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D-Index & Metrics

Computer Science

D-Index
40
Citations
9797
World Ranking
9121
National Ranking
3878

Overview

Huan Zhang is affiliated with the University of California, Los Angeles in the United States and contributes extensively to the field of computer science. Their research primarily spans areas such as artificial intelligence and electrical and electronic engineering, with significant work in atomic and molecular physics and optics, industrial and manufacturing engineering, and computer vision and pattern recognition.

Their work focuses on various specialized topics including adversarial robustness in machine learning, anomaly detection techniques and applications, quantum information and cryptography, Bayesian modeling and causal inference, imbalanced data classification techniques, quantum mechanics and applications, and quantum computing algorithms and architecture.

Huan Zhang has authored several research papers with notable examples including:

  • Chinese clinical named entity recognition with variant neural structures based on BERT methods, 2020, Journal of Biomedical Informatics
  • CS-ResNet: Cost-sensitive residual convolutional neural network for PCB cosmetic defect detection, 2021, Expert Systems with Applications
  • Seq2Sick: Evaluating the Robustness of Sequence-to-Sequence Models with Adversarial Examples, 2020, Proceedings of the AAAI Conference on Artificial Intelligence
  • Robust Deep Reinforcement Learning against Adversarial Perturbations on State Observations, 2020, arXiv (Cornell University)
  • Attribute and instance weighted naive Bayes, 2020, Pattern Recognition

Their frequent co-authors include:

  • Cho-Jui Hsieh
  • Liangxiao Jiang
  • Wei Ye
  • Liyun Hu
  • Ying Xia

Publications by Huan Zhang have appeared in various venues, most prominently:

  • arXiv (Cornell University)
  • Pattern Recognition
  • SSRN Electronic Journal
  • Swarm and Evolutionary Computation
  • Results in Physics

Huan Zhang's body of work is categorized under a broad main field of computer science featuring 143 publications, with 106 in artificial intelligence as a key subfield. Their research outputs have contributed knowledge across multiple interrelated disciplines.

Best Publications

  • ZOO: Zeroth Order Optimization Based Black-box Attacks to Deep Neural Networks without Training Substitute Models

    Pin-Yu Chen;Huan Zhang;Yash Sharma;Jinfeng Yi

  • Can Decentralized Algorithms Outperform Centralized Algorithms? A Case Study for Decentralized Parallel Stochastic Gradient Descent

    Xiangru Lian;Ce Zhang;Huan Zhang;Cho-Jui Hsieh

  • EAD: Elastic-Net Attacks to Deep Neural Networks via Adversarial Examples

    Pin-Yu Chen;Yash Sharma;Huan Zhang;Jinfeng Yi

  • Towards Fast Computation of Certified Robustness for ReLU Networks

    Tsui-Wei Weng;Huan Zhang;Hongge Chen;Zhao Song

  • Efficient Neural Network Robustness Certification with General Activation Functions

    Huan Zhang;Tsui-Wei Weng;Pin-Yu Chen;Cho-Jui Hsieh

  • Towards Robust Neural Networks via Random Self-ensemble

    Xuanqing Liu;Minhao Cheng;Huan Zhang;Cho-Jui Hsieh

  • AutoZOOM: Autoencoder-Based Zeroth Order Optimization Method for Attacking Black-Box Neural Networks

    Chun-Chen Tu;Paishun Ting;Pin-Yu Chen;Sijia Liu

  • Is Robustness the Cost of Accuracy? – A Comprehensive Study on the Robustness of 18 Deep Image Classification Models

    Dong Su;Huan Zhang;Hongge Chen;Jinfeng Yi

  • Spectral and spatial 2D fragmentation-aware routing and spectrum assignment algorithms in elastic optical networks [invited]

    Yawei Yin;Huan Zhang;Mingyang Zhang;Ming Xia

  • Evaluating the Robustness of Neural Networks: An Extreme Value Theory Approach

    Tsui-Wei Weng;Huan Zhang;Pin-Yu Chen;Jinfeng Yi

  • Query-Efficient Hard-label Black-box Attack: An Optimization-based Approach

    Minhao Cheng;Thong Le;Pin-Yu Chen;Jinfeng Yi

  • Seq2Sick: Evaluating the Robustness of Sequence-to-Sequence Models with Adversarial Examples

    Minhao Cheng;Jinfeng Yi;Pin-Yu Chen;Huan Zhang

  • GenAttack: practical black-box attacks with gradient-free optimization

    Moustafa Alzantot;Yash Sharma;Supriyo Chakraborty;Huan Zhang

  • Provably Robust Deep Learning via Adversarially Trained Smoothed Classifiers

    Hadi Salman;Jerry Li;Ilya P. Razenshteyn;Pengchuan Zhang

  • Towards Stable and Efficient Training of Verifiably Robust Neural Networks

    Huan Zhang;Hongge Chen;Chaowei Xiao;Sven Gowal

  • Robust Deep Reinforcement Learning against Adversarial Perturbations on State Observations

    Huan Zhang;Hongge Chen;Chaowei Xiao;Bo Li

  • A Convex Relaxation Barrier to Tight Robustness Verification of Neural Networks

    Hadi Salman;Greg Yang;Huan Zhang;Cho-Jui Hsieh

  • Provably Robust Deep Learning via Adversarially Trained Smoothed Classifiers

    Hadi Salman;Greg Yang;Jerry Li;Pengchuan Zhang

  • Reducing Sentiment Bias in Language Models via Counterfactual Evaluation

    Po-Sen Huang;Huan Zhang;Ray Jiang;Robert Stanforth

  • Attacking Visual Language Grounding with Adversarial Examples: A Case Study on Neural Image Captioning

    Hongge Chen;Huan Zhang;Pin-Yu Chen;Jinfeng Yi

  • Structured Adversarial Attack: Towards General Implementation and Better Interpretability

    Kaidi Xu;Sijia Liu;Pu Zhao;Pin-Yu Chen

  • Automatic Perturbation Analysis for Scalable Certified Robustness and Beyond

    Kaidi Xu;Zhouxing Shi;Huan Zhang;Yihan Wang

  • Adversarial Robustness vs Model Compression, or Both?

    Shaokai Ye;Kaidi Xu;Sijia Liu;Jan-Henrik Lambrechts

Frequent Co-Authors

Cho-Jui Hsieh
Cho-Jui Hsieh University of California, Los Angeles
Jinfeng Yi
Jinfeng Yi IBM (United States)
Pin-Yu Chen
Pin-Yu Chen IBM (United States)
Kai-Wei Chang
Kai-Wei Chang University of California, Los Angeles
Sijia Liu
Sijia Liu Michigan State University
Minlie Huang
Minlie Huang Tsinghua University
Yanzhi Wang
Yanzhi Wang Northeastern University
Zhao Song
Zhao Song Adobe Systems (United States)

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