Sijia Liu
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
167
Venues
38
Active years
2013–2026
Best venue rank
A*
Where they publish
- A*ICLR21 papers
- MulticonferenceICASSP18 papers
- A*ICML17 papers
- A*AAAI15 papers
- NationalAMIA15 papers
- A*CVPR13 papers
- A*ACL6 papers
- A*ICCV5 papers
- A*ECCV5 papers
- A*EMNLP4 papers
- ANAACL4 papers
- NationalACSSC4 papers
- BASPDAC3 papers
- A*IJCAI3 papers
- A*KDD3 papers
- AAISTATS3 papers
- ACIKM2 papers
- BIJCNN2 papers
- AWACV2 papers
- BSIGdial2 papers
- NationalCISS2 papers
- BPIMRC2 papers
- AEACL1 paper
- AECAI1 paper
- BCCGRID1 paper
- A*CHI1 paper
- A*HRI1 paper
- CICICS1 paper
- BWCNC1 paper
- AUAI1 paper
- ARTAS1 paper
- AIUI1 paper
- AWSDM1 paper
- BCogSci1 paper
- A*ICDM1 paper
- CCIS1 paper
- CFUSION1 paper
- BISIT1 paper
Papers
167 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2026 | AAAI | Robust Learning from Noisily Labeled Long-Tailed Data via Fairness Regularizer. | Jiaheng Wei, Zhaowei Zhu, Gang Niu, Tongliang Liu, Sijia Liu, Masashi Sugiyama, Yang Liu |
| 2026 | ACL | Unlearners Can Lie: Evaluating and Improving Honesty in LLM Unlearning. | Renjie Gu, Jiazhen Du, Yihua Zhang, Sijia Liu |
| 2026 | ACL | ReasonRec: A Reasoning-Augmented Multimodal Agent for Unified Recommendation. | Yihua Zhang, Mingfu Liang, Jiyan Yang, Rong Jin, Wen-Yen Chen, Yiping Han, Huayu Li, Buyun Zhang, Liang Luo, Luke Simon, Sijia Liu, Tianlong Chen, Xi Liu |
| 2026 | EACL | BLUR: A Bi-Level Optimization Approach for LLM Unlearning. | Hadi Reisizadeh, Jinghan Jia, Zhiqi Bu, Bhanukiran Vinzamuri, Anil Ramakrishna, Kai-Wei Chang, Volkan Cevher, Sijia Liu, Mingyi Hong |
| 2025 | AAAI | Visual Prompting Upgrades Neural Network Sparsification: A Data-Model Perspective. | Can Jin, Tianjin Huang, Yihua Zhang, Mykola Pechenizkiy, Sijia Liu, Shiwei Liu, Tianlong Chen |
| 2025 | ACL | SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? | Haomin Zhuang, Yihua Zhang, Kehan Guo, Jinghan Jia, Gaowen Liu, Sijia Liu, Xiangliang Zhang |
| 2025 | CIKM | FROG: Fair Removal on Graph. | Ziheng Chen, Jiali Cheng, Hadi Amiri, Kaushiki Nag, Lu Lin, Sijia Liu, Gabriele Tolomei, Xiangguo Sun |
| 2025 | CVPR | PSBD: Prediction Shift Uncertainty Unlocks Backdoor Detection. | Wei Li, Pin-Yu Chen, Sijia Liu, Ren Wang |
| 2025 | CVPR | 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 |
| 2025 | CVPR | 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 |
| 2025 | ECAI | Overexposed Frame Reconstruction in Ultra-High-Speed Imaging via Event-Guided Diffusion Models. | Han Wang, Sijia Liu, Juntao Wu, Xirui Zhang, Zhou Wang, Xiaofeng Yang, Yaoxiong Wang, Saiao Zhou, Pinguo Cao, Yuman Nie |
| 2025 | EMNLP | Reasoning Model Unlearning: Forgetting Traces, Not Just Answers, While Preserving Reasoning Skills. | Changsheng Wang, Chongyu Fan, Yihua Zhang, Jinghan Jia, Dennis Wei, Parikshit Ram, Nathalie Baracaldo, Sijia Liu |
