Sijia Liu - RankMe

371 papers A* 94A 10B 2C 1Misc 23Journal 208Unranked 33

Year	Rank	Type	Title / Venue / Authors
2026	—	`conf`	BLUR: A Bi-Level Optimization Approach for LLM Unlearning. EACL (Volume 1: Long Papers) Hadi Reisizadeh, Jinghan Jia, Zhiqi Bu, Bhanukiran Vinzamuri, Anil Ramakrishna, Kai-Wei Chang, Volkan Cevher, Sijia Liu, Mingyi Hong
2026	J	`jnl`	Powering Up Zeroth-Order Training via Subspace Gradient Orthogonalization. CoRR Yicheng Lang, Changsheng Wang, Yihua Zhang, Mingyi Hong, Zheng Zhang, Wotao Yin, Sijia Liu
2026	A*	`conf`	Robust Learning from Noisily Labeled Long-Tailed Data via Fairness Regularizer. AAAI Jiaheng Wei, Zhaowei Zhu, Gang Niu, Tongliang Liu, Sijia Liu, Masashi Sugiyama, Yang Liu
2026	J	`jnl`	TEON: Tensorized Orthonormalization Beyond Layer-Wise Muon for Large Language Model Pre-Training. CoRR Ruijie Zhang, Yequan Zhao, Ziyue Liu, Zhengyang Wang, Dongyang Li, Yupeng Su, Sijia Liu, Zheng Zhang
2025	J	`jnl`	BLUR: A Bi-Level Optimization Approach for LLM Unlearning. CoRR Hadi Reisizadeh, Jinghan Jia, Zhiqi Bu, Bhanukiran Vinzamuri, Anil Ramakrishna, Kai-Wei Chang, Volkan Cevher, Sijia Liu, Mingyi Hong
2025	J	`jnl`	Beyond SFT: Reinforcement Learning for Safer Large Reasoning Models with Better Reasoning Ability. CoRR Jinghan Jia, Nathalie Baracaldo, Sijia Liu
2025	A	`conf`	Can Adversarial Examples be Parsed to Reveal Victim Model Information? WACV Yuguang Yao, Jiancheng Liu, Yifan Gong, Xiaoming Liu, Yanzhi Wang, Xue Lin, Sijia Liu
2025	J	`jnl`	CyclicReflex: Improving Large Reasoning Models via Cyclical Reflection Token Scheduling. CoRR Chongyu Fan, Yihua Zhang, Jinghan Jia, Alfred Olivier Hero, Sijia Liu
2025	J	`jnl`	Downgrade to Upgrade: Optimizer Simplification Enhances Robustness in LLM Unlearning. CoRR Yicheng Lang, Yihua Zhang, Chongyu Fan, Changsheng Wang, Jinghan Jia, Sijia Liu
2025	J	`jnl`	EPiC: Towards Lossless Speedup for Reasoning Training through Edge-Preserving CoT Condensation. CoRR Jinghan Jia, Hadi Reisizadeh, Chongyu Fan, Nathalie Baracaldo, Mingyi Hong, Sijia Liu
2025	A*	`conf`	Edit Away and My Face Will not Stay: Personal Biometric Defense against Malicious Generative Editing. CVPR Hanhui Wang, Yihua Zhang, Ruizheng Bai, Yue Zhao, Sijia Liu, Zhengzhong Tu
2025	A	`conf`	FROG: Fair Removal on Graph. CIKM Ziheng Chen, Jiali Cheng, Hadi Amiri, Kaushiki Nag, Lu Lin, Sijia Liu, Gabriele Tolomei, Xiangguo Sun
2025	J	`jnl`	FROG: Fair Removal on Graphs. CoRR Ziheng Chen, Jiali Cheng, Gabriele Tolomei, Sijia Liu, Hadi Amiri, Yu Wang, Kaushiki Nag, Lu Lin
2025	A*	`conf`	ID-Patch: Robust ID Association for Group Photo Personalization. CVPR Yimeng Zhang, Tiancheng Zhi, Jing Liu, Shen Sang, Liming Jiang, Qing Yan, Sijia Liu, Linjie Luo
2025	A*	`conf`	Invariance Makes LLM Unlearning Resilient Even to Unanticipated Downstream Fine-Tuning. ICML Changsheng Wang, Yihua Zhang, Jinghan Jia, Parikshit Ram, Dennis Wei, Yuguang Yao, Soumyadeep Pal, Nathalie Baracaldo, Sijia Liu
2025	J	`jnl`	Invariance Makes LLM Unlearning Resilient Even to Unanticipated Downstream Fine-Tuning. CoRR Changsheng Wang, Yihua Zhang, Jinghan Jia, Parikshit Ram, Dennis Wei, Yuguang Yao, Soumyadeep Pal, Nathalie Baracaldo, Sijia Liu
2025	J	`jnl`	Invisible Watermarks, Visible Gains: Steering Machine Unlearning with Bi-Level Watermarking Design. CoRR Yuhao Sun, Yihua Zhang, Gaowen Liu, Hongtao Xie, Sijia Liu
2025	J	`jnl`	LLM Unlearning Reveals a Stronger-Than-Expected Coreset Effect in Current Benchmarks. CoRR Soumyadeep Pal, Changsheng Wang, James Diffenderfer, Bhavya Kailkhura, Sijia Liu
2025	J	`jnl`	LLM Unlearning Under the Microscope: A Full-Stack View on Methods and Metrics. CoRR Chongyu Fan, Changsheng Wang, Yancheng Huang, Soumyadeep Pal, Sijia Liu
2025	—	`conf`	LLM Unlearning on Noisy Forget Sets: A Study of Incomplete, Rewritten, and Watermarked Data. AISec@CCS Changsheng Wang, Yihua Zhang, Dennis Wei, Jinghan Jia, Pin-Yu Chen, Sijia Liu
2025	J	`jnl`	LLM Unlearning on Noisy Forget Sets: A Study of Incomplete, Rewritten, and Watermarked Data. CoRR Changsheng Wang, Yihua Zhang, Dennis Wei, Jinghan Jia, Pin-Yu Chen, Sijia Liu
2025	J	`jnl`	Leak@k: Unlearning Does Not Make LLMs Forget Under Probabilistic Decoding. CoRR Hadi Reisizadeh, Jiajun Ruan, Yiwei Chen, Soumyadeep Pal, Sijia Liu, Mingyi Hong
2025	J	`jnl`	One Token Embedding Is Enough to Deadlock Your Large Reasoning Model. CoRR Mohan Zhang, Yihua Zhang, Jinghan Jia, Zhangyang Wang, Sijia Liu, Tianlong Chen
2025	A*	`conf`	PSBD: Prediction Shift Uncertainty Unlocks Backdoor Detection. CVPR Wei Li, Pin-Yu Chen, Sijia Liu, Ren Wang
2025	Misc	`conf`	Pruning then Reweighting: Towards Data-Efficient Training of Diffusion Models. ICASSP Yize Li, Yihua Zhang, Sijia Liu, Xue Lin
2025	A*	`conf`	Reasoning Model Unlearning: Forgetting Traces, Not Just Answers, While Preserving Reasoning Skills. EMNLP Changsheng Wang, Chongyu Fan, Yihua Zhang, Jinghan Jia, Dennis Wei, Parikshit Ram, Nathalie Baracaldo, Sijia Liu
2025	J	`jnl`	Reasoning Model Unlearning: Forgetting Traces, Not Just Answers, While Preserving Reasoning Skills. CoRR Changsheng Wang, Chongyu Fan, Yihua Zhang, Jinghan Jia, Dennis Wei, Parikshit Ram, Nathalie Baracaldo, Sijia Liu
2025	J	`jnl`	Rethinking machine unlearning for large language models. Nat. Mac. Intell. Sijia Liu, Yuanshun Yao, Jinghan Jia, Stephen Casper, Nathalie Baracaldo, Peter Hase, Yuguang Yao, Chris Yuhao Liu, Xiaojun Xu, Hang Li, Kush R. Varshney, Mohit Bansal, Sanmi Koyejo, Yang Liu
2025	J	`jnl`	Robust MRI Reconstruction by Smoothed Unrolling (SMUG). IEEE J. Sel. Top. Signal Process. Shijun Liang, Van Hoang Minh Nguyen, Jinghan Jia, Ismail R. Alkhouri, Sijia Liu, Saiprasad Ravishankar
2025	—	`conf`	SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? ACL (1) Haomin Zhuang, Yihua Zhang, Kehan Guo, Jinghan Jia, Gaowen Liu, Sijia Liu, Xiangliang Zhang
2025	J	`jnl`	Safety Mirage: How Spurious Correlations Undermine VLM Safety Fine-tuning. CoRR Yiwei Chen, Yuguang Yao, Yihua Zhang, Bingquan Shen, Gaowen Liu, Sijia Liu
2025	J	`jnl`	Scalable Back-Propagation-Free Training of Optical Physics-Informed Neural Networks. CoRR Yequan Zhao, Xinling Yu, Xian Xiao, Zhixiong Chen, Ziyue Liu, Geza Kurczveil, Raymond G. Beausoleil, Sijia Liu, Zheng Zhang
2025	J	`jnl`	The Dual Power of Interpretable Token Embeddings: Jailbreaking Attacks and Defenses for Diffusion Model Unlearning. CoRR Siyi Chen, Yimeng Zhang, Sijia Liu, Qing Qu
2025	A*	`conf`	Towards LLM Unlearning Resilient to Relearning Attacks: A Sharpness-Aware Minimization Perspective and Beyond. ICML Chongyu Fan, Jinghan Jia, Yihua Zhang, Anil Ramakrishna, Mingyi Hong, Sijia Liu
2025	J	`jnl`	Towards LLM Unlearning Resilient to Relearning Attacks: A Sharpness-Aware Minimization Perspective and Beyond. CoRR Chongyu Fan, Jinghan Jia, Yihua Zhang, Anil Ramakrishna, Mingyi Hong, Sijia Liu
2025	J	`jnl`	Unlearning Isn't Invisible: Detecting Unlearning Traces in LLMs from Model Outputs. CoRR Yiwei Chen, Soumyadeep Pal, Yimeng Zhang, Qing Qu, Sijia Liu
2025	A*	`conf`	Visual Prompting Upgrades Neural Network Sparsification: A Data-Model Perspective. AAAI Can Jin, Tianjin Huang, Yihua Zhang, Mykola Pechenizkiy, Sijia Liu, Shiwei Liu, Tianlong Chen
2025	A*	`conf`	When is Task Vector Provably Effective for Model Editing? A Generalization Analysis of Nonlinear Transformers. ICLR Hongkang Li, Yihua Zhang, Shuai Zhang, Pin-Yu Chen, Sijia Liu, Meng Wang
2025	J	`jnl`	When is Task Vector Provably Effective for Model Editing? A Generalization Analysis of Nonlinear Transformers. CoRR Hongkang Li, Yihua Zhang, Shuai Zhang, Meng Wang, Sijia Liu, Pin-Yu Chen
2024	—	`conf`	Advancing the Robustness of Large Language Models through Self-Denoised Smoothing. NAACL (Short Papers) Jiabao Ji, Bairu Hou, Zhen Zhang, Guanhua Zhang, Wenqi Fan, Qing Li, Yang Zhang, Gaowen Liu, Sijia Liu, Shiyu Chang
2024	J	`jnl`	Advancing the Robustness of Large Language Models through Self-Denoised Smoothing. CoRR Jiabao Ji, Bairu Hou, Zhen Zhang, Guanhua Zhang, Wenqi Fan, Qing Li, Yang Zhang, Gaowen Liu, Sijia Liu, Shiyu Chang
2024	J	`jnl`	Adversarial Watermarking for Face Recognition. CoRR Yuguang Yao, Anil K. Jain, Sijia Liu
2024	J	`jnl`	An Introduction to Bilevel Optimization: Foundations and applications in signal processing and machine learning. IEEE Signal Process. Mag. Yihua Zhang, Prashant Khanduri, Ioannis C. Tsaknakis, Yuguang Yao, Mingyi Hong, Sijia Liu
2024	A*	`conf`	Backdoor Secrets Unveiled: Identifying Backdoor Data with Optimized Scaled Prediction Consistency. ICLR Soumyadeep Pal, Yuguang Yao, Ren Wang, Bingquan Shen, Sijia Liu
