Ruoxi Shi, Borui Yang, Yangzhou Jiang +2

In this work we propose Energy Attack, a transfer-based black-box -adversarial attack. The attack is parameter-free and does not require gradient approximation. In partic…

cs.AI20212 cited

MUSE: Multi-Scale Temporal Features Evolution for Knowledge Tracing

Chengwei Zhang, Yangzhou Jiang, Wei Zhang +1

Transformer based knowledge tracing model is an extensively studied problem in the field of computer-aided education. By integrating temporal features into the encoder-decoder stru…

cs.CR2020

Learning Black-Box Attackers with Transferable Priors and Query Feedback

Jiancheng Yang, Yangzhou Jiang, Xiaoyang Huang +2

This paper addresses the challenging black-box adversarial attack problem, where only classification confidence of a victim model is available. Inspired by consistency of visual sa…

cs.LG2019

Neural Architecture Refinement: A Practical Way for Avoiding Overfitting in NAS

Yang Jiang, Cong Zhao, Zeyang Dou +1

Neural architecture search (NAS) is proposed to automate the architecture design process and attracts overwhelming interest from both academia and industry. However, it is confront…

cs.LG2017

An Effective Training Method For Deep Convolutional Neural Network

Yang Jiang, Zeyang Dou, Qun Hao +3

In this paper, we propose the nonlinearity generation method to speed up and stabilize the training of deep convolutional neural networks. The proposed method modifies a family of…