| 2025 | ICASSP | Pruning then Reweighting: Towards Data-Efficient Training of Diffusion Models. | Yize Li, Yihua Zhang, Sijia Liu, Xue Lin |
| 2025 | ICCV | Invisible Watermarks, Visible Gains: Steering Machine Unlearning with Bi-Level Watermarking Design. | Yuhao Sun, Yihua Zhang, Gaowen Liu, Hongtao Xie, Sijia Liu |
| 2025 | ICLR | 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 |
| 2025 | ICML | 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 |
| 2025 | ICML | 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 |
| 2025 | IJCNN | Federated Unlearning with Oriented Saliency Compression. | Boxu Xiao, Sijia Liu, Qing Ling |
| 2025 | NAACL | Improve Decoding Factuality by Token-wise Cross Layer Entropy of Large Language Models. | Jialiang Wu, Yi Shen, Sijia Liu, Yi Tang, Sen Song, Xiaoyi Wang, Longjun Cai |
| 2025 | WACV | Can Adversarial Examples be Parsed to Reveal Victim Model Information? | Yuguang Yao, Jiancheng Liu, Yifan Gong, Xiaoming Liu, Yanzhi Wang, Xue Lin, Sijia Liu |
| 2024 | ACL | Do Large Language Models have Problem-Solving Capability under Incomplete Information Scenarios? | Yuyan Chen, Yueze Li, Songzhou Yan, Sijia Liu, Jiaqing Liang, Yanghua Xiao |
| 2024 | ACL | EmotionQueen: A Benchmark for Evaluating Empathy of Large Language Models. | Yuyan Chen, Songzhou Yan, Sijia Liu, Yueze Li, Yanghua Xiao |
| 2024 | CCGRID | MDSTGCN : Multi-Scale Dynamic Spatial-Temporal Graph Convolution Network With Edge Feature Embedding for Traffic Forecasting. | Sijia Liu, Hui Xu, Fanyu Meng, Qianqian Ren |
| 2024 | CHI | Virtual Dream Reliving: Exploring Generative AI in Immersive Environment for Dream Re-experiencing. | Pinyao Liu, Alexandra Kitson, Claudia Picard-Deland, Michelle Carr, Sijia Liu, Ray LC, Chen Zhu-Tian |
| 2024 | ECCV | Challenging Forgets: Unveiling the Worst-Case Forget Sets in Machine Unlearning. | Chongyu Fan, Jiancheng Liu, Alfred Olivier Hero, Sijia Liu |
| 2024 | ECCV | 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 |
| 2024 | EMNLP | 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 |
| 2024 | EMNLP | SOUL: Unlocking the Power of Second-Order Optimization for LLM Unlearning. | Jinghan Jia, Yihua Zhang, Yimeng Zhang, Jiancheng Liu, Bharat Runwal, James Diffenderfer, Bhavya Kailkhura, Sijia Liu |
| 2024 | HRI | "Sorry to Keep You Waiting": Recovering from Negative Consequences Resulting from Service Robot Unintended Rejection. | Xiaoyu Chang, Yanheng Li, Sijia Liu, Ling Ma, Ray LC |
| 2024 | ICASSP | The Power of Few: Accelerating and Enhancing Data Reweighting with Coreset Selection. | Mohammad Jafari, Yimeng Zhang, Yihua Zhang, Sijia Liu |
| 2024 | ICASSP | Elevating Visual Prompting in Transfer Learning Via Pruned Model Ensembles: No Retrain, No Pain. | Brian Zhang, Yuguang Yao, Sijia Liu |
| 2024 | ICLR | 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 |
| 2024 | ICLR | 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 |