2024	J	`jnl`	Backdoor Secrets Unveiled: Identifying Backdoor Data with Optimized Scaled Prediction Consistency. CoRR Soumyadeep Pal, Yuguang Yao, Ren Wang, Bingquan Shen, Sijia Liu
2024	—	`conf`	Challenging Forgets: Unveiling the Worst-Case Forget Sets in Machine Unlearning. ECCV (21) Chongyu Fan, Jiancheng Liu, Alfred Olivier Hero, Sijia Liu
2024	J	`jnl`	Challenging Forgets: Unveiling the Worst-Case Forget Sets in Machine Unlearning. CoRR Chongyu Fan, Jiancheng Liu, Alfred O. Hero III, Sijia Liu
2024	J	`jnl`	Correction to: Stochastic inexact augmented Lagrangian method for nonconvex expectation constrained optimization. Comput. Optim. Appl. Zichong Li, Pin-Yu Chen, Sijia Liu, Songtao Lu, Yangyang Xu
2024	A	`conf`	CryoRL: Reinforcement Learning Enables Efficient Cryo-EM Data Collection. WACV Quanfu Fan, Yilai Li, Yuguang Yao, John Cohn, Sijia Liu, Ziping Xu, Seychelle M. Vos, Michael A. Cianfrocco
2024	A*	`conf`	DeepZero: Scaling Up Zeroth-Order Optimization for Deep Model Training. ICLR Aochuan Chen, Yimeng Zhang, Jinghan Jia, James Diffenderfer, Konstantinos Parasyris, Jiancheng Liu, Yihua Zhang, Zheng Zhang, Bhavya Kailkhura, Sijia Liu
2024	A*	`conf`	Defensive Unlearning with Adversarial Training for Robust Concept Erasure in Diffusion Models. NeurIPS Yimeng Zhang, Xin Chen, Jinghan Jia, Yihua Zhang, Chongyu Fan, Jiancheng Liu, Mingyi Hong, Ke Ding, Sijia Liu
2024	J	`jnl`	Defensive Unlearning with Adversarial Training for Robust Concept Erasure in Diffusion Models. CoRR Yimeng Zhang, Xin Chen, Jinghan Jia, Yihua Zhang, Chongyu Fan, Jiancheng Liu, Mingyi Hong, Ke Ding, Sijia Liu
2024	J	`jnl`	Edit Away and My Face Will not Stay: Personal Biometric Defense against Malicious Generative Editing. CoRR Hanhui Wang, Yihua Zhang, Ruizheng Bai, Yue Zhao, Sijia Liu, Zhengzhong Tu
2024	Misc	`conf`	Elevating Visual Prompting in Transfer Learning Via Pruned Model Ensembles: No Retrain, No Pain. ICASSP Brian Zhang, Yuguang Yao, Sijia Liu
2024	J	`jnl`	FairSkin: Fair Diffusion for Skin Disease Image Generation. CoRR Ruichen Zhang, Yuguang Yao, Zhen Tan, Zhiming Li, Pan Wang, Huan Liu, Jingtong Hu, Sijia Liu, Tianlong Chen
2024	J	`jnl`	Forget Vectors at Play: Universal Input Perturbations Driving Machine Unlearning in Image Classification. CoRR Changchang Sun, Ren Wang, Yihua Zhang, Jinghan Jia, Jiancheng Liu, Gaowen Liu, Sijia Liu, Yan Yan
2024	A*	`conf`	From Trojan Horses to Castle Walls: Unveiling Bilateral Data Poisoning Effects in Diffusion Models. NeurIPS Zhuoshi Pan, Yuguang Yao, Gaowen Liu, Bingquan Shen, H. Vicky Zhao, Ramana Kompella, Sijia Liu
2024	J	`jnl`	Hide and Seek: How Does Watermarking Impact Face Recognition? CoRR Yuguang Yao, Steven A. Grosz, Sijia Liu, Anil K. Jain
2024	J	`jnl`	How does promoting the minority fraction affect generalization? A theoretical study of the one-hidden-layer neural network on group imbalance. CoRR Hongkang Li, Shuai Zhang, Yihua Zhang, Meng Wang, Sijia Liu, Pin-Yu Chen
2024	J	`jnl`	ID-Patch: Robust ID Association for Group Photo Personalization. CoRR Yimeng Zhang, Tiancheng Zhi, Jing Liu, Shen Sang, Liming Jiang, Qing Yan, Sijia Liu, Linjie Luo
2024	J	`jnl`	Label Smoothing Improves Machine Unlearning. CoRR Zonglin Di, Zhaowei Zhu, Jinghan Jia, Jiancheng Liu, Zafar Takhirov, Bo Jiang, Yuanshun Yao, Sijia Liu, Yang Liu
2024	—	`conf`	Learning on Transformers is Provable Low-Rank and Sparse: A One-layer Analysis. SAM Hongkang Li, Meng Wang, Shuai Zhang, Sijia Liu, Pin-Yu Chen
2024	J	`jnl`	Learning on Transformers is Provable Low-Rank and Sparse: A One-layer Analysis. CoRR Hongkang Li, Meng Wang, Shuai Zhang, Sijia Liu, Pin-Yu Chen
2024	—	`conf`	More Samples or More Prompts? Exploring Effective Few-Shot In-Context Learning for LLMs with In-Context Sampling. NAACL-HLT (Findings) Bingsheng Yao, Guiming Chen, Ruishi Zou, Yuxuan Lu, Jiachen Li, Shao Zhang, Yisi Sang, Sijia Liu, James A. Hendler, Dakuo Wang
2024	J	`jnl`	PSBD: Prediction Shift Uncertainty Unlocks Backdoor Detection. CoRR Wei Li, Pin-Yu Chen, Sijia Liu, Ren Wang
2024	J	`jnl`	Pruning then Reweighting: Towards Data-Efficient Training of Diffusion Models. CoRR Yize Li, Yihua Zhang, Sijia Liu, Xue Lin
2024	J	`jnl`	Rethinking Machine Unlearning for Large Language Models. CoRR Sijia Liu, Yuanshun Yao, Jinghan Jia, Stephen Casper, Nathalie Baracaldo, Peter Hase, Xiaojun Xu, Yuguang Yao, Hang Li, Kush R. Varshney, Mohit Bansal, Sanmi Koyejo, Yang Liu
2024	J	`jnl`	Reverse Engineering of Deceptions on Machine- and Human-Centric Attacks. Found. Trends Priv. Secur. Yuguang Yao, Xiao Guo, Vishal Asnani, Yifan Gong, Jiancheng Liu, Xue Lin, Xiaoming Liu, Sijia Liu
2024	A*	`conf`	Reversing the Forget-Retain Objectives: An Efficient LLM Unlearning Framework from Logit Difference. NeurIPS Jiabao Ji, Yujian Liu, Yang Zhang, Gaowen Liu, Ramana Kompella, Sijia Liu, Shiyu Chang
2024	J	`jnl`	Reversing the Forget-Retain Objectives: An Efficient LLM Unlearning Framework from Logit Difference. CoRR Jiabao Ji, Yujian Liu, Yang Zhang, Gaowen Liu, Ramana Rao Kompella, Sijia Liu, Shiyu Chang
2024	A*	`conf`	Revisiting Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning: A Benchmark. ICML 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
2024	J	`jnl`	Revisiting Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning: A Benchmark. CoRR 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
2024	A*	`conf`	SOUL: Unlocking the Power of Second-Order Optimization for LLM Unlearning. EMNLP Jinghan Jia, Yihua Zhang, Yimeng Zhang, Jiancheng Liu, Bharat Runwal, James Diffenderfer, Bhavya Kailkhura, Sijia Liu
2024	J	`jnl`	SOUL: Unlocking the Power of Second-Order Optimization for LLM Unlearning. CoRR Jinghan Jia, Yihua Zhang, Yimeng Zhang, Jiancheng Liu, Bharat Runwal, James Diffenderfer, Bhavya Kailkhura, Sijia Liu
2024	A*	`conf`	SalUn: Empowering Machine Unlearning via Gradient-based Weight Saliency in Both Image Classification and Generation. ICLR Chongyu Fan, Jiancheng Liu, Yihua Zhang, Eric Wong, Dennis Wei, Sijia Liu
2024	J	`jnl`	Simplicity Prevails: Rethinking Negative Preference Optimization for LLM Unlearning. CoRR Chongyu Fan, Jiancheng Liu, Licong Lin, Jinghan Jia, Ruiqi Zhang, Song Mei, Sijia Liu
2024	J	`jnl`	Stochastic inexact augmented Lagrangian method for nonconvex expectation constrained optimization. Comput. Optim. Appl. Zichong Li, Pin-Yu Chen, Sijia Liu, Songtao Lu, Yangyang Xu
2024	Misc	`conf`	The Power of Few: Accelerating and Enhancing Data Reweighting with Coreset Selection. ICASSP Mohammad Jafari, Yimeng Zhang, Yihua Zhang, Sijia Liu
2024	J	`jnl`	The Power of Few: Accelerating and Enhancing Data Reweighting with Coreset Selection. CoRR Mohammad Jafari, Yimeng Zhang, Yihua Zhang, Sijia Liu
2024	—	`conf`	To Generate or Not? Safety-Driven Unlearned Diffusion Models Are Still Easy to Generate Unsafe Images ... For Now. ECCV (57) Yimeng Zhang, Jinghan Jia, Xin Chen, Aochuan Chen, Yihua Zhang, Jiancheng Liu, Ke Ding, Sijia Liu
2024	A*	`conf`	Tracing Hyperparameter Dependencies for Model Parsing via Learnable Graph Pooling Network. NeurIPS Xiao Guo, Vishal Asnani, Sijia Liu, Xiaoming Liu
2024	J	`jnl`	UOE: Unlearning One Expert Is Enough For Mixture-of-experts LLMS. CoRR Haomin Zhuang, Yihua Zhang, Kehan Guo, Jinghan Jia, Gaowen Liu, Sijia Liu, Xiangliang Zhang
2024	J	`jnl`	UnlearnCanvas: A Stylized Image Dataset to Benchmark Machine Unlearning for Diffusion Models. CoRR Yihua Zhang, Yimeng Zhang, Yuguang Yao, Jinghan Jia, Jiancheng Liu, Xiaoming Liu, Sijia Liu
2024	A*	`conf`	UnlearnCanvas: Stylized Image Dataset for Enhanced Machine Unlearning Evaluation in Diffusion Models. NeurIPS Yihua Zhang, Chongyu Fan, Yimeng Zhang, Yuguang Yao, Jinghan Jia, Jiancheng Liu, Gaoyuan Zhang, Gaowen Liu, Ramana Kompella, Xiaoming Liu, Sijia Liu
2024	A*	`conf`	WAGLE: Strategic Weight Attribution for Effective and Modular Unlearning in Large Language Models. NeurIPS Jinghan Jia, Jiancheng Liu, Yihua Zhang, Parikshit Ram, Nathalie Baracaldo, Sijia Liu
2024	J	`jnl`	WAGLE: Strategic Weight Attribution for Effective and Modular Unlearning in Large Language Models. CoRR Jinghan Jia, Jiancheng Liu, Yihua Zhang, Parikshit Ram, Nathalie Baracaldo, Sijia Liu
2024	A*	`conf`	What Improves the Generalization of Graph Transformers? A Theoretical Dive into the Self-attention and Positional Encoding. ICML Hongkang Li, Meng Wang, Tengfei Ma, Sijia Liu, Zaixi Zhang, Pin-Yu Chen
2024	J	`jnl`	What Improves the Generalization of Graph Transformers? A Theoretical Dive into the Self-attention and Positional Encoding. CoRR Hongkang Li, Meng Wang, Tengfei Ma, Sijia Liu, Zaixi Zhang, Pin-Yu Chen
