activity
20172021
most citedAdversarial Examples: Attacks and Defenses for Deep Learning

221 citations · 269 across the 8 of their papers we have counts for

collaborators

8 papers

cs.LG2021★ 11 cited

A Vertical Federated Learning Framework for Horizontally Partitioned Labels

Wensheng Xia, Ying Li, Lan Zhang +2

Vertical federated learning is a collaborative machine learning framework to train deep leaning models on vertically partitioned data with privacy-preservation. It attracts much at…

astro-ph.GA2019★ 14 cited

Identifying MgII Narrow Absorption Lines with Deep Learning

Yinan Zhao, Jian Ge, Xiaoyong Yuan +3

Metal absorption line systems in distant quasar spectra probe of the history of gas content in the universe. The MgII 2796, 2803 doublet is one of the most important absorptio…

cs.LG2018★ 1 cited

Generalized Batch Normalization: Towards Accelerating Deep Neural Networks

Xiaoyong Yuan, Zheng Feng, Matthew Norton +1

Utilizing recently introduced concepts from statistics and quantitative risk management, we present a general variant of Batch Normalization (BN) that offers accelerated convergenc…

cs.CV2018★ 9 cited

Adaptive Adversarial Attack on Scene Text Recognition

Xiaoyong Yuan, Pan He, Xiaolin Andy Li +1

Recent studies have shown that state-of-the-art deep learning models are vulnerable to the inputs with small perturbations (adversarial examples). We observe two critical obstacles…

cs.CR2018

A Praise for Defensive Programming: Leveraging Uncertainty for Effective Malware Mitigation

Ruimin Sun, Marcus Botacin, Nikolaos Sapountzis +6

A promising avenue for improving the effectiveness of behavioral-based malware detectors would be to combine fast traditional machine learning detectors with high-accuracy, but tim…

cs.LG2017★ 221 cited

Adversarial Examples: Attacks and Defenses for Deep Learning

Xiaoyong Yuan, Pan He, Qile Zhu +1

With rapid progress and significant successes in a wide spectrum of applications, deep learning is being applied in many safety-critical environments. However, deep neural networks…

cs.CR2017★ 12 cited

Learning Fast and Slow: PROPEDEUTICA for Real-time Malware Detection

Ruimin Sun, Xiaoyong Yuan, Pan He +5

Existing malware detectors on safety-critical devices have difficulties in runtime detection due to the performance overhead. In this paper, we introduce PROPEDEUTICA, a framework…

cs.SE2017★ 1 cited

Intelligent Perioperative System: Towards Real-time Big Data Analytics in Surgery Risk Assessment

Zheng Feng, Rajendra Rana Bhat, Xiaoyong Yuan +4

Surgery risk assessment is an effective tool for physicians to manage the treatment of patients, but most current research projects fall short in providing a comprehensive platform…