Liu, Sijia

117 publications

WACV 2025 Can Adversarial Examples Be Parsed to Reveal Victim Model Information? Yuguang Yao, Jiancheng Liu, Yifan Gong, Xiaoming Liu, Yanzhi Wang, Xue Lin, Sijia Liu

CVPR 2025 Edit Away and My Face Will Not Stay: Personal Biometric Defense Against Malicious Generative Editing Hanhui Wang, Yihua Zhang, Ruizheng Bai, Yue Zhao, Sijia Liu, Zhengzhong Tu

CVPR 2025 ID-Patch: Robust ID Association for Group Photo Personalization Yimeng Zhang, Tiancheng Zhi, Jing Liu, Shen Sang, Liming Jiang, Qing Yan, Sijia Liu, Linjie Luo

ICML 2025 Invariance Makes LLM Unlearning Resilient Even to Unanticipated Downstream Fine-Tuning Changsheng Wang, Yihua Zhang, Jinghan Jia, Parikshit Ram, Dennis Wei, Yuguang Yao, Soumyadeep Pal, Nathalie Baracaldo, Sijia Liu

ICCV 2025 Invisible Watermarks, Visible Gains: Steering Machine Unlearning with Bi-Level Watermarking Design Yuhao Sun, Yihua Zhang, Gaowen Liu, Hongtao Xie, Sijia Liu

NeurIPS 2025 One Token Embedding Is Enough to Deadlock Your Large Reasoning Model Mohan Zhang, Yihua Zhang, Jinghan Jia, Zhangyang Wang, Sijia Liu, Tianlong Chen

CVPR 2025 PSBD: Prediction Shift Uncertainty Unlocks Backdoor Detection Wei Li, Pin-Yu Chen, Sijia Liu, Ren Wang

NeurIPS 2025 Simplicity Prevails: Rethinking Negative Preference Optimization for LLM Unlearning Chongyu Fan, Jiancheng Liu, Licong Lin, Jinghan Jia, Ruiqi Zhang, Song Mei, Sijia Liu

NeurIPS 2025 The Fragile Truth of Saliency: Improving LLM Input Attribution via Attention Bias Optimization Yihua Zhang, Changsheng Wang, Yiwei Chen, Chongyu Fan, Jinghan Jia, Sijia Liu

ICML 2025 Towards LLM Unlearning Resilient to Relearning Attacks: A Sharpness-Aware Minimization Perspective and Beyond Chongyu Fan, Jinghan Jia, Yihua Zhang, Anil Ramakrishna, Mingyi Hong, Sijia Liu

AAAI 2025 Visual Prompting Upgrades Neural Network Sparsification: A Data-Model Perspective Can Jin, Tianjin Huang, Yihua Zhang, Mykola Pechenizkiy, Sijia Liu, Shiwei Liu, Tianlong Chen

ICLR 2025 When Is Task Vector Provably Effective for Model Editing? a Generalization Analysis of Nonlinear Transformers Hongkang Li, Yihua Zhang, Shuai Zhang, Pin-Yu Chen, Sijia Liu, Meng Wang

NeurIPSW 2024 Adversarial Watermarking for Face Recognition Yuguang Yao, Anil K. Jain, Sijia Liu

ICLR 2024 AutoVP: An Automated Visual Prompting Framework and Benchmark Hsi-Ai Tsao, Lei Hsiung, Pin-Yu Chen, Sijia Liu, Tsung-Yi Ho

ICLR 2024 Backdoor Secrets Unveiled: Identifying Backdoor Data with Optimized Scaled Prediction Consistency Soumyadeep Pal, Yuguang Yao, Ren Wang, Bingquan Shen, Sijia Liu

ECCV 2024 Challenging Forgets: Unveiling the Worst-Case Forget Sets in Machine Unlearning Chongyu Fan, Jiancheng Liu, Alfred Hero, Sijia Liu

WACV 2024 CryoRL: Reinforcement Learning Enables Efficient Cryo-EM Data Collection Quanfu Fan, Yilai Li, Yuguang Yao, John Cohn, Sijia Liu, Ziping Xu, Seychelle Vos, Michael Cianfrocco