2023	—	`conf`	A Pilot Study of Query-Free Adversarial Attack against Stable Diffusion. CVPR Workshops Haomin Zhuang, Yihua Zhang, Sijia Liu
2023	J	`jnl`	A Pilot Study of Query-Free Adversarial Attack against Stable Diffusion. CoRR Haomin Zhuang, Yihua Zhang, Sijia Liu
2023	A*	`conf`	A Theoretical Understanding of Shallow Vision Transformers: Learning, Generalization, and Sample Complexity. ICLR Hongkang Li, Meng Wang, Sijia Liu, Pin-Yu Chen
2023	J	`jnl`	A Theoretical Understanding of shallow Vision Transformers: Learning, Generalization, and Sample Complexity. CoRR Hongkang Li, Meng Wang, Sijia Liu, Pin-Yu Chen
2023	A*	`conf`	AAAI New Faculty Highlights: General and Scalable Optimization for Robust AI. AAAI Sijia Liu
2023	J	`jnl`	An Introduction to Bi-level Optimization: Foundations and Applications in Signal Processing and Machine Learning. CoRR Yihua Zhang, Prashant Khanduri, Ioannis C. Tsaknakis, Yuguang Yao, Mingyi Hong, Sijia Liu
2023	A	`conf`	AutoSeqRec: Autoencoder for Efficient Sequential Recommendation. CIKM Sijia Liu, Jiahao Liu, Hansu Gu, Dongsheng Li, Tun Lu, Peng Zhang, Ning Gu
2023	J	`jnl`	AutoSeqRec: Autoencoder for Efficient Sequential Recommendation. CoRR Sijia Liu, Jiahao Liu, Hansu Gu, Dongsheng Li, Tun Lu, Peng Zhang, Ning Gu
2023	J	`jnl`	AutoVP: An Automated Visual Prompting Framework and Benchmark. CoRR Hsi-Ai Tsao, Lei Hsiung, Pin-Yu Chen, Sijia Liu, Tsung-Yi Ho
2023	J	`jnl`	Can Adversarial Examples Be Parsed to Reveal Victim Model Information? CoRR Yuguang Yao, Jiancheng Liu, Yifan Gong, Xiaoming Liu, Yanzhi Wang, Xue Lin, Sijia Liu
2023	J	`jnl`	Certified Interpretability Robustness for Class Activation Mapping. CoRR Alex Gu, Tsui-Wei Weng, Pin-Yu Chen, Sijia Liu, Luca Daniel
2023	J	`jnl`	Certified Robustness for Large Language Models with Self-Denoising. CoRR Zhen Zhang, Guanhua Zhang, Bairu Hou, Wenqi Fan, Qing Li, Sijia Liu, Yang Zhang, Shiyu Chang
2023	A	`conf`	ClawSAT: Towards Both Robust and Accurate Code Models. SANER Jinghan Jia, Shashank Srikant, Tamara Mitrovska, Chuang Gan, Shiyu Chang, Sijia Liu, Una-May O'Reilly
2023	—	`conf`	Data-Model-Circuit Tri-Design for Ultra-Light Video Intelligence on Edge Devices. ASP-DAC Yimeng Zhang, Akshay Karkal Kamath, Qiucheng Wu, Zhiwen Fan, Wuyang Chen, Zhangyang Wang, Shiyu Chang, Sijia Liu, Cong Hao
2023	J	`jnl`	DeepZero: Scaling up Zeroth-Order Optimization for Deep Model Training. CoRR Aochuan Chen, Yimeng Zhang, Jinghan Jia, James Diffenderfer, Jiancheng Liu, Konstantinos Parasyris, Yihua Zhang, Zheng Zhang, Bhavya Kailkhura, Sijia Liu
2023	J	`jnl`	Designing a Direct Feedback Loop between Humans and Convolutional Neural Networks through Local Explanations. CoRR Tong Steven Sun, Yuyang Gao, Shubham Khaladkar, Sijia Liu, Liang Zhao, Young-Ho Kim, Sungsoo Ray Hong
2023	J	`jnl`	Designing a Direct Feedback Loop between Humans and Convolutional Neural Networks through Local Explanations. Proc. ACM Hum. Comput. Interact. Tong Steven Sun, Yuyang Gao, Shubham Khaladkar, Sijia Liu, Liang Zhao, Young-Ho Kim, Sungsoo Ray Hong
2023	—	`conf`	Exploring Diversified Adversarial Robustness in Neural Networks via Robust Mode Connectivity. CVPR Workshops Ren Wang, Yuxuan Li, Sijia Liu
2023	J	`jnl`	Fairness Improves Learning from Noisily Labeled Long-Tailed Data. CoRR Jiaheng Wei, Zhaowei Zhu, Gang Niu, Tongliang Liu, Sijia Liu, Masashi Sugiyama, Yang Liu
2023	J	`jnl`	From Trojan Horses to Castle Walls: Unveiling Bilateral Backdoor Effects in Diffusion Models. CoRR Zhuoshi Pan, Yuguang Yao, Gaowen Liu, Bingquan Shen, H. Vicky Zhao, Ramana Rao Kompella, Sijia Liu
2023	A*	`conf`	Holistic Adversarial Robustness of Deep Learning Models. AAAI Pin-Yu Chen, Sijia Liu
2023	A*	`conf`	Joint Edge-Model Sparse Learning is Provably Efficient for Graph Neural Networks. ICLR Shuai Zhang, Meng Wang, Pin-Yu Chen, Sijia Liu, Songtao Lu, Miao Liu
2023	J	`jnl`	Joint Edge-Model Sparse Learning is Provably Efficient for Graph Neural Networks. CoRR Shuai Zhang, Meng Wang, Pin-Yu Chen, Sijia Liu, Songtao Lu, Miao Liu
2023	A*	`conf`	Linearly Constrained Bilevel Optimization: A Smoothed Implicit Gradient Approach. ICML Prashant Khanduri, Ioannis C. Tsaknakis, Yihua Zhang, Jia Liu, Sijia Liu, Jiawei Zhang, Mingyi Hong
2023	J	`jnl`	Model Sparsification Can Simplify Machine Unlearning. CoRR Jinghan Jia, Jiancheng Liu, Parikshit Ram, Yuguang Yao, Gaowen Liu, Yang Liu, Pranay Sharma, Sijia Liu
2023	A*	`conf`	Model Sparsity Can Simplify Machine Unlearning. NeurIPS Jinghan Jia, Jiancheng Liu, Parikshit Ram, Yuguang Yao, Gaowen Liu, Yang Liu, Pranay Sharma, Sijia Liu
2023	J	`jnl`	More Samples or More Prompt Inputs? Exploring Effective In-Context Sampling for LLM Few-Shot Prompt Engineering. CoRR Bingsheng Yao, Guiming Chen, Ruishi Zou, Yuxuan Lu, Jiachen Li, Shao Zhang, Sijia Liu, James A. Hendler, Dakuo Wang
2023	A*	`conf`	On the Convergence and Sample Complexity Analysis of Deep Q-Networks with ε-Greedy Exploration. NeurIPS Shuai Zhang, Hongkang Li, Meng Wang, Miao Liu, Pin-Yu Chen, Songtao Lu, Sijia Liu, Keerthiram Murugesan, Subhajit Chaudhury
2023	J	`jnl`	On the Convergence and Sample Complexity Analysis of Deep Q-Networks with ε-Greedy Exploration. CoRR Shuai Zhang, Hongkang Li, Meng Wang, Miao Liu, Pin-Yu Chen, Songtao Lu, Sijia Liu, Keerthiram Murugesan, Subhajit Chaudhury
2023	A*	`conf`	Patch-level Routing in Mixture-of-Experts is Provably Sample-efficient for Convolutional Neural Networks. ICML Mohammed Nowaz Rabbani Chowdhury, Shuai Zhang, Meng Wang, Sijia Liu, Pin-Yu Chen
2023	J	`jnl`	Patch-level Routing in Mixture-of-Experts is Provably Sample-efficient for Convolutional Neural Networks. CoRR Mohammed Nowaz Rabbani Chowdhury, Shuai Zhang, Meng Wang, Sijia Liu, Pin-Yu Chen
2023	J	`jnl`	Robust MRI Reconstruction by Smoothed Unrolling (SMUG). CoRR Shijun Liang, Van Hoang Minh Nguyen, Jinghan Jia, Ismail Alkhouri, Sijia Liu, Saiprasad Ravishankar
2023	A*	`conf`	Robust Mixture-of-Expert Training for Convolutional Neural Networks. ICCV Yihua Zhang, Ruisi Cai, Tianlong Chen, Guanhua Zhang, Huan Zhang, Pin-Yu Chen, Shiyu Chang, Zhangyang Wang, Sijia Liu
2023	J	`jnl`	Robust Mixture-of-Expert Training for Convolutional Neural Networks. CoRR Yihua Zhang, Ruisi Cai, Tianlong Chen, Guanhua Zhang, Huan Zhang, Pin-Yu Chen, Shiyu Chang, Zhangyang Wang, Sijia Liu
2023	J	`jnl`	Robust Mode Connectivity-Oriented Adversarial Defense: Enhancing Neural Network Robustness Against Diversified 𝓁 CoRR Ren Wang, Yuxuan Li, Sijia Liu
2023	Misc	`conf`	Robustness-Preserving Lifelong Learning Via Dataset Condensation. ICASSP Jinghan Jia, Yihua Zhang, Dogyoon Song, Sijia Liu, Alfred O. Hero III
2023	J	`jnl`	Robustness-preserving Lifelong Learning via Dataset Condensation. CoRR Jinghan Jia, Yihua Zhang, Dogyoon Song, Sijia Liu, Alfred O. Hero III
2023	Misc	`conf`	SMUG: Towards Robust Mri Reconstruction by Smoothed Unrolling. ICASSP Hui Li, Jinghan Jia, Shijun Liang, Yuguang Yao, Saiprasad Ravishankar, Sijia Liu
2023	J	`jnl`	SMUG: Towards robust MRI reconstruction by smoothed unrolling. CoRR Hui Li, Jinghan Jia, Shijun Liang, Yuguang Yao, Saiprasad Ravishankar, Sijia Liu
2023	J	`jnl`	SalUn: Empowering Machine Unlearning via Gradient-based Weight Saliency in Both Image Classification and Generation. CoRR Chongyu Fan, Jiancheng Liu, Yihua Zhang, Dennis Wei, Eric Wong, Sijia Liu
2023	A*	`conf`	Selectivity Drives Productivity: Efficient Dataset Pruning for Enhanced Transfer Learning. NeurIPS Yihua Zhang, Yimeng Zhang, Aochuan Chen, Jinghan Jia, Jiancheng Liu, Gaowen Liu, Mingyi Hong, Shiyu Chang, Sijia Liu
2023	J	`jnl`	Selectivity Drives Productivity: Efficient Dataset Pruning for Enhanced Transfer Learning. CoRR Yihua Zhang, Yimeng Zhang, Aochuan Chen, Jinghan Jia, Jiancheng Liu, Gaowen Liu, Mingyi Hong, Shiyu Chang, Sijia Liu
2023	J	`jnl`	Tensor-Compressed Back-Propagation-Free Training for (Physics-Informed) Neural Networks. CoRR Yequan Zhao, Xinling Yu, Zhixiong Chen, Ziyue Liu, Sijia Liu, Zheng Zhang
2023	A*	`conf`	Text-Visual Prompting for Efficient 2D Temporal Video Grounding. CVPR Yimeng Zhang, Xin Chen, Jinghan Jia, Sijia Liu, Ke Ding
2023	J	`jnl`	Text-Visual Prompting for Efficient 2D Temporal Video Grounding. CoRR Yimeng Zhang, Xin Chen, Jinghan Jia, Sijia Liu, Ke Ding
2023	A*	`conf`	TextGrad: Advancing Robustness Evaluation in NLP by Gradient-Driven Optimization. ICLR Bairu Hou, Jinghan Jia, Yihua Zhang, Guanhua Zhang, Yang Zhang, Sijia Liu, Shiyu Chang
