most citedImproving Robustness of Deep-Learning-Based Image Reconstruction

15 citations · 27 across the 3 of their papers we have counts for

collaborators

6 papers

cs.CL20208 cited

Towards Evaluating the Robustness of Chinese BERT Classifiers

Boxin Wang, Boyuan Pan, Xin Li +1

Recent advances in large-scale language representation models such as BERT have improved the state-of-the-art performances in many NLP tasks. Meanwhile, character-level Chinese NLP…

cs.LG202015 cited

Improving Robustness of Deep-Learning-Based Image Reconstruction

Ankit Raj, Yoram Bresler, Bo Li

Deep-learning-based methods for different applications have been shown vulnerable to adversarial examples. These examples make deployment of such models in safety-critical tasks qu…

q-fin.PM20204 cited

Reinforcement-Learning based Portfolio Management with Augmented Asset Movement Prediction States

Yunan Ye, Hengzhi Pei, Boxin Wang +4

Portfolio management (PM) is a fundamental financial planning task that aims to achieve investment goals such as maximal profits or minimal risks. Its decision process involves con…

cs.LG2019

The Secret Revealer: Generative Model-Inversion Attacks Against Deep Neural Networks

Yuheng Zhang, Ruoxi Jia, Hengzhi Pei +3

This paper studies model-inversion attacks, in which the access to a model is abused to infer information about the training data. Since its first introduction, such attacks have r…

cs.AI2019

Detecting AI Trojans Using Meta Neural Analysis

Xiaojun Xu, Qi Wang, Huichen Li +3

In machine learning Trojan attacks, an adversary trains a corrupted model that obtains good performance on normal data but behaves maliciously on data samples with certain trigger…

cs.CR2019

To Warn or Not to Warn: Online Signaling in Audit Games

Chao Yan, Haifeng Xu, Yevgeniy Vorobeychik +3

Routine operational use of sensitive data is often governed by law and regulation. For instance, in the medical domain, there are various statues at the state and federal level tha…