ICLR 2024 DeepZero: Scaling up Zeroth-Order Optimization for Deep Model Training Aochuan Chen, Yimeng Zhang, Jinghan Jia, James Diffenderfer, Konstantinos Parasyris, Jiancheng Liu, Yihua Zhang, Zheng Zhang, Bhavya Kailkhura, Sijia Liu

NeurIPS 2024 Defensive Unlearning with Adversarial Training for Robust Concept Erasure in Diffusion Models Yimeng Zhang, Xin Chen, Jinghan Jia, Yihua Zhang, Chongyu Fan, Jiancheng Liu, Mingyi Hong, Ke Ding, Sijia Liu

NeurIPS 2024 From Trojan Horses to Castle Walls: Unveiling Bilateral Data Poisoning Effects in Diffusion Models Zhuoshi Pan, Yuguang Yao, Gaowen Liu, Bingquan Shen, H. Vicky Zhao, Ramana Rao Kompella, Sijia Liu

NeurIPSW 2024 LLM Self-Correction with DeCRIM: Decompose, Critique, and Refine for Enhanced Following of Instructions with Multiple Constraints Thomas Palmeira Ferraz, Kartik Mehta, Yu-Hsiang Lin, Haw-Shiuan Chang, Shereen Oraby, Sijia Liu, Vivek Subramanian, Tagyoung Chung, Mohit Bansal, Nanyun Peng

NeurIPS 2024 Reversing the Forget-Retain Objectives: An Efficient LLM Unlearning Framework from Logit Difference Jiabao Ji, Yujian Liu, Yang Zhang, Gaowen Liu, Ramana Rao Kompella, Sijia Liu, Shiyu Chang

ICML 2024 Revisiting Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning: A Benchmark Yihua Zhang, Pingzhi Li, Junyuan Hong, Jiaxiang Li, Yimeng Zhang, Wenqing Zheng, Pin-Yu Chen, Jason D. Lee, Wotao Yin, Mingyi Hong, Zhangyang Wang, Sijia Liu, Tianlong Chen

ICLR 2024 SalUn: Empowering Machine Unlearning via Gradient-Based Weight Saliency in Both Image Classification and Generation Chongyu Fan, Jiancheng Liu, Yihua Zhang, Eric Wong, Dennis Wei, Sijia Liu

NeurIPSW 2024 Simplicity Prevails: Rethinking Negative Preference Optimization for LLM Unlearning Chongyu Fan, Jiancheng Liu, Licong Lin, Jinghan Jia, Ruiqi Zhang, Song Mei, Sijia Liu

ECCV 2024 To Generate or Not? Safety-Driven Unlearned Diffusion Models Are Still Easy to Generate Unsafe Images ... for Now Yimeng Zhang, Jinghan Jia, Xin Chen, Aochuan Chen, Yihua Zhang, Jiancheng Liu, Ke Ding, Sijia Liu

NeurIPS 2024 Tracing Hyperparameter Dependencies for Model Parsing via Learnable Graph Pooling Network Xiao Guo, Vishal Asnani, Sijia Liu, Xiaoming Liu

NeurIPS 2024 UnlearnCanvas: Stylized Image Dataset for Enhanced Machine Unlearning Evaluation in Diffusion Models Yihua Zhang, Chongyu Fan, Yimeng Zhang, Yuguang Yao, Jinghan Jia, Jiancheng Liu, Gaoyuan Zhang, Gaowen Liu, Ramana Kompella, Xiaoming Liu, Sijia Liu

NeurIPS 2024 WAGLE: Strategic Weight Attribution for Effective and Modular Unlearning in Large Language Models Jinghan Jia, Jiancheng Liu, Yihua Zhang, Parikshit Ram, Nathalie Baracaldo, Sijia Liu

ICML 2024 What Improves the Generalization of Graph Transformers? a Theoretical Dive into the Self-Attention and Positional Encoding Hongkang Li, Meng Wang, Tengfei Ma, Sijia Liu, Zaixi Zhang, Pin-Yu Chen

CVPRW 2023 A Pilot Study of Query-Free Adversarial Attack Against Stable Diffusion Haomin Zhuang, Yihua Zhang, Sijia Liu

ICLR 2023 A Theoretical Understanding of Shallow Vision Transformers: Learning, Generalization, and Sample Complexity Hongkang Li, Meng Wang, Sijia Liu, Pin-Yu Chen