2023	J	`jnl`	To Generate or Not? Safety-Driven Unlearned Diffusion Models Are Still Easy To Generate Unsafe Images ... For Now. CoRR Yimeng Zhang, Jinghan Jia, Xin Chen, Aochuan Chen, Yihua Zhang, Jiancheng Liu, Ke Ding, Sijia Liu
2023	—	`conf`	Towards Understanding How Self-training Tolerates Data Backdoor Poisoning. SafeAI@AAAI Soumyadeep Pal, Ren Wang, Yuguang Yao, Sijia Liu
2023	J	`jnl`	Towards Understanding How Self-training Tolerates Data Backdoor Poisoning. CoRR Soumyadeep Pal, Ren Wang, Yuguang Yao, Sijia Liu
2023	J	`jnl`	Tracing Hyperparameter Dependencies for Model Parsing via Learnable Graph Pooling Network. CoRR Xiao Guo, Vishal Asnani, Sijia Liu, Xiaoming Liu
2023	A*	`conf`	Understanding and Improving Visual Prompting: A Label-Mapping Perspective. CVPR Aochuan Chen, Yuguang Yao, Pin-Yu Chen, Yihua Zhang, Sijia Liu
2023	J	`jnl`	Visual Prompting Upgrades Neural Network Sparsification: A Data-Model Perspective. CoRR Can Jin, Tianjin Huang, Yihua Zhang, Mykola Pechenizkiy, Sijia Liu, Shiwei Liu, Tianlong Chen
2023	Misc	`conf`	Visual Prompting for Adversarial Robustness. ICASSP Aochuan Chen, Peter Lorenz, Yuguang Yao, Pin-Yu Chen, Sijia Liu
2023	A*	`conf`	What Is Missing in IRM Training and Evaluation? Challenges and Solutions. ICLR Yihua Zhang, Pranay Sharma, Parikshit Ram, Mingyi Hong, Kush R. Varshney, Sijia Liu
2023	J	`jnl`	What Is Missing in IRM Training and Evaluation? Challenges and Solutions. CoRR Yihua Zhang, Pranay Sharma, Parikshit Ram, Mingyi Hong, Kush R. Varshney, Sijia Liu
2022	—	`conf`	A Word is Worth A Thousand Dollars: Adversarial Attack on Tweets Fools Stock Prediction. NAACL-HLT Yong Xie, Dakuo Wang, Pin-Yu Chen, Jinjun Xiong, Sijia Liu, Oluwasanmi Koyejo
2022	J	`jnl`	A Word is Worth A Thousand Dollars: Adversarial Attack on Tweets Fools Stock Prediction. CoRR Yong Xie, Dakuo Wang, Pin-Yu Chen, Jinjun Xiong, Sijia Liu, Sanmi Koyejo
2022	J	`jnl`	ASK: Adversarial Soft k-Nearest Neighbor Attack and Defense. IEEE Access Ren Wang, Tianqi Chen, Philip Yao, Sijia Liu, Indika Rajapakse, Alfred O. Hero III
2022	A*	`conf`	Advancing Model Pruning via Bi-level Optimization. NeurIPS Yihua Zhang, Yuguang Yao, Parikshit Ram, Pu Zhao, Tianlong Chen, Mingyi Hong, Yanzhi Wang, Sijia Liu
2022	J	`jnl`	Advancing Model Pruning via Bi-level Optimization. CoRR Yihua Zhang, Yuguang Yao, Parikshit Ram, Pu Zhao, Tianlong Chen, Mingyi Hong, Yanzhi Wang, Sijia Liu
2022	A*	`conf`	Adversarial Examples Can Be Effective Data Augmentation for Unsupervised Machine Learning. AAAI Chia-Yi Hsu, Pin-Yu Chen, Songtao Lu, Sijia Liu, Chia-Mu Yu
2022	J	`jnl`	Automatic Mapping of the Best-Suited DNN Pruning Schemes for Real-Time Mobile Acceleration. ACM Trans. Design Autom. Electr. Syst. Yifan Gong, Geng Yuan, Zheng Zhan, Wei Niu, Zhengang Li, Pu Zhao, Yuxuan Cai, Sijia Liu, Bin Ren, Xue Lin, Xulong Tang, Yanzhi Wang
2022	J	`jnl`	CLAWSAT: Towards Both Robust and Accurate Code Models. CoRR Jinghan Jia, Shashank Srikant, Tamara Mitrovska, Chuang Gan, Shiyu Chang, Sijia Liu, Una-May O'Reilly
2022	J	`jnl`	Can You Win Everything with A Lottery Ticket? Trans. Mach. Learn. Res. Tianlong Chen, Zhenyu Zhang, Jun Wu, Randy Huang, Sijia Liu, Shiyu Chang, Zhangyang Wang
2022	J	`jnl`	Certifiably robust interpretation via Rényi differential privacy. Artif. Intell. Ao Liu, Xiaoyu Chen, Sijia Liu, Lirong Xia, Chuang Gan
2022	J	`jnl`	CryoRL: Reinforcement Learning Enables Efficient Cryo-EM Data Collection. CoRR Quanfu Fan, Yilai Li, Yuguang Yao, John Cohn, Sijia Liu, Seychelle M. Vos, Michael A. Cianfrocco
2022	A*	`conf`	Data-Efficient Double-Win Lottery Tickets from Robust Pre-training. ICML Tianlong Chen, Zhenyu Zhang, Sijia Liu, Yang Zhang, Shiyu Chang, Zhangyang Wang
2022	J	`jnl`	Data-Efficient Double-Win Lottery Tickets from Robust Pre-training. CoRR Tianlong Chen, Zhenyu Zhang, Sijia Liu, Yang Zhang, Shiyu Chang, Zhangyang Wang
2022	J	`jnl`	Data-Model-Circuit Tri-Design for Ultra-Light Video Intelligence on Edge Devices. CoRR Yimeng Zhang, Akshay Karkal Kamath, Qiucheng Wu, Zhiwen Fan, Wuyang Chen, Zhangyang Wang, Shiyu Chang, Sijia Liu, Cong Hao
2022	A*	`conf`	Decentralized Learning for Overparameterized Problems: A Multi-Agent Kernel Approximation Approach. ICLR Prashant Khanduri, Haibo Yang, Mingyi Hong, Jia Liu, Hoi-To Wai, Sijia Liu
2022	J	`jnl`	Distributed Adversarial Training to Robustify Deep Neural Networks at Scale. CoRR Gaoyuan Zhang, Songtao Lu, Yihua Zhang, Xiangyi Chen, Pin-Yu Chen, Quanfu Fan, Lee Martie, Lior Horesh, Mingyi Hong, Sijia Liu
2022	A	`conf`	Distributed adversarial training to robustify deep neural networks at scale. UAI Gaoyuan Zhang, Songtao Lu, Yihua Zhang, Xiangyi Chen, Pin-Yu Chen, Quanfu Fan, Lee Martie, Lior Horesh, Mingyi Hong, Sijia Liu
2022	A*	`conf`	Fairness Reprogramming. NeurIPS Guanhua Zhang, Yihua Zhang, Yang Zhang, Wenqi Fan, Qing Li, Sijia Liu, Shiyu Chang
2022	J	`jnl`	Fairness Reprogramming. CoRR Guanhua Zhang, Yihua Zhang, Yang Zhang, Wenqi Fan, Qing Li, Sijia Liu, Shiyu Chang
2022	A*	`conf`	Generalization Guarantee of Training Graph Convolutional Networks with Graph Topology Sampling. ICML Hongkang Li, Meng Wang, Sijia Liu, Pin-Yu Chen, Jinjun Xiong
2022	J	`jnl`	Generalization Guarantee of Training Graph Convolutional Networks with Graph Topology Sampling. CoRR Hongkang Li, Meng Wang, Sijia Liu, Pin-Yu Chen, Jinjun Xiong
2022	J	`jnl`	Holistic Adversarial Robustness of Deep Learning Models. CoRR Pin-Yu Chen, Sijia Liu
2022	J	`jnl`	How does unlabeled data improve generalization in self-training? A one-hidden-layer theoretical analysis. CoRR Shuai Zhang, Meng Wang, Sijia Liu, Pin-Yu Chen, Jinjun Xiong
2022	A*	`conf`	How to Robustify Black-Box ML Models? A Zeroth-Order Optimization Perspective. ICLR Yimeng Zhang, Yuguang Yao, Jinghan Jia, Jinfeng Yi, Mingyi Hong, Shiyu Chang, Sijia Liu
2022	J	`jnl`	How to Robustify Black-Box ML Models? A Zeroth-Order Optimization Perspective. CoRR Yimeng Zhang, Yuguang Yao, Jinghan Jia, Jinfeng Yi, Mingyi Hong, Shiyu Chang, Sijia Liu
2022	A*	`conf`	How unlabeled data improve generalization in self-training? A one-hidden-layer theoretical analysis. ICLR Shuai Zhang, Meng Wang, Sijia Liu, Pin-Yu Chen, Jinjun Xiong
2022	A*	`conf`	Learning to Generate Image Source-Agnostic Universal Adversarial Perturbations. IJCAI Pu Zhao, Parikshit Ram, Songtao Lu, Yuguang Yao, Djallel Bouneffouf, Xue Lin, Sijia Liu
2022	A*	`conf`	Linearity Grafting: Relaxed Neuron Pruning Helps Certifiable Robustness. ICML Tianlong Chen, Huan Zhang, Zhenyu Zhang, Shiyu Chang, Sijia Liu, Pin-Yu Chen, Zhangyang Wang
2022	J	`jnl`	Linearity Grafting: Relaxed Neuron Pruning Helps Certifiable Robustness. CoRR Tianlong Chen, Huan Zhang, Zhenyu Zhang, Shiyu Chang, Sijia Liu, Pin-Yu Chen, Zhangyang Wang
2022	A*	`conf`	Optimizer Amalgamation. ICLR Tianshu Huang, Tianlong Chen, Sijia Liu, Shiyu Chang, Lisa Amini, Zhangyang Wang
2022	J	`jnl`	Optimizer Amalgamation. CoRR Tianshu Huang, Tianlong Chen, Sijia Liu, Shiyu Chang, Lisa Amini, Zhangyang Wang
2022	A*	`conf`	Proactive Image Manipulation Detection. CVPR Vishal Asnani, Xi Yin, Tal Hassner, Sijia Liu, Xiaoming Liu
2022	J	`jnl`	Proactive Image Manipulation Detection. CoRR Vishal Asnani, Xi Yin, Tal Hassner, Sijia Liu, Xiaoming Liu
2022	A*	`conf`	Quarantine: Sparsity Can Uncover the Trojan Attack Trigger for Free. CVPR Tianlong Chen, Zhenyu Zhang, Yihua Zhang, Shiyu Chang, Sijia Liu, Zhangyang Wang
2022	J	`jnl`	Quarantine: Sparsity Can Uncover the Trojan Attack Trigger for Free. CoRR Tianlong Chen, Zhenyu Zhang, Yihua Zhang, Shiyu Chang, Sijia Liu, Zhangyang Wang
2022	J	`jnl`	Queried Unlabeled Data Improves and Robustifies Class-Incremental Learning. CoRR Tianlong Chen, Sijia Liu, Shiyu Chang, Lisa Amini, Zhangyang Wang
2022	J	`jnl`	Queried Unlabeled Data Improves and Robustifies Class-Incremental Learning. Trans. Mach. Learn. Res. Tianlong Chen, Sijia Liu, Shiyu Chang, Lisa Amini, Zhangyang Wang
2022	A*	`conf`	Reverse Engineering of Imperceptible Adversarial Image Perturbations. ICLR Yifan Gong, Yuguang Yao, Yize Li, Yimeng Zhang, Xiaoming Liu, Xue Lin, Sijia Liu
2022	J	`jnl`	Reverse Engineering of Imperceptible Adversarial Image Perturbations. CoRR Yifan Gong, Yuguang Yao, Yize Li, Yimeng Zhang, Xiaoming Liu, Xue Lin, Sijia Liu
2022	A*	`conf`	Revisiting Contrastive Learning through the Lens of Neighborhood Component Analysis: an Integrated Framework. ICML Ching-Yun Ko, Jeet Mohapatra, Sijia Liu, Pin-Yu Chen, Luca Daniel, Lily Weng
2022	A*	`conf`	Revisiting and Advancing Fast Adversarial Training Through The Lens of Bi-Level Optimization. ICML Yihua Zhang, Guanhua Zhang, Prashant Khanduri, Mingyi Hong, Shiyu Chang, Sijia Liu