| 2024 | ICLR | Backdoor Secrets Unveiled: Identifying Backdoor Data with Optimized Scaled Prediction Consistency. | Soumyadeep Pal, Yuguang Yao, Ren Wang, Bingquan Shen, Sijia Liu |
| 2024 | ICML | 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 |
| 2024 | ICML | 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 |
| 2024 | NAACL | Advancing the Robustness of Large Language Models through Self-Denoised Smoothing. | Jiabao Ji, Bairu Hou, Zhen Zhang, Guanhua Zhang, Wenqi Fan, Qing Li, Yang Zhang, Gaowen Liu, Sijia Liu, Shiyu Chang |
| 2024 | NAACL | More Samples or More Prompts? Exploring Effective Few-Shot In-Context Learning for LLMs with In-Context Sampling. | Bingsheng Yao, Guiming Chen, Ruishi Zou, Yuxuan Lu, Jiachen Li, Shao Zhang, Yisi Sang, Sijia Liu, James A. Hendler, Dakuo Wang |
| 2024 | WACV | CryoRL: Reinforcement Learning Enables Efficient Cryo-EM Data Collection. | Quanfu Fan, Yilai Li, Yuguang Yao, John Cohn, Sijia Liu, Ziping Xu, Seychelle M. Vos, Michael A. Cianfrocco |
| 2023 | AAAI | AAAI New Faculty Highlights: General and Scalable Optimization for Robust AI. | Sijia Liu |
| 2023 | AAAI | Holistic Adversarial Robustness of Deep Learning Models. | Pin-Yu Chen, Sijia Liu |
| 2023 | AAAI | 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 |
| 2023 | AAAI | Towards Understanding How Self-training Tolerates Data Backdoor Poisoning. | Soumyadeep Pal, Ren Wang, Yuguang Yao, Sijia Liu |
| 2023 | ACL | PersLEARN: Research Training through the Lens of Perspective Cultivation. | Yu-Zhe Shi, Shiqian Li, Xinyi Niu, Qiao Xu, Jiawen Liu, Yifan Xu, Shiyu Gu, Bingru He, Xinyang Li, Xinyu Zhao, Zijian Zhao, Yidong Lyu, Zhen Li, Sijia Liu, Lin Qiu, Jinhao Ji, Lecheng Ruan, Yuxi Ma, Wenjuan Han, Yixin Zhu |
| 2023 | ASPDAC | Data-Model-Circuit Tri-Design for Ultra-Light Video Intelligence on Edge Devices. | Yimeng Zhang, Akshay Karkal Kamath, Qiucheng Wu, Zhiwen Fan, Wuyang Chen, Zhangyang Wang, Shiyu Chang, Sijia Liu, Cong Hao |
| 2023 | CIKM | AutoSeqRec: Autoencoder for Efficient Sequential Recommendation. | Sijia Liu, Jiahao Liu, Hansu Gu, Dongsheng Li, Tun Lu, Peng Zhang, Ning Gu |
| 2023 | CVPR | Understanding and Improving Visual Prompting: A Label-Mapping Perspective. | Aochuan Chen, Yuguang Yao, Pin-Yu Chen, Yihua Zhang, Sijia Liu |
| 2023 | CVPR | Exploring Diversified Adversarial Robustness in Neural Networks via Robust Mode Connectivity. | Ren Wang, Yuxuan Li, Sijia Liu |
| 2023 | CVPR | Text-Visual Prompting for Efficient 2D Temporal Video Grounding. | Yimeng Zhang, Xin Chen, Jinghan Jia, Sijia Liu, Ke Ding |
| 2023 | CVPR | A Pilot Study of Query-Free Adversarial Attack against Stable Diffusion. | Haomin Zhuang, Yihua Zhang, Sijia Liu |
| 2023 | EMNLP | DialGuide: Aligning Dialogue Model Behavior with Developer Guidelines. | Prakhar Gupta, Yang Liu, Di Jin, Behnam Hedayatnia, Spandana Gella, Sijia Liu, Patrick Lange, Julia Hirschberg, Dilek Hakkani-Tur |
| 2023 | ICASSP | Visual Prompting for Adversarial Robustness. | Aochuan Chen, Peter Lorenz, Yuguang Yao, Pin-Yu Chen, Sijia Liu |