AAAI 2023 AAAI New Faculty Highlights: General and Scalable Optimization for Robust AI Sijia Liu

NeurIPSW 2023 AutoVP: An Automated Visual Prompting Framework and Benchmark Hsi-Ai Tsao, Lei Hsiung, Pin-Yu Chen, Sijia Liu, Tsung-Yi Ho

NeurIPSW 2023 AutoVP: An Automated Visual Prompting Framework and Benchmark Hsi-Ai Tsao, Lei Hsiung, Pin-Yu Chen, Sijia Liu, Tsung-Yi Ho

CVPRW 2023 Exploring Diversified Adversarial Robustness in Neural Networks via Robust Mode Connectivity Ren Wang, Yuxuan Li, Sijia Liu

NeurIPSW 2023 From Trojan Horses to Castle Walls: Unveiling Bilateral Backdoor Effects in Diffusion Models Zhuoshi Pan, Yuguang Yao, Gaowen Liu, Bingquan Shen, H. Vicky Zhao, Ramana Rao Kompella, Sijia Liu

AAAI 2023 Holistic Adversarial Robustness of Deep Learning Models Pin-Yu Chen, Sijia Liu

ICLR 2023 Joint Edge-Model Sparse Learning Is Provably Efficient for Graph Neural Networks Shuai Zhang, Meng Wang, Pin-Yu Chen, Sijia Liu, Songtao Lu, Miao Liu

ICML 2023 Linearly Constrained Bilevel Optimization: A Smoothed Implicit Gradient Approach Prashant Khanduri, Ioannis Tsaknakis, Yihua Zhang, Jia Liu, Sijia Liu, Jiawei Zhang, Mingyi Hong

NeurIPS 2023 Model Sparsity Can Simplify Machine Unlearning Jinghan Jia, Jiancheng Liu, Parikshit Ram, Yuguang Yao, Gaowen Liu, Yang Liu, Pranay Sharma, Sijia Liu

NeurIPS 2023 On the Convergence and Sample Complexity Analysis of Deep Q-Networks with $\epsilon$-Greedy Exploration Shuai Zhang, Hongkang Li, Meng Wang, Miao Liu, Pin-Yu Chen, Songtao Lu, Sijia Liu, Keerthiram Murugesan, Subhajit Chaudhury

ICML 2023 Patch-Level Routing in Mixture-of-Experts Is Provably Sample-Efficient for Convolutional Neural Networks Mohammed Nowaz Rabbani Chowdhury, Shuai Zhang, Meng Wang, Sijia Liu, Pin-Yu Chen

ICCV 2023 Robust Mixture-of-Expert Training for Convolutional Neural Networks Yihua Zhang, Ruisi Cai, Tianlong Chen, Guanhua Zhang, Huan Zhang, Pin-Yu Chen, Shiyu Chang, Zhangyang Wang, Sijia Liu

NeurIPS 2023 Selectivity Drives Productivity: Efficient Dataset Pruning for Enhanced Transfer Learning Yihua Zhang, Yimeng Zhang, Aochuan Chen, Jinghan Jia, Jiancheng Liu, Gaowen Liu, Mingyi Hong, Shiyu Chang, Sijia Liu

CVPR 2023 Text-Visual Prompting for Efficient 2D Temporal Video Grounding Yimeng Zhang, Xin Chen, Jinghan Jia, Sijia Liu, Ke Ding

ICLR 2023 TextGrad: Advancing Robustness Evaluation in NLP by Gradient-Driven Optimization Bairu Hou, Jinghan Jia, Yihua Zhang, Guanhua Zhang, Yang Zhang, Sijia Liu, Shiyu Chang

AAAI 2023 Towards Credible Human Evaluation of Open-Domain Dialog Systems Using Interactive Setup Sijia Liu, Patrick Lange, Behnam Hedayatnia, Alexandros Papangelis, Di Jin, Andrew Wirth, Yang Liu, Dilek Hakkani-Tur

CVPR 2023 Understanding and Improving Visual Prompting: A Label-Mapping Perspective Aochuan Chen, Yuguang Yao, Pin-Yu Chen, Yihua Zhang, Sijia Liu