2022	J	`jnl`	Stochastic Inexact Augmented Lagrangian Method for Nonconvex Expectation Constrained Optimization. CoRR Zichong Li, Pin-Yu Chen, Sijia Liu, Songtao Lu, Yangyang Xu
2022	J	`jnl`	StructADMM: Achieving Ultrahigh Efficiency in Structured Pruning for DNNs. IEEE Trans. Neural Networks Learn. Syst. Tianyun Zhang, Shaokai Ye, Xiaoyu Feng, Xiaolong Ma, Kaiqi Zhang, Zhengang Li, Jian Tang, Sijia Liu, Xue Lin, Yongpan Liu, Makan Fardad, Yanzhi Wang
2022	J	`jnl`	TextGrad: Advancing Robustness Evaluation in NLP by Gradient-Driven Optimization. CoRR Bairu Hou, Jinghan Jia, Yihua Zhang, Guanhua Zhang, Yang Zhang, Sijia Liu, Shiyu Chang
2022	A*	`conf`	The Fourth Workshop on Adversarial Learning Methods for Machine Learning and Data Mining (AdvML 2022). KDD Pin-Yu Chen, Cho-Jui Hsieh, Bo Li, Sijia Liu
2022	J	`jnl`	Understanding and Improving Visual Prompting: A Label-Mapping Perspective. CoRR Aochuan Chen, Yuguang Yao, Pin-Yu Chen, Yihua Zhang, Sijia Liu
2022	J	`jnl`	Visual Prompting for Adversarial Robustness. CoRR Aochuan Chen, Peter Lorenz, Yuguang Yao, Pin-Yu Chen, Sijia Liu
2022	Misc	`conf`	When Does Backdoor Attack Succeed in Image Reconstruction? A Study of Heuristics vs. Bi-Level Solution. ICASSP Vardaan Taneja, Pin-Yu Chen, Yuguang Yao, Sijia Liu
2022	A*	`conf`	Zeroth-Order Optimization for Composite Problems with Functional Constraints. AAAI Zichong Li, Pin-Yu Chen, Sijia Liu, Songtao Lu, Yangyang Xu
2022	J	`jnl`	Zeroth-Order SciML: Non-intrusive Integration of Scientific Software with Deep Learning. CoRR Ioannis C. Tsaknakis, Bhavya Kailkhura, Sijia Liu, Donald Loveland, James Diffenderfer, Anna Maria Hiszpanski, Mingyi Hong
2021	A*	`conf`	A Compression-Compilation Framework for On-mobile Real-time BERT Applications. IJCAI Wei Niu, Zhenglun Kong, Geng Yuan, Weiwen Jiang, Jiexiong Guan, Caiwen Ding, Pu Zhao, Sijia Liu, Bin Ren, Yanzhi Wang
2021	J	`jnl`	A Compression-Compilation Framework for On-mobile Real-time BERT Applications. CoRR Wei Niu, Zhenglun Kong, Geng Yuan, Weiwen Jiang, Jiexiong Guan, Caiwen Ding, Pu Zhao, Sijia Liu, Bin Ren, Yanzhi Wang
2021	J	`jnl`	ASK: Adversarial Soft k-Nearest Neighbor Attack and Defense. CoRR Ren Wang, Tianqi Chen, Philip Yao, Sijia Liu, Indika Rajapakse, Alfred O. Hero III
2021	A*	`conf`	Adversarial Attack Generation Empowered by Min-Max Optimization. NeurIPS Jingkang Wang, Tianyun Zhang, Sijia Liu, Pin-Yu Chen, Jiacen Xu, Makan Fardad, Bo Li
2021	J	`jnl`	Automatic Mapping of the Best-Suited DNN Pruning Schemes for Real-Time Mobile Acceleration. CoRR Yifan Gong, Geng Yuan, Zheng Zhan, Wei Niu, Zhengang Li, Pu Zhao, Yuxuan Cai, Sijia Liu, Bin Ren, Xue Lin, Xulong Tang, Yanzhi Wang
2021	A	`conf`	Brief Industry Paper: Towards Real-Time 3D Object Detection for Autonomous Vehicles with Pruning Search. RTAS Pu Zhao, Wei Niu, Geng Yuan, Yuxuan Cai, Hsin-Hsuan Sung, Shaoshan Liu, Sijia Liu, Xipeng Shen, Bin Ren, Yanzhi Wang, Xue Lin
2021	J	`jnl`	Certifiably Robust Interpretation via Renyi Differential Privacy. CoRR Ao Liu, Xiaoyu Chen, Sijia Liu, Lirong Xia, Chuang Gan
2021	A*	`conf`	Fast Training of Provably Robust Neural Networks by SingleProp. AAAI Akhilan Boopathy, Lily Weng, Sijia Liu, Pin-Yu Chen, Gaoyuan Zhang, Luca Daniel
2021	J	`jnl`	Fast Training of Provably Robust Neural Networks by SingleProp. CoRR Akhilan Boopathy, Tsui-Wei Weng, Sijia Liu, Pin-Yu Chen, Gaoyuan Zhang, Luca Daniel
2021	A*	`conf`	Generating Adversarial Computer Programs using Optimized Obfuscations. ICLR Shashank Srikant, Sijia Liu, Tamara Mitrovska, Shiyu Chang, Quanfu Fan, Gaoyuan Zhang, Una-May O'Reilly
2021	J	`jnl`	Generating Adversarial Computer Programs using Optimized Obfuscations. CoRR Shashank Srikant, Sijia Liu, Tamara Mitrovska, Shiyu Chang, Quanfu Fan, Gaoyuan Zhang, Una-May O'Reilly
2021	A	`conf`	Hidden Cost of Randomized Smoothing. AISTATS Jeet Mohapatra, Ching-Yun Ko, Lily Weng, Pin-Yu Chen, Sijia Liu, Luca Daniel
2021	J	`jnl`	Improved Linear Convergence of Training CNNs With Generalizability Guarantees: A One-Hidden-Layer Case. IEEE Trans. Neural Networks Learn. Syst. Shuai Zhang, Meng Wang, Jinjun Xiong, Sijia Liu, Pin-Yu Chen
2021	—	`conf`	Instabilities in Conventional Multi-Coil MRI Reconstruction with Small Adversarial Perturbations. ACSCC Chi Zhang, Jinghan Jia, Burhaneddin Yaman, Steen Moeller, Sijia Liu, Mingyi Hong, Mehmet Akçakaya
2021	A*	`conf`	Long Live the Lottery: The Existence of Winning Tickets in Lifelong Learning. ICLR Tianlong Chen, Zhenyu Zhang, Sijia Liu, Shiyu Chang, Zhangyang Wang
2021	J	`jnl`	Lottery Ticket Implies Accuracy Degradation, Is It a Desirable Phenomenon? CoRR Ning Liu, Geng Yuan, Zhengping Che, Xuan Shen, Xiaolong Ma, Qing Jin, Jian Ren, Jian Tang, Sijia Liu, Yanzhi Wang
2021	A*	`conf`	Lottery Ticket Preserves Weight Correlation: Is It Desirable or Not? ICML Ning Liu, Geng Yuan, Zhengping Che, Xuan Shen, Xiaolong Ma, Qing Jin, Jian Ren, Jian Tang, Sijia Liu, Yanzhi Wang
2021	A*	`conf`	MEST: Accurate and Fast Memory-Economic Sparse Training Framework on the Edge. NeurIPS 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
2021	J	`jnl`	MEST: Accurate and Fast Memory-Economic Sparse Training Framework on the Edge. CoRR 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
2021	A*	`conf`	NPAS: A Compiler-Aware Framework of Unified Network Pruning and Architecture Search for Beyond Real-Time Mobile Acceleration. CVPR 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
2021	A*	`conf`	On Fast Adversarial Robustness Adaptation in Model-Agnostic Meta-Learning. ICLR Ren Wang, Kaidi Xu, Sijia Liu, Pin-Yu Chen, Tsui-Wei Weng, Chuang Gan, Meng Wang
2021	J	`jnl`	On Fast Adversarial Robustness Adaptation in Model-Agnostic Meta-Learning. CoRR Ren Wang, Kaidi Xu, Sijia Liu, Pin-Yu Chen, Tsui-Wei Weng, Chuang Gan, Meng Wang
2021	J	`jnl`	On Instabilities of Conventional Multi-Coil MRI Reconstruction to Small Adverserial Perturbations. CoRR Chi Zhang, Jinghan Jia, Burhaneddin Yaman, Steen Moeller, Sijia Liu, Mingyi Hong, Mehmet Akçakaya
2021	J	`jnl`	Preserve, Promote, or Attack? GNN Explanation via Topology Perturbation. CoRR Yi Sun, Abel N. Valente, Sijia Liu, Dakuo Wang
2021	A*	`conf`	RMSMP: A Novel Deep Neural Network Quantization Framework with Row-wise Mixed Schemes and Multiple Precisions. ICCV Sung-En Chang, Yanyu Li, Mengshu Sun, Weiwen Jiang, Sijia Liu, Yanzhi Wang, Xue Lin
2021	J	`jnl`	RMSMP: A Novel Deep Neural Network Quantization Framework with Row-wise Mixed Schemes and Multiple Precisions. CoRR Sung-En Chang, Yanyu Li, Mengshu Sun, Weiwen Jiang, Sijia Liu, Yanzhi Wang, Xue Lin
2021	A*	`conf`	RT3D: Achieving Real-Time Execution of 3D Convolutional Neural Networks on Mobile Devices. AAAI Wei Niu, Mengshu Sun, Zhengang Li, Jou-An Chen, Jiexiong Guan, Xipeng Shen, Yanzhi Wang, Sijia Liu, Xue Lin, Bin Ren
2021	A	`conf`	Rate-improved inexact augmented Lagrangian method for constrained nonconvex optimization. AISTATS Zichong Li, Pin-Yu Chen, Sijia Liu, Songtao Lu, Yangyang Xu
2021	J	`jnl`	Revisiting Contrastive Learning through the Lens of Neighborhood Component Analysis: an Integrated Framework. CoRR Ching-Yun Ko, Jeet Mohapatra, Sijia Liu, Pin-Yu Chen, Luca Daniel, Lily Weng
2021	J	`jnl`	Revisiting and Advancing Fast Adversarial Training Through The Lens of Bi-Level Optimization. CoRR Yihua Zhang, Guanhua Zhang, Prashant Khanduri, Mingyi Hong, Shiyu Chang, Sijia Liu
2021	A*	`conf`	Robust Overfitting may be mitigated by properly learned smoothening. ICLR Tianlong Chen, Zhenyu Zhang, Sijia Liu, Shiyu Chang, Zhangyang Wang
2021	A*	`conf`	Sanity Checks for Lottery Tickets: Does Your Winning Ticket Really Win the Jackpot? NeurIPS Xiaolong Ma, Geng Yuan, Xuan Shen, Tianlong Chen, Xuxi Chen, Xiaohan Chen, Ning Liu, Minghai Qin, Sijia Liu, Zhangyang Wang, Yanzhi Wang
2021	J	`jnl`	Sanity Checks for Lottery Tickets: Does Your Winning Ticket Really Win the Jackpot? CoRR Xiaolong Ma, Geng Yuan, Xuan Shen, Tianlong Chen, Xuxi Chen, Xiaohan Chen, Ning Liu, Minghai Qin, Sijia Liu, Zhangyang Wang, Yanzhi Wang
2021	A*	`conf`	Self-Progressing Robust Training. AAAI Minhao Cheng, Pin-Yu Chen, Sijia Liu, Shiyu Chang, Cho-Jui Hsieh, Payel Das
2021	J	`jnl`	Sign-MAML: Efficient Model-Agnostic Meta-Learning by SignSGD. CoRR Chen Fan, Parikshit Ram, Sijia Liu
2021	A*	`conf`	The Lottery Tickets Hypothesis for Supervised and Self-Supervised Pre-Training in Computer Vision Models. CVPR Tianlong Chen, Jonathan Frankle, Shiyu Chang, Sijia Liu, Yang Zhang, Michael Carbin, Zhangyang Wang