| 2023 | ICASSP | Robustness-Preserving Lifelong Learning Via Dataset Condensation. | Jinghan Jia, Yihua Zhang, Dogyoon Song, Sijia Liu, Alfred O. Hero III |
| 2023 | ICASSP | SMUG: Towards Robust Mri Reconstruction by Smoothed Unrolling. | Hui Li, Jinghan Jia, Shijun Liang, Yuguang Yao, Saiprasad Ravishankar, Sijia Liu |
| 2023 | ICCV | 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 |
| 2023 | ICICS | Block Ciphers Classification Based on Randomness Test Statistic Value via LightGBM. | Sijia Liu, Min Luo, Cong Peng, Debiao He |
| 2023 | ICLR | 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 |
| 2023 | ICLR | TextGrad: Advancing Robustness Evaluation in NLP by Gradient-Driven Optimization. | Bairu Hou, Jinghan Jia, Yihua Zhang, Guanhua Zhang, Yang Zhang, Sijia Liu, Shiyu Chang |
| 2023 | ICLR | A Theoretical Understanding of Shallow Vision Transformers: Learning, Generalization, and Sample Complexity. | Hongkang Li, Meng Wang, Sijia Liu, Pin-Yu Chen |
| 2023 | ICLR | What Is Missing in IRM Training and Evaluation? Challenges and Solutions. | Yihua Zhang, Pranay Sharma, Parikshit Ram, Mingyi Hong, Kush R. Varshney, Sijia Liu |
| 2023 | ICML | 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 |
| 2023 | ICML | Linearly Constrained Bilevel Optimization: A Smoothed Implicit Gradient Approach. | Prashant Khanduri, Ioannis C. Tsaknakis, Yihua Zhang, Jia Liu, Sijia Liu, Jiawei Zhang, Mingyi Hong |
| 2023 | SIGdial | MERCY: Multiple Response Ranking Concurrently in Realistic Open-Domain Conversational Systems. | Sarik Ghazarian, Behnam Hedayatnia, Di Jin, Sijia Liu, Nanyun Peng, Yang Liu, Dilek Hakkani-Tur |
| 2022 | AAAI | Adversarial Examples Can Be Effective Data Augmentation for Unsupervised Machine Learning. | Chia-Yi Hsu, Pin-Yu Chen, Songtao Lu, Sijia Liu, Chia-Mu Yu |
| 2022 | AAAI | Zeroth-Order Optimization for Composite Problems with Functional Constraints. | Zichong Li, Pin-Yu Chen, Sijia Liu, Songtao Lu, Yangyang Xu |
| 2022 | AMIA | Towards User-centered Corpus Development: Lessons Learnt from Designing and Developing MedTator. | Huan He, Sunyang Fu, Liwei Wang, Andrew Wen, Sijia Liu, Sungrim Moon, Kurt Miller, Hongfang Liu |
| 2022 | CVPR | Proactive Image Manipulation Detection. | Vishal Asnani, Xi Yin, Tal Hassner, Sijia Liu, Xiaoming Liu |
| 2022 | CVPR | Quarantine: Sparsity Can Uncover the Trojan Attack Trigger for Free. | Tianlong Chen, Zhenyu Zhang, Yihua Zhang, Shiyu Chang, Sijia Liu, Zhangyang Wang |
| 2022 | ICASSP | When Does Backdoor Attack Succeed in Image Reconstruction? A Study of Heuristics vs. Bi-Level Solution. | Vardaan Taneja, Pin-Yu Chen, Yuguang Yao, Sijia Liu |
| 2022 | ICLR | Reverse Engineering of Imperceptible Adversarial Image Perturbations. | Yifan Gong, Yuguang Yao, Yize Li, Yimeng Zhang, Xiaoming Liu, Xue Lin, Sijia Liu |
| 2022 | ICLR | 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 |