NeurIPSW 2023 What Improves the Generalization of Graph Transformer? a Theoretical Dive into Self-Attention and Positional Encoding Hongkang Li, Meng Wang, Tengfei Ma, Sijia Liu, Zaixi Zhang, Pin-Yu Chen

ICLR 2023 What Is Missing in IRM Training and Evaluation? Challenges and Solutions Yihua Zhang, Pranay Sharma, Parikshit Ram, Mingyi Hong, Kush R. Varshney, Sijia Liu

NeurIPS 2022 Advancing Model Pruning via Bi-Level Optimization Yihua Zhang, Yuguang Yao, Parikshit Ram, Pu Zhao, Tianlong Chen, Mingyi Hong, Yanzhi Wang, Sijia Liu

AAAI 2022 Adversarial Examples Can Be Effective Data Augmentation for Unsupervised Machine Learning Chia-Yi Hsu, Pin-Yu Chen, Songtao Lu, Sijia Liu, Chia-Mu Yu

TMLR 2022 Can You Win Everything with a Lottery Ticket? Tianlong Chen, Zhenyu Zhang, Jun Wu, Randy Huang, Sijia Liu, Shiyu Chang, Zhangyang Wang

ICML 2022 Data-Efficient Double-Win Lottery Tickets from Robust Pre-Training Tianlong Chen, Zhenyu Zhang, Sijia Liu, Yang Zhang, Shiyu Chang, Zhangyang Wang

ICLR 2022 Decentralized Learning for Overparameterized Problems: A Multi-Agent Kernel Approximation Approach Prashant Khanduri, Haibo Yang, Mingyi Hong, Jia Liu, Hoi To Wai, Sijia Liu

UAI 2022 Distributed Adversarial Training to Robustify Deep Neural Networks at Scale Gaoyuan Zhang, Songtao Lu, Yihua Zhang, Xiangyi Chen, Pin-Yu Chen, Quanfu Fan, Lee Martie, Lior Horesh, Mingyi Hong, Sijia Liu

NeurIPS 2022 Fairness Reprogramming Guanhua Zhang, Yihua Zhang, Yang Zhang, Wenqi Fan, Qing Li, Sijia Liu, Shiyu Chang

ICML 2022 Generalization Guarantee of Training Graph Convolutional Networks with Graph Topology Sampling Hongkang Li, Meng Wang, Sijia Liu, Pin-Yu Chen, Jinjun Xiong

ICLR 2022 How Unlabeled Data Improve Generalization in Self-Training? a One-Hidden-Layer Theoretical Analysis Shuai Zhang, Meng Wang, Sijia Liu, Pin-Yu Chen, Jinjun Xiong

ICLR 2022 How to Robustify Black-Box ML Models? a Zeroth-Order Optimization Perspective Yimeng Zhang, Yuguang Yao, Jinghan Jia, Jinfeng Yi, Mingyi Hong, Shiyu Chang, Sijia Liu

IJCAI 2022 Learning to Generate Image Source-Agnostic Universal Adversarial Perturbations Pu Zhao, Parikshit Ram, Songtao Lu, Yuguang Yao, Djallel Bouneffouf, Xue Lin, Sijia Liu

ICML 2022 Linearity Grafting: Relaxed Neuron Pruning Helps Certifiable Robustness Tianlong Chen, Huan Zhang, Zhenyu Zhang, Shiyu Chang, Sijia Liu, Pin-Yu Chen, Zhangyang Wang

NeurIPSW 2022 On the Robustness of Deep Learning-Based MRI Reconstruction to Image Transformations Jinghan Jia, Mingyi Hong, Yimeng Zhang, Mehmet Akcakaya, Sijia Liu

ICLR 2022 Optimizer Amalgamation Tianshu Huang, Tianlong Chen, Sijia Liu, Shiyu Chang, Lisa Amini, Zhangyang Wang

CVPR 2022 Proactive Image Manipulation Detection Vishal Asnani, Xi Yin, Tal Hassner, Sijia Liu, Xiaoming Liu

CVPR 2022 Quarantine: Sparsity Can Uncover the Trojan Attack Trigger for Free Tianlong Chen, Zhenyu Zhang, Yihua Zhang, Shiyu Chang, Sijia Liu, Zhangyang Wang