2021	A*	`conf`	Third Workshop on Adversarial Learning Methods for Machine Learning and Data Mining (AdvML 2021). KDD Pin-Yu Chen, Cho-Jui Hsieh, Bo Li, Sijia Liu
2021	—	`conf`	To Supervise or Not to Supervise: How to Effectively Learn Wireless Interference Management Models? SPAWC Bingqing Song, Haoran Sun, Wenqiang Pu, Sijia Liu, Mingyi Hong
2021	J	`jnl`	To Supervise or Not: How to Effectively Learn Wireless Interference Management Models? CoRR Bingqing Song, Haoran Sun, Wenqiang Pu, Sijia Liu, Mingyi Hong
2021	J	`jnl`	When Does Contrastive Learning Preserve Adversarial Robustness from Pretraining to Finetuning? CoRR Lijie Fan, Sijia Liu, Pin-Yu Chen, Gaoyuan Zhang, Chuang Gan
2021	A*	`conf`	When does Contrastive Learning Preserve Adversarial Robustness from Pretraining to Finetuning? NeurIPS Lijie Fan, Sijia Liu, Pin-Yu Chen, Gaoyuan Zhang, Chuang Gan
2021	J	`jnl`	Why Lottery Ticket Wins? A Theoretical Perspective of Sample Complexity on Pruned Neural Networks. CoRR Shuai Zhang, Meng Wang, Sijia Liu, Pin-Yu Chen, Jinjun Xiong
2021	A*	`conf`	Why Lottery Ticket Wins? A Theoretical Perspective of Sample Complexity on Sparse Neural Networks. NeurIPS Shuai Zhang, Meng Wang, Sijia Liu, Pin-Yu Chen, Jinjun Xiong
2020	J	`jnl`	6.7ms on Mobile with over 78% ImageNet Accuracy: Unified Network Pruning and Architecture Search for Beyond Real-Time Mobile Acceleration. CoRR Zhengang Li, Geng Yuan, Wei Niu, Yanyu Li, Pu Zhao, Yuxuan Cai, Xuan Shen, Zheng Zhan, Zhenglun Kong, Qing Jin, Zhiyu Chen, Sijia Liu, Kaiyuan Yang, Bin Ren, Yanzhi Wang, Xue Lin
2020	J	`jnl`	A Primer on Zeroth-Order Optimization in Signal Processing and Machine Learning. CoRR Sijia Liu, Pin-Yu Chen, Bhavya Kailkhura, Gaoyuan Zhang, Alfred O. Hero III, Pramod K. Varshney
2020	J	`jnl`	A Primer on Zeroth-Order Optimization in Signal Processing and Machine Learning: Principals, Recent Advances, and Applications. IEEE Signal Process. Mag. Sijia Liu, Pin-Yu Chen, Bhavya Kailkhura, Gaoyuan Zhang, Alfred O. Hero III, Pramod K. Varshney
2020	J	`jnl`	Achieving Real-Time Execution of Transformer-based Large-scale Models on Mobile with Compiler-aware Neural Architecture Optimization. CoRR Wei Niu, Zhenglun Kong, Geng Yuan, Weiwen Jiang, Jiexiong Guan, Caiwen Ding, Pu Zhao, Sijia Liu, Bin Ren, Yanzhi Wang
2020	J	`jnl`	Achieving Real-Time LiDAR 3D Object Detection on a Mobile Device. CoRR Pu Zhao, Wei Niu, Geng Yuan, Yuxuan Cai, Hsin-Hsuan Sung, Wujie Wen, Sijia Liu, Xipeng Shen, Bin Ren, Yanzhi Wang, Xue Lin
2020	A*	`conf`	Adversarial Robustness: From Self-Supervised Pre-Training to Fine-Tuning. CVPR Tianlong Chen, Sijia Liu, Shiyu Chang, Yu Cheng, Lisa Amini, Zhangyang Wang
2020	J	`jnl`	Adversarial Robustness: From Self-Supervised Pre-Training to Fine-Tuning. CoRR Tianlong Chen, Sijia Liu, Shiyu Chang, Yu Cheng, Lisa Amini, Zhangyang Wang
2020	—	`conf`	Adversarial T-Shirt! Evading Person Detectors in a Physical World. ECCV (5) Kaidi Xu, Gaoyuan Zhang, Sijia Liu, Quanfu Fan, Mengshu Sun, Hongge Chen, Pin-Yu Chen, Yanzhi Wang, Xue Lin
2020	A*	`conf`	An ADMM Based Framework for AutoML Pipeline Configuration. AAAI Sijia Liu, Parikshit Ram, Deepak Vijaykeerthy, Djallel Bouneffouf, Gregory Bramble, Horst Samulowitz, Dakuo Wang, Andrew Conn, Alexander G. Gray
2020	—	`conf`	An Image Enhancing Pattern-Based Sparsity for Real-Time Inference on Mobile Devices. ECCV (13) Xiaolong Ma, Wei Niu, Tianyun Zhang, Sijia Liu, Sheng Lin, Hongjia Li, Wujie Wen, Xiang Chen, Jian Tang, Kaisheng Ma, Bin Ren, Yanzhi Wang
2020	J	`jnl`	An Image Enhancing Pattern-based Sparsity for Real-time Inference on Mobile Devices. CoRR Xiaolong Ma, Wei Niu, Tianyun Zhang, Sijia Liu, Fu-Ming Guo, Sheng Lin, Hongjia Li, Xiang Chen, Jian Tang, Kaisheng Ma, Bin Ren, Yanzhi Wang
2020	—	`conf`	AutoAI: Automating the End-to-End AI Lifecycle with Humans-in-the-Loop. IUI Companion Dakuo Wang, Parikshit Ram, Daniel Karl I. Weidele, Sijia Liu, Michael J. Muller, Justin D. Weisz, Abel N. Valente, Arunima Chaudhary, Dustin Ramsey Torres, Horst Samulowitz, Lisa Amini
2020	J	`jnl`	Can 3D Adversarial Logos Cloak Humans? CoRR Tianlong Chen, Yi Wang, Jingyang Zhou, Sijia Liu, Shiyu Chang, Chandrajit Bajaj, Zhangyang Wang
2020	Misc	`conf`	Decentralized Min-Max Optimization: Formulations, Algorithms and Applications in Network Poisoning Attack. ICASSP Ioannis C. Tsaknakis, Mingyi Hong, Sijia Liu
2020	J	`jnl`	Defending against Backdoor Attack on Deep Neural Networks. CoRR Hao Cheng, Kaidi Xu, Sijia Liu, Pin-Yu Chen, Pu Zhao, Xue Lin
2020	A*	`conf`	Fast Learning of Graph Neural Networks with Guaranteed Generalizability: One-hidden-layer Case. ICML Shuai Zhang, Meng Wang, Sijia Liu, Pin-Yu Chen, Jinjun Xiong
2020	J	`jnl`	Fast Learning of Graph Neural Networks with Guaranteed Generalizability: One-hidden-layer Case. CoRR Shuai Zhang, Meng Wang, Sijia Liu, Pin-Yu Chen, Jinjun Xiong
2020	Misc	`conf`	Guaranteed Convergence of Training Convolutional Neural Networks via Accelerated Gradient Descent. CISS Shuai Zhang, Meng Wang, Sijia Liu, Pin-Yu Chen, Jinjun Xiong
2020	A*	`conf`	Higher-Order Certification For Randomized Smoothing. NeurIPS Jeet Mohapatra, Ching-Yun Ko, Tsui-Wei Weng, Pin-Yu Chen, Sijia Liu, Luca Daniel
2020	J	`jnl`	Higher-Order Certification for Randomized Smoothing. CoRR Jeet Mohapatra, Ching-Yun Ko, Tsui-Wei Weng, Pin-Yu Chen, Sijia Liu, Luca Daniel
2020	A*	`conf`	Is There a Trade-Off Between Fairness and Accuracy? A Perspective Using Mismatched Hypothesis Testing. ICML Sanghamitra Dutta, Dennis Wei, Hazar Yueksel, Pin-Yu Chen, Sijia Liu, Kush R. Varshney
2020	J	`jnl`	Learned Fine-Tuner for Incongruous Few-Shot Learning. CoRR Pu Zhao, Sijia Liu, Parikshit Ram, Songtao Lu, Djallel Bouneffouf, Xue Lin
2020	A*	`conf`	Min-Max Optimization without Gradients: Convergence and Applications to Black-Box Evasion and Poisoning Attacks. ICML Sijia Liu, Songtao Lu, Xiangyi Chen, Yao Feng, Kaidi Xu, Abdullah Al-Dujaili, Mingyi Hong, Una-May O'Reilly
2020	—	`conf`	Practical Detection of Trojan Neural Networks: Data-Limited and Data-Free Cases. ECCV (23) Ren Wang, Gaoyuan Zhang, Sijia Liu, Pin-Yu Chen, Jinjun Xiong, Meng Wang
2020	J	`jnl`	Practical Detection of Trojan Neural Networks: Data-Limited and Data-Free Cases. CoRR Ren Wang, Gaoyuan Zhang, Sijia Liu, Pin-Yu Chen, Jinjun Xiong, Meng Wang
2020	J	`jnl`	Privacy-Preserving Energy Scheduling for Smart Grid With Renewables. IEEE Access Kai Yang, Libin Jiang, Steven H. Low, Sijia Liu
2020	A*	`conf`	Proper Network Interpretability Helps Adversarial Robustness in Classification. ICML Akhilan Boopathy, Sijia Liu, Gaoyuan Zhang, Cynthia Liu, Pin-Yu Chen, Shiyu Chang, Luca Daniel
2020	J	`jnl`	Proper Network Interpretability Helps Adversarial Robustness in Classification. CoRR Akhilan Boopathy, Sijia Liu, Gaoyuan Zhang, Cynthia Liu, Pin-Yu Chen, Shiyu Chang, Luca Daniel
2020	J	`jnl`	Rethinking Randomized Smoothing for Adversarial Robustness. CoRR Jeet Mohapatra, Ching-Yun Ko, Tsui-Wei Weng, Sijia Liu, Pin-Yu Chen, Luca Daniel
2020	J	`jnl`	SS-Auto: A Single-Shot, Automatic Structured Weight Pruning Framework of DNNs with Ultra-High Efficiency. CoRR Zhengang Li, Yifan Gong, Xiaolong Ma, Sijia Liu, Mengshu Sun, Zheng Zhan, Zhenglun Kong, Geng Yuan, Yanzhi Wang
2020	J	`jnl`	Self-Progressing Robust Training. CoRR Minhao Cheng, Pin-Yu Chen, Sijia Liu, Shiyu Chang, Cho-Jui Hsieh, Payel Das
2020	A*	`conf`	Sign-OPT: A Query-Efficient Hard-label Adversarial Attack. ICLR Minhao Cheng, Simranjit Singh, Patrick H. Chen, Pin-Yu Chen, Sijia Liu, Cho-Jui Hsieh
2020	J	`jnl`	Solving Constrained CASH Problems with ADMM. CoRR Parikshit Ram, Sijia Liu, Deepak Vijaykeerthy, Dakuo Wang, Djallel Bouneffouf, Gregory Bramble, Horst Samulowitz, Alexander G. Gray
2020	B	`conf`	Survey on Automated End-to-End Data Science? IJCNN Djallel Bouneffouf, Charu C. Aggarwal, Thanh Hoang, Udayan Khurana, Horst Samulowitz, Beat Buesser, Sijia Liu, Tejaswini Pedapati, Parikshit Ram, Ambrish Rawat, Martin Wistuba, Alexander G. Gray
2020	A*	`conf`	The Lottery Ticket Hypothesis for Pre-trained BERT Networks. NeurIPS Tianlong Chen, Jonathan Frankle, Shiyu Chang, Sijia Liu, Yang Zhang, Zhangyang Wang, Michael Carbin
2020	J	`jnl`	The Lottery Ticket Hypothesis for Pre-trained BERT Networks. CoRR Tianlong Chen, Jonathan Frankle, Shiyu Chang, Sijia Liu, Yang Zhang, Zhangyang Wang, Michael Carbin
2020	J	`jnl`	The Lottery Tickets Hypothesis for Supervised and Self-supervised Pre-training in Computer Vision Models. CoRR Tianlong Chen, Jonathan Frankle, Shiyu Chang, Sijia Liu, Yang Zhang, Michael Carbin, Zhangyang Wang