| 2022 | ICLR | Optimizer Amalgamation. | Tianshu Huang, Tianlong Chen, Sijia Liu, Shiyu Chang, Lisa Amini, Zhangyang Wang |
| 2022 | ICLR | Decentralized Learning for Overparameterized Problems: A Multi-Agent Kernel Approximation Approach. | Prashant Khanduri, Haibo Yang, Mingyi Hong, Jia Liu, Hoi-To Wai, Sijia Liu |
| 2022 | ICLR | 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 |
| 2022 | ICML | Data-Efficient Double-Win Lottery Tickets from Robust Pre-training. | Tianlong Chen, Zhenyu Zhang, Sijia Liu, Yang Zhang, Shiyu Chang, Zhangyang Wang |
| 2022 | ICML | Linearity Grafting: Relaxed Neuron Pruning Helps Certifiable Robustness. | Tianlong Chen, Huan Zhang, Zhenyu Zhang, Shiyu Chang, Sijia Liu, Pin-Yu Chen, Zhangyang Wang |
| 2022 | ICML | 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 |
| 2022 | ICML | Generalization Guarantee of Training Graph Convolutional Networks with Graph Topology Sampling. | Hongkang Li, Meng Wang, Sijia Liu, Pin-Yu Chen, Jinjun Xiong |
| 2022 | ICML | 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 |
| 2022 | IJCAI | Learning to Generate Image Source-Agnostic Universal Adversarial Perturbations. | Pu Zhao, Parikshit Ram, Songtao Lu, Yuguang Yao, Djallel Bouneffouf, Xue Lin, Sijia Liu |
| 2022 | KDD | The Fourth Workshop on Adversarial Learning Methods for Machine Learning and Data Mining (AdvML 2022). | Pin-Yu Chen, Cho-Jui Hsieh, Bo Li, Sijia Liu |
| 2022 | NAACL | A Word is Worth A Thousand Dollars: Adversarial Attack on Tweets Fools Stock Prediction. | Yong Xie, Dakuo Wang, Pin-Yu Chen, Jinjun Xiong, Sijia Liu, Oluwasanmi Koyejo |
| 2022 | WCNC | Co-Optimizing Latency and Energy with Learning Based 360° Video Edge Caching Policy. | Zhendong Yu, Jiayi Liu, Sijia Liu, Qinghai Yang |
| 2022 | UAI | 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 |
| 2022 | SIGdial | Improving Bot Response Contradiction Detection via Utterance Rewriting. | Di Jin, Sijia Liu, Yang Liu, Dilek Hakkani-Tur |
| 2021 | AAAI | Fast Training of Provably Robust Neural Networks by SingleProp. | Akhilan Boopathy, Lily Weng, Sijia Liu, Pin-Yu Chen, Gaoyuan Zhang, Luca Daniel |
| 2021 | AAAI | Self-Progressing Robust Training. | Minhao Cheng, Pin-Yu Chen, Sijia Liu, Shiyu Chang, Cho-Jui Hsieh, Payel Das |
| 2021 | AAAI | 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 |
| 2021 | ACSSC | Instabilities in Conventional Multi-Coil MRI Reconstruction with Small Adversarial Perturbations. | Chi Zhang, Jinghan Jia, Burhaneddin Yaman, Steen Moeller, Sijia Liu, Mingyi Hong, Mehmet Akakaya |
| 2021 | AISTATS | Rate-improved inexact augmented Lagrangian method for constrained nonconvex optimization. | Zichong Li, Pin-Yu Chen, Sijia Liu, Songtao Lu, Yangyang Xu |
| 2021 | AISTATS | Hidden Cost of Randomized Smoothing. | Jeet Mohapatra, Ching-Yun Ko, Lily Weng, Pin-Yu Chen, Sijia Liu, Luca Daniel |