TMLR 2022 Queried Unlabeled Data Improves and Robustifies Class-Incremental Learning Tianlong Chen, Sijia Liu, Shiyu Chang, Lisa Amini, Zhangyang Wang

ICLR 2022 Reverse Engineering of Imperceptible Adversarial Image Perturbations Yifan Gong, Yuguang Yao, Yize Li, Yimeng Zhang, Xiaoming Liu, Xue Lin, Sijia Liu

ICML 2022 Revisiting Contrastive Learning Through the Lens of Neighborhood Component Analysis: An Integrated Framework Ching-Yun Ko, Jeet Mohapatra, Sijia Liu, Pin-Yu Chen, Luca Daniel, Lily Weng

ICML 2022 Revisiting and Advancing Fast Adversarial Training Through the Lens of Bi-Level Optimization Yihua Zhang, Guanhua Zhang, Prashant Khanduri, Mingyi Hong, Shiyu Chang, Sijia Liu

NeurIPSW 2022 Visual Prompting for Adversarial Robustness Aochuan Chen, Peter Lorenz, Yuguang Yao, Pin-Yu Chen, Sijia Liu

NeurIPSW 2022 Visual Prompting for Adversarial Robustness Aochuan Chen, Peter Lorenz, Yuguang Yao, Pin-Yu Chen, Sijia Liu

AAAI 2022 Zeroth-Order Optimization for Composite Problems with Functional Constraints Zichong Li, Pin-Yu Chen, Sijia Liu, Songtao Lu, Yangyang Xu

AISTATS 2021 Hidden Cost of Randomized Smoothing Jeet Mohapatra, Ching-Yun Ko, Lily Weng, Pin-Yu Chen, Sijia Liu, Luca Daniel

AISTATS 2021 Rate-Improved Inexact Augmented Lagrangian Method for Constrained Nonconvex Optimization Zichong Li, Pin-Yu Chen, Sijia Liu, Songtao Lu, Yangyang Xu

IJCAI 2021 A Compression-Compilation Framework for On-Mobile Real-Time BERT Applications Wei Niu, Zhenglun Kong, Geng Yuan, Weiwen Jiang, Jiexiong Guan, Caiwen Ding, Pu Zhao, Sijia Liu, Bin Ren, Yanzhi Wang

NeurIPS 2021 Adversarial Attack Generation Empowered by Min-Max Optimization Jingkang Wang, Tianyun Zhang, Sijia Liu, Pin-Yu Chen, Jiacen Xu, Makan Fardad, Bo Li

AAAI 2021 Fast Training of Provably Robust Neural Networks by SingleProp Akhilan Boopathy, Lily Weng, Sijia Liu, Pin-Yu Chen, Gaoyuan Zhang, Luca Daniel

ICLR 2021 Generating Adversarial Computer Programs Using Optimized Obfuscations Shashank Srikant, Sijia Liu, Tamara Mitrovska, Shiyu Chang, Quanfu Fan, Gaoyuan Zhang, Una-May O'Reilly

ICLR 2021 Long Live the Lottery: The Existence of Winning Tickets in Lifelong Learning Tianlong Chen, Zhenyu Zhang, Sijia Liu, Shiyu Chang, Zhangyang Wang

ICML 2021 Lottery Ticket Preserves Weight Correlation: Is It Desirable or Not? Ning Liu, Geng Yuan, Zhengping Che, Xuan Shen, Xiaolong Ma, Qing Jin, Jian Ren, Jian Tang, Sijia Liu, Yanzhi Wang

NeurIPS 2021 MEST: Accurate and Fast Memory-Economic Sparse Training Framework on the Edge Geng Yuan, Xiaolong Ma, Wei Niu, Zhengang Li, Zhenglun Kong, Ning Liu, Yifan Gong, Zheng Zhan, Chaoyang He, Qing Jin, Siyue Wang, Minghai Qin, Bin Ren, Yanzhi Wang, Sijia Liu, Xue Lin

CVPR 2021 NPAS: A Compiler-Aware Framework of Unified Network Pruning and Architecture Search for Beyond Real-Time Mobile Acceleration Zhengang Li, Geng Yuan, Wei Niu, Pu Zhao, Yanyu Li, Yuxuan Cai, Xuan Shen, Zheng Zhan, Zhenglun Kong, Qing Jin, Zhiyu Chen, Sijia Liu, Kaiyuan Yang, Bin Ren, Yanzhi Wang, Xue Lin