2020	J	`jnl`	TimeAutoML: Autonomous Representation Learning for Multivariate Irregularly Sampled Time Series. CoRR Yang Jiao, Kai Yang, Shaoyu Dou, Pan Luo, Sijia Liu, Dongjin Song
2020	A*	`conf`	Towards Certificated Model Robustness Against Weight Perturbations. AAAI Tsui-Wei Weng, Pu Zhao, Sijia Liu, Pin-Yu Chen, Xue Lin, Luca Daniel
2020	A*	`conf`	Towards Verifying Robustness of Neural Networks Against A Family of Semantic Perturbations. CVPR Jeet Mohapatra, Tsui-Wei Weng, Pin-Yu Chen, Sijia Liu, Luca Daniel
2020	Misc	`conf`	Towards an Efficient and General Framework of Robust Training for Graph Neural Networks. ICASSP Kaidi Xu, Sijia Liu, Pin-Yu Chen, Mengshu Sun, Caiwen Ding, Bhavya Kailkhura, Xue Lin
2020	J	`jnl`	Towards an Efficient and General Framework of Robust Training for Graph Neural Networks. CoRR Kaidi Xu, Sijia Liu, Pin-Yu Chen, Mengshu Sun, Caiwen Ding, Bhavya Kailkhura, Xue Lin
2020	A*	`conf`	Training Stronger Baselines for Learning to Optimize. NeurIPS Tianlong Chen, Weiyi Zhang, Jingyang Zhou, Shiyu Chang, Sijia Liu, Lisa Amini, Zhangyang Wang
2020	J	`jnl`	Training Stronger Baselines for Learning to Optimize. CoRR Tianlong Chen, Weiyi Zhang, Jingyang Zhou, Shiyu Chang, Sijia Liu, Lisa Amini, Zhangyang Wang
2020	J	`jnl`	Zeroth-Order Hybrid Gradient Descent: Towards A Principled Black-Box Optimization Framework. CoRR Pranay Sharma, Kaidi Xu, Sijia Liu, Pin-Yu Chen, Xue Lin, Pramod K. Varshney
2019	—	`conf`	ADMM attack: an enhanced adversarial attack for deep neural networks with undetectable distortions. ASP-DAC Pu Zhao, Kaidi Xu, Sijia Liu, Yanzhi Wang, Xue Lin
2019	A*	`conf`	Adversarial Robustness vs. Model Compression, or Both? ICCV Shaokai Ye, Xue Lin, Kaidi Xu, Sijia Liu, Hao Cheng, Jan-Henrik Lambrechts, Huan Zhang, Aojun Zhou, Kaisheng Ma, Yanzhi Wang
2019	J	`jnl`	An Information-Theoretic Perspective on the Relationship Between Fairness and Accuracy. CoRR Sanghamitra Dutta, Dennis Wei, Hazar Yueksel, Pin-Yu Chen, Sijia Liu, Kush R. Varshney
2019	A*	`conf`	AutoZOOM: Autoencoder-Based Zeroth Order Optimization Method for Attacking Black-Box Neural Networks. AAAI Chun-Chen Tu, Pai-Shun Ting, Pin-Yu Chen, Sijia Liu, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh, Shin-Ming Cheng
2019	J	`jnl`	Automated Machine Learning via ADMM. CoRR Sijia Liu, Parikshit Ram, Djallel Bouneffouf, Gregory Bramble, Andrew R. Conn, Horst Samulowitz, Alexander G. Gray
2019	J	`jnl`	Beyond Adversarial Training: Min-Max Optimization in Adversarial Attack and Defense. CoRR Jingkang Wang, Tianyun Zhang, Sijia Liu, Pin-Yu Chen, Jiacen Xu, Makan Fardad, Bo Li
2019	A*	`conf`	CNN-Cert: An Efficient Framework for Certifying Robustness of Convolutional Neural Networks. AAAI Akhilan Boopathy, Tsui-Wei Weng, Pin-Yu Chen, Sijia Liu, Luca Daniel
2019	J	`jnl`	Evading Real-Time Person Detectors by Adversarial T-shirt. CoRR Kaidi Xu, Gaoyuan Zhang, Sijia Liu, Quanfu Fan, Mengshu Sun, Hongge Chen, Pin-Yu Chen, Yanzhi Wang, Xue Lin
2019	A*	`conf`	Fast Incremental von Neumann Graph Entropy Computation: Theory, Algorithm, and Applications. ICML Pin-Yu Chen, Lingfei Wu, Sijia Liu, Indika Rajapakse
2019	A*	`conf`	Generation of Low Distortion Adversarial Attacks via Convex Programming. ICDM Tianyun Zhang, Sijia Liu, Yanzhi Wang, Makan Fardad
2019	J	`jnl`	Guest Editorial Special Issue on AI Enabled Cognitive Communication and Networking for IoT. IEEE Internet Things J. Kai Yang, Sijia Liu, Lin Cai, Yasin Yilmaz, Pin-Yu Chen, Anwar Walid
2019	J	`jnl`	How can AI Automate End-to-End Data Science? CoRR Charu C. Aggarwal, Djallel Bouneffouf, Horst Samulowitz, Beat Buesser, Thanh Hoang, Udayan Khurana, Sijia Liu, Tejaswini Pedapati, Parikshit Ram, Ambrish Rawat, Martin Wistuba, Alexander G. Gray
2019	J	`jnl`	Interpreting Adversarial Examples by Activation Promotion and Suppression. CoRR Kaidi Xu, Sijia Liu, Gaoyuan Zhang, Mengshu Sun, Pu Zhao, Quanfu Fan, Chuang Gan, Xue Lin
2019	Misc	`conf`	Latent Heterogeneous Multilayer Community Detection. ICASSP Hafiz Tiomoko Ali, Sijia Liu, Yasin Yilmaz, Romain Couillet, Indika Rajapakse, Alfred O. Hero III
2019	J	`jnl`	Min-Max Optimization without Gradients: Convergence and Applications to Adversarial ML. CoRR Sijia Liu, Songtao Lu, Xiangyi Chen, Yao Feng, Kaidi Xu, Abdullah Al-Dujaili, Mingyi Hong, Una-May O'Reilly
2019	—	`conf`	On the Convergence of A Class of Adam-Type Algorithms for Non-Convex Optimization. ICLR (Poster) Xiangyi Chen, Sijia Liu, Ruoyu Sun, Mingyi Hong
2019	A*	`conf`	On the Design of Black-Box Adversarial Examples by Leveraging Gradient-Free Optimization and Operator Splitting Method. ICCV Pu Zhao, Sijia Liu, Pin-Yu Chen, Nghia Hoang, Kaidi Xu, Bhavya Kailkhura, Xue Lin
2019	J	`jnl`	On the Design of Black-box Adversarial Examples by Leveraging Gradient-free Optimization and Operator Splitting Method. CoRR Pu Zhao, Sijia Liu, Pin-Yu Chen, Nghia Hoang, Kaidi Xu, Bhavya Kailkhura, Xue Lin
2019	J	`jnl`	Progressive DNN Compression: A Key to Achieve Ultra-High Weight Pruning and Quantization Rates using ADMM. CoRR Shaokai Ye, Xiaoyu Feng, Tianyun Zhang, Xiaolong Ma, Sheng Lin, Zhengang Li, Kaidi Xu, Wujie Wen, Sijia Liu, Jian Tang, Makan Fardad, Xue Lin, Yongpan Liu, Yanzhi Wang
2019	A*	`conf`	Recent Progress in Zeroth Order Optimization and Its Applications to Adversarial Robustness in Data Mining and Machine Learning. KDD Pin-Yu Chen, Sijia Liu
2019	J	`jnl`	Reweighted Proximal Pruning for Large-Scale Language Representation. CoRR Fu-Ming Guo, Sijia Liu, Finlay S. Mungall, Xue Lin, Yanzhi Wang
2019	J	`jnl`	Second Rethinking of Network Pruning in the Adversarial Setting. CoRR Shaokai Ye, Kaidi Xu, Sijia Liu, Hao Cheng, Jan-Henrik Lambrechts, Huan Zhang, Aojun Zhou, Kaisheng Ma, Yanzhi Wang, Xue Lin
2019	J	`jnl`	Sign-OPT: A Query-Efficient Hard-label Adversarial Attack. CoRR Minhao Cheng, Simranjit Singh, Patrick H. Chen, Pin-Yu Chen, Sijia Liu, Cho-Jui Hsieh
2019	—	`conf`	Structured Adversarial Attack: Towards General Implementation and Better Interpretability. ICLR (Poster) Kaidi Xu, Sijia Liu, Pu Zhao, Pin-Yu Chen, Huan Zhang, Quanfu Fan, Deniz Erdogmus, Yanzhi Wang, Xue Lin
2019	A*	`conf`	Topology Attack and Defense for Graph Neural Networks: An Optimization Perspective. IJCAI Kaidi Xu, Hongge Chen, Sijia Liu, Pin-Yu Chen, Tsui-Wei Weng, Mingyi Hong, Xue Lin
2019	J	`jnl`	Topology Attack and Defense for Graph Neural Networks: An Optimization Perspective. CoRR Kaidi Xu, Hongge Chen, Sijia Liu, Pin-Yu Chen, Tsui-Wei Weng, Mingyi Hong, Xue Lin
2019	J	`jnl`	Towards Verifying Robustness of Neural Networks Against Semantic Perturbations. CoRR Jeet Mohapatra, Tsui-Wei Weng, Pin-Yu Chen, Sijia Liu, Luca Daniel
2019	A*	`conf`	ZO-AdaMM: Zeroth-Order Adaptive Momentum Method for Black-Box Optimization. NeurIPS Xiangyi Chen, Sijia Liu, Kaidi Xu, Xingguo Li, Xue Lin, Mingyi Hong, David D. Cox
2019	J	`jnl`	ZO-AdaMM: Zeroth-Order Adaptive Momentum Method for Black-Box Optimization. CoRR Xiangyi Chen, Sijia Liu, Kaidi Xu, Xingguo Li, Xue Lin, Mingyi Hong, David D. Cox
2019	—	`conf`	signSGD via Zeroth-Order Oracle. ICLR (Poster) Sijia Liu, Pin-Yu Chen, Xiangyi Chen, Mingyi Hong
2018	J	`jnl`	A Unified Framework of DNN Weight Pruning and Weight Clustering/Quantization Using ADMM. CoRR Shaokai Ye, Tianyun Zhang, Kaiqi Zhang, Jiayu Li, Jiaming Xie, Yun Liang, Sijia Liu, Xue Lin, Yanzhi Wang
2018	J	`jnl`	Accelerated Distributed Dual Averaging Over Evolving Networks of Growing Connectivity. IEEE Trans. Signal Process. Sijia Liu, Pin-Yu Chen, Alfred O. Hero III
2018	J	`jnl`	Algorithm-Hardware Co-Optimization of the Memristor-Based Framework for Solving SOCP and Homogeneous QCQP Problems. CoRR Ao Ren, Sijia Liu, Ruizhe Cai, Wujie Wen, Pramod K. Varshney, Yanzhi Wang
2018	A*	`conf`	An ADMM-Based Universal Framework for Adversarial Attacks on Deep Neural Networks. ACM Multimedia Pu Zhao, Sijia Liu, Yanzhi Wang, Xue Lin
2018	J	`jnl`	An ADMM-Based Universal Framework for Adversarial Attacks on Deep Neural Networks. CoRR Pu Zhao, Sijia Liu, Yanzhi Wang, Xue Lin
2018	J	`jnl`	AutoZOOM: Autoencoder-based Zeroth Order Optimization Method for Attacking Black-box Neural Networks. CoRR Chun-Chen Tu, Pai-Shun Ting, Pin-Yu Chen, Sijia Liu, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh, Shin-Ming Cheng
2018	J	`jnl`	CNN-Cert: An Efficient Framework for Certifying Robustness of Convolutional Neural Networks. CoRR Akhilan Boopathy, Tsui-Wei Weng, Pin-Yu Chen, Sijia Liu, Luca Daniel