ICLR 2021 On Fast Adversarial Robustness Adaptation in Model-Agnostic Meta-Learning Ren Wang, Kaidi Xu, Sijia Liu, Pin-Yu Chen, Tsui-Wei Weng, Chuang Gan, Meng Wang

ICCV 2021 RMSMP: A Novel Deep Neural Network Quantization Framework with Row-Wise Mixed Schemes and Multiple Precisions Sung-En Chang, Yanyu Li, Mengshu Sun, Weiwen Jiang, Sijia Liu, Yanzhi Wang, Xue Lin

AAAI 2021 RT3D: Achieving Real-Time Execution of 3D Convolutional Neural Networks on Mobile Devices Wei Niu, Mengshu Sun, Zhengang Li, Jou-An Chen, Jiexiong Guan, Xipeng Shen, Yanzhi Wang, Sijia Liu, Xue Lin, Bin Ren

ICLR 2021 Robust Overfitting May Be Mitigated by Properly Learned Smoothening Tianlong Chen, Zhenyu Zhang, Sijia Liu, Shiyu Chang, Zhangyang Wang

NeurIPS 2021 Sanity Checks for Lottery Tickets: Does Your Winning Ticket Really Win the Jackpot? Xiaolong Ma, Geng Yuan, Xuan Shen, Tianlong Chen, Xuxi Chen, Xiaohan Chen, Ning Liu, Minghai Qin, Sijia Liu, Zhangyang Wang, Yanzhi Wang

AAAI 2021 Self-Progressing Robust Training Minhao Cheng, Pin-Yu Chen, Sijia Liu, Shiyu Chang, Cho-Jui Hsieh, Payel Das

NeurIPSW 2021 Sign-MAML: Efficient Model-Agnostic Meta-Learning by SignSGD Chen Fan, Parikshit Ram, Sijia Liu

CVPR 2021 The Lottery Tickets Hypothesis for Supervised and Self-Supervised Pre-Training in Computer Vision Models Tianlong Chen, Jonathan Frankle, Shiyu Chang, Sijia Liu, Yang Zhang, Michael Carbin, Zhangyang Wang

NeurIPS 2021 When Does Contrastive Learning Preserve Adversarial Robustness from Pretraining to Finetuning? Lijie Fan, Sijia Liu, Pin-Yu Chen, Gaoyuan Zhang, Chuang Gan

NeurIPS 2021 Why Lottery Ticket Wins? a Theoretical Perspective of Sample Complexity on Sparse Neural Networks Shuai Zhang, Meng Wang, Sijia Liu, Pin-Yu Chen, Jinjun Xiong

ECCV 2020 Adversarial T-Shirt! Evading Person Detectors in a Physical World Kaidi Xu, Gaoyuan Zhang, Sijia Liu, Quanfu Fan, Mengshu Sun, Hongge Chen, Pin-Yu Chen, Yanzhi Wang, Xue Lin

AAAI 2020 An ADMM Based Framework for AutoML Pipeline Configuration Sijia Liu, Parikshit Ram, Deepak Vijaykeerthy, Djallel Bouneffouf, Gregory Bramble, Horst Samulowitz, Dakuo Wang, Andrew Conn, Alexander G. Gray

ECCV 2020 An Image Enhancing Pattern-Based Sparsity for Real-Time Inference on Mobile Devices Xiaolong Ma, Wei Niu, Tianyun Zhang, Sijia Liu, Sheng Lin, Hongjia Li, Wujie Wen, Xiang Chen, Jian Tang, Kaisheng Ma, Bin Ren, Yanzhi Wang

ICML 2020 Fast Learning of Graph Neural Networks with Guaranteed Generalizability: One-Hidden-Layer Case Shuai Zhang, Meng Wang, Sijia Liu, Pin-Yu Chen, Jinjun Xiong

NeurIPS 2020 Higher-Order Certification for Randomized Smoothing Jeet Mohapatra, Ching-Yun Ko, Tsui-Wei Weng, Pin-Yu Chen, Sijia Liu, Luca Daniel