2018	J	`jnl`	Fast Incremental von Neumann Graph Entropy Computation: Theory, Algorithm, and Applications. CoRR Pin-Yu Chen, Lingfei Wu, Sijia Liu, Indika Rajapakse
2018	Misc	`conf`	First-Order Bifurcation Detection for Dynamic Complex Networks. ICASSP Sijia Liu, Pin-Yu Chen, Indika Rajapakse, Alfred O. Hero III
2018	J	`jnl`	Is Ordered Weighted ℓ CoRR Pin-Yu Chen, Bhanukiran Vinzamuri, Sijia Liu
2018	—	`conf`	Is Ordered Weighted ℓ1 Regularized Regression Robust to Adversarial Perturbation? A Case Study on OSCAR. GlobalSIP Pin-Yu Chen, Bhanukiran Vinzamuri, Sijia Liu
2018	J	`jnl`	Latent heterogeneous multilayer community detection. CoRR Hafiz Tiomoko Ali, Sijia Liu, Yasin Yilmaz, Alfred O. Hero III, Romain Couillet, Indika Rajapakse
2018	—	`conf`	Multi-Layer Relevance Networks. SPAWC Brandon Oselio, Sijia Liu, Alfred O. Hero III
2018	J	`jnl`	On the Convergence of A Class of Adam-Type Algorithms for Non-Convex Optimization. CoRR Xiangyi Chen, Sijia Liu, Ruoyu Sun, Mingyi Hong
2018	J	`jnl`	Optimal Sensor Collaboration for Parameter Tracking Using Energy Harvesting Sensors. IEEE Trans. Signal Process. Shan Zhang, Sijia Liu, Vinod Sharma, Pramod K. Varshney
2018	J	`jnl`	Progressive Weight Pruning of Deep Neural Networks using ADMM. CoRR Shaokai Ye, Tianyun Zhang, Kaiqi Zhang, Jiayu Li, Kaidi Xu, Yunfei Yang, Fuxun Yu, Jian Tang, Makan Fardad, Sijia Liu, Xiang Chen, Xue Lin, Yanzhi Wang
2018	J	`jnl`	Structured Adversarial Attack: Towards General Implementation and Better Interpretability. CoRR Kaidi Xu, Sijia Liu, Pu Zhao, Pin-Yu Chen, Huan Zhang, Deniz Erdogmus, Yanzhi Wang, Xue Lin
2018	Misc	`conf`	Zeroth-Order Diffusion Adaptation Over Networks. ICASSP Jie Chen, Sijia Liu, Pin-Yu Chen
2018	A	`conf`	Zeroth-Order Online Alternating Direction Method of Multipliers: Convergence Analysis and Applications. AISTATS Sijia Liu, Jie Chen, Pin-Yu Chen, Alfred O. Hero III
2018	—	`conf`	Zeroth-Order Stochastic Projected Gradient Descent for Nonconvex Optimization. GlobalSIP Sijia Liu, Xingguo Li, Pin-Yu Chen, Jarvis D. Haupt, Lisa Amini
2018	A*	`conf`	Zeroth-Order Stochastic Variance Reduction for Nonconvex Optimization. NeurIPS Sijia Liu, Bhavya Kailkhura, Pin-Yu Chen, Pai-Shun Ting, Shiyu Chang, Lisa Amini
2018	J	`jnl`	Zeroth-Order Stochastic Variance Reduction for Nonconvex Optimization. CoRR Sijia Liu, Bhavya Kailkhura, Pin-Yu Chen, Pai-Shun Ting, Shiyu Chang, Lisa Amini
2017	J	`jnl`	A Data-Driven Sparse-Learning Approach to Model Reduction in Chemical Reaction Networks. CoRR Farshad Harirchi, Omar A. Khalil, Sijia Liu, Paolo Elvati, Angela Violi, Alfred O. Hero III
2017	J	`jnl`	A Memristor-Based Optimization Framework for AI Applications. CoRR Sijia Liu, Yanzhi Wang, Makan Fardad, Pramod K. Varshney
2017	—	`conf`	Algorithm-hardware co-optimization of the memristor-based framework for solving SOCP and homogeneous QCQP problems. ASP-DAC Ao Ren, Sijia Liu, Ruizhe Cai, Wujie Wen, Pramod K. Varshney, Yanzhi Wang
2017	J	`jnl`	Bias-Variance Tradeoff of Graph Laplacian Regularizer. CoRR Pin-Yu Chen, Sijia Liu
2017	J	`jnl`	Bias-Variance Tradeoff of Graph Laplacian Regularizer. IEEE Signal Process. Lett. Pin-Yu Chen, Sijia Liu
2017	Misc	`conf`	Distributed optimization for evolving networks of growing connectivity. ICASSP Sijia Liu, Pin-Yu Chen, Alfred O. Hero III
2017	Misc	`conf`	Distributed sensor selection for field estimation. ICASSP Sijia Liu, Sundeep Prabhakar Chepuri, Geert Leus, Alfred O. Hero III
2017	Misc	`conf`	Learning sparse graphs under smoothness prior. ICASSP Sundeep Prabhakar Chepuri, Sijia Liu, Geert Leus, Alfred O. Hero III
2017	J	`jnl`	Model Reduction in Chemical Reaction Networks: A Data-Driven Sparse-Learning Approach. CoRR Omar A. Khalil, Farshad Harirchi, Doohyun Kim, Sijia Liu, Paolo Elvati, Angela Violi, Alfred O. Hero III
2017	—	`conf`	Semiblind subgraph reconstruction in Gaussian graphical models. GlobalSIP Tianpei Xie, Sijia Liu, Alfred O. Hero III
2017	J	`jnl`	Semiblind subgraph reconstruction in Gaussian graphical models. CoRR Tianpei Xie, Sijia Liu, Alfred O. Hero III
2017	Misc	`conf`	Ultra-fast robust compressive sensing based on memristor crossbars. ICASSP Sijia Liu, Ao Ren, Yanzhi Wang, Pramod K. Varshney
2017	J	`jnl`	Zeroth-Order Online Alternating Direction Method of Multipliers: Convergence Analysis and Applications. CoRR Sijia Liu, Jie Chen, Pin-Yu Chen, Alfred O. Hero III
2016	J	`jnl`	Learning Sparse Graphs Under Smoothness Prior. CoRR Sundeep Prabhakar Chepuri, Sijia Liu, Geert Leus, Alfred O. Hero III
2016	J	`jnl`	Measurement Matrix Design for Compressed Detection With Secrecy Guarantees. IEEE Wirel. Commun. Lett. Bhavya Kailkhura, Sijia Liu, Thakshila Wimalajeewa, Pramod K. Varshney
2016	Misc	`conf`	Optimal energy allocation and storage control for distributed estimation with sensor collaboration. CISS Sijia Liu, Yanzhi Wang, Makan Fardad, Pramod K. Varshney
2016	J	`jnl`	Optimized Sensor Collaboration for Estimation of Temporally Correlated Parameters. CoRR Sijia Liu, Swarnendu Kar, Makan Fardad, Pramod K. Varshney
2016	J	`jnl`	Optimized Sensor Collaboration for Estimation of Temporally Correlated Parameters. IEEE Trans. Signal Process. Sijia Liu, Swarnendu Kar, Makan Fardad, Pramod K. Varshney
2016	J	`jnl`	Sensor Selection for Estimation with Correlated Measurement Noise. IEEE Trans. Signal Process. Sijia Liu, Sundeep Prabhakar Chepuri, Makan Fardad, Engin Masazade, Geert Leus, Pramod K. Varshney
2016	—	`conf`	Sensor placement for field estimation via Poisson disk sampling. GlobalSIP Sijia Liu, Nianxia Cao, Pramod K. Varshney
2016	—	`conf`	Towards an online energy allocation policy for distributed estimation with sensor collaboration using energy harvesting sensors. GlobalSIP Sijia Liu, Vinod Sharma, Pramod K. Varshney
2015	—	`conf`	Design of transmit-diversity schemes in detection networks under secrecy constraints. Allerton V. Sriram Siddhardh Nadendla, Sijia Liu, Pramod K. Varshney
2015	Misc	`conf`	Joint sparsity pattern recovery with 1-bit compressive sensing in sensor networks. ACSSC Vipul Gupta, Bhavya Kailkhura, Thakshila Wimalajeewa, Sijia Liu, Pramod K. Varshney
2015	J	`jnl`	Measurement Matrix Design for Compressive Detection with Secrecy Guarantees. CoRR Bhavya Kailkhura, Sijia Liu, Thakshila Wimalajeewa, Pramod K. Varshney
2015	Misc	`conf`	On optimal sensor collaboration for distributed estimation with individual power constraints. ACSSC Sijia Liu, Swarnendu Kar, Makan Fardad, Pramod K. Varshney
2015	Misc	`conf`	Sensor selection with correlated measurements for target tracking in wireless sensor networks. ICASSP Sijia Liu, Engin Masazade, Makan Fardad, Pramod K. Varshney
2015	J	`jnl`	Sparsity-Aware Sensor Collaboration for Linear Coherent Estimation. IEEE Trans. Signal Process. Sijia Liu, Swarnendu Kar, Makan Fardad, Pramod K. Varshney
2015	C	`conf`	Sparsity-promoting sensor management for estimation: An energy balance point of view. FUSION Sijia Liu, Feishe Chen, Aditya Vempaty, Makan Fardad, Lixin Shen, Pramod K. Varshney
2014	J	`jnl`	Energy-Aware Sensor Selection in Field Reconstruction. IEEE Signal Process. Lett. Sijia Liu, Aditya Vempaty, Makan Fardad, Engin Masazade, Pramod K. Varshney
2014	B	`conf`	On optimal sensor collaboration topologies for linear coherent estimation. ISIT Sijia Liu, Makan Fardad, Swarnendu Kar, Pramod K. Varshney
2014	J	`jnl`	Optimal Periodic Sensor Scheduling in Networks of Dynamical Systems. IEEE Trans. Signal Process. Sijia Liu, Makan Fardad, Pramod K. Varshney, Engin Masazade
2014	J	`jnl`	Sensor selection for nonlinear systems in large sensor networks. IEEE Trans. Aerosp. Electron. Syst. Xiaojing Shen, Sijia Liu, Pramod K. Varshney
2014	J	`jnl`	Sparsity-Aware Sensor Collaboration for Linear Coherent Estimation. CoRR Sijia Liu, Swarnendu Kar, Makan Fardad, Pramod K. Varshney
2014	Misc	`conf`	Sparsity-aware field estimation via ordinary Kriging. ICASSP Sijia Liu, Engin Masazade, Makan Fardad, Pramod K. Varshney
2013	Misc	`conf`	Adaptive non-myopic quantizer design for target tracking in wireless sensor networks. ACSSC Sijia Liu, Engin Masazade, Xiaojing Shen, Pramod K. Varshney
2013	—	`conf`	On optimal periodic sensor scheduling for field estimation in wireless sensor networks. GlobalSIP Sijia Liu, Makan Fardad, Engin Masazade, Pramod K. Varshney
2013	J	`jnl`	Optimal Periodic Sensor Scheduling in Large-Scale Dynamical Networks CoRR Sijia Liu, Makan Fardad, Engin Masazade, Pramod K. Varshney
2012	—	`conf`	Temporally staggered sensing for field estimation with quantized data in wireless sensor networks. SSP Sijia Liu, Engin Masazade, Pramod K. Varshney