ICML 2020 Is There a Trade-Off Between Fairness and Accuracy? a Perspective Using Mismatched Hypothesis Testing Sanghamitra Dutta, Dennis Wei, Hazar Yueksel, Pin-Yu Chen, Sijia Liu, Kush Varshney

ICML 2020 Min-Max Optimization Without Gradients: Convergence and Applications to Black-Box Evasion and Poisoning Attacks Sijia Liu, Songtao Lu, Xiangyi Chen, Yao Feng, Kaidi Xu, Abdullah Al-Dujaili, Mingyi Hong, Una-May O’Reilly

ECCV 2020 Practical Detection of Trojan Neural Networks: Data-Limited and Data-Free Cases Ren Wang, Gaoyuan Zhang, Sijia Liu, Pin-Yu Chen, Jinjun Xiong, Meng Wang

ICML 2020 Proper Network Interpretability Helps Adversarial Robustness in Classification Akhilan Boopathy, Sijia Liu, Gaoyuan Zhang, Cynthia Liu, Pin-Yu Chen, Shiyu Chang, Luca Daniel

ICLR 2020 Sign-OPT: A Query-Efficient Hard-Label Adversarial Attack Minhao Cheng, Simranjit Singh, Patrick Chen, Pin-Yu Chen, Sijia Liu, Cho-Jui Hsieh

NeurIPS 2020 The Lottery Ticket Hypothesis for Pre-Trained BERT Networks Tianlong Chen, Jonathan Frankle, Shiyu Chang, Sijia Liu, Yang Zhang, Zhangyang Wang, Michael Carbin

AAAI 2020 Towards Certificated Model Robustness Against Weight Perturbations Tsui-Wei Weng, Pu Zhao, Sijia Liu, Pin-Yu Chen, Xue Lin, Luca Daniel

NeurIPS 2020 Training Stronger Baselines for Learning to Optimize Tianlong Chen, Weiyi Zhang, Zhou Jingyang, Shiyu Chang, Sijia Liu, Lisa Amini, Zhangyang Wang

AAAI 2019 AutoZOOM: Autoencoder-Based Zeroth Order Optimization Method for Attacking Black-Box Neural Networks Chun-Chen Tu, Pai-Shun Ting, Pin-Yu Chen, Sijia Liu, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh, Shin-Ming Cheng

AAAI 2019 CNN-Cert: An Efficient Framework for Certifying Robustness of Convolutional Neural Networks Akhilan Boopathy, Tsui-Wei Weng, Pin-Yu Chen, Sijia Liu, Luca Daniel

ICML 2019 Fast Incremental Von Neumann Graph Entropy Computation: Theory, Algorithm, and Applications Pin-Yu Chen, Lingfei Wu, Sijia Liu, Indika Rajapakse

ICLR 2019 On the Convergence of a Class of Adam-Type Algorithms for Non-Convex Optimization Xiangyi Chen, Sijia Liu, Ruoyu Sun, Mingyi Hong

ICLR 2019 Structured Adversarial Attack: Towards General Implementation and Better Interpretability Kaidi Xu, Sijia Liu, Pu Zhao, Pin-Yu Chen, Huan Zhang, Quanfu Fan, Deniz Erdogmus, Yanzhi Wang, Xue Lin

IJCAI 2019 Topology Attack and Defense for Graph Neural Networks: An Optimization Perspective Kaidi Xu, Hongge Chen, Sijia Liu, Pin-Yu Chen, Tsui-Wei Weng, Mingyi Hong, Xue Lin

NeurIPS 2019 ZO-AdaMM: Zeroth-Order Adaptive Momentum Method for Black-Box Optimization Xiangyi Chen, Sijia Liu, Kaidi Xu, Xingguo Li, Xue Lin, Mingyi Hong, David Cox

ICLR 2019 signSGD via Zeroth-Order Oracle Sijia Liu, Pin-Yu Chen, Xiangyi Chen, Mingyi Hong

AISTATS 2018 Zeroth-Order Online Alternating Direction Method of Multipliers: Convergence Analysis and Applications Sijia Liu, Jie Chen, Pin-Yu Chen, Alfred O. Hero Iii

NeurIPS 2018 Zeroth-Order Stochastic Variance Reduction for Nonconvex Optimization Sijia Liu, Bhavya Kailkhura, Pin-Yu Chen, Paishun Ting, Shiyu Chang, Lisa Amini