| 2021 | AMIA | Patient Asynchronous Response to Coronavirus Disease 2019 (COVID-19): A Retrospective Analysis of Patient Portal Messages. | Ming Huang, Aditya Khurana, George M. Mastorakos, Andrew Wen, Huan He, Liwei Wang, Sijia Liu, Yanshan Wang, Julie E. Prigge, Brian Costello, Nilay D. Shah, Henry Ting, Christi A. Patten, Jungwei Fan, Hongfang Liu |
| 2021 | AMIA | Disparity analysis of patient portal messaging use for COVID-19 in urban versus rural locality. | Ming Huang, Andrew Wen, Huan He, Liwei Wang, Sijia Liu, Yanshan Wang, Nansu Zong, Yue Yu, Julie E. Prigge, Brian Costello, Nilay D. Shah, Henry Ting, Chyke Doubeni, Jungwei Fan, Hongfang Liu, Christi A. Patten |
| 2021 | AMIA | FHIRTime: Standardizing Temporal Patterns Identified from Clinical Narratives Using HL7 FHIR. | Daniel J. Stone, Sijia Liu, Yuan Luo, Andrew Wen, Nansu Zong, Luke V. Rasmussen, Prakash Adekkanattu, Pascal S. Brandt, Jennifer A. Pacheco, Fei Wang, Cui Tao, Jyotishman Pathak, Hongfang Liu, Guoqian Jiang |
| 2021 | AMIA | On Constraints and Considerations for Extending Support for Natural Language Processing-Based FHIR Resource Generation. | Andrew Wen, Luke V. Rasmussen, Daniel J. Stone, Sijia Liu, Prakash Adekkanattu, Pascal S. Brandt, Jennifer A. Pacheco, Yuan Luo, Fei Wang, Jyotishman Pathak, Hongfang Liu, Guoqian Jiang |
| 2021 | CVPR | 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 |
| 2021 | CVPR | 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 |
| 2021 | ICCV | 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 |
| 2021 | ICLR | 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 |
| 2021 | ICLR | Robust Overfitting may be mitigated by properly learned smoothening. | Tianlong Chen, Zhenyu Zhang, Sijia Liu, Shiyu Chang, Zhangyang Wang |
| 2021 | ICLR | Long Live the Lottery: The Existence of Winning Tickets in Lifelong Learning. | Tianlong Chen, Zhenyu Zhang, Sijia Liu, Shiyu Chang, Zhangyang Wang |
| 2021 | ICLR | Generating Adversarial Computer Programs using Optimized Obfuscations. | Shashank Srikant, Sijia Liu, Tamara Mitrovska, Shiyu Chang, Quanfu Fan, Gaoyuan Zhang, Una-May O'Reilly |
| 2021 | ICML | 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 |
| 2021 | IJCAI | 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 |
| 2021 | KDD | Third Workshop on Adversarial Learning Methods for Machine Learning and Data Mining (AdvML 2021). | Pin-Yu Chen, Cho-Jui Hsieh, Bo Li, Sijia Liu |
| 2021 | RTAS | Brief Industry Paper: Towards Real-Time 3D Object Detection for Autonomous Vehicles with Pruning Search. | Pu Zhao, Wei Niu, Geng Yuan, Yuxuan Cai, Hsin-Hsuan Sung, Shaoshan Liu, Sijia Liu, Xipeng Shen, Bin Ren, Yanzhi Wang, Xue Lin |
| 2020 | AAAI | 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 |
| 2020 | AAAI | Towards Certificated Model Robustness Against Weight Perturbations. | Tsui-Wei Weng, Pu Zhao, Sijia Liu, Pin-Yu Chen, Xue Lin, Luca Daniel |
| 2020 | AMIA | Predicting Section Location of Clinical Sentences using BERT Encoder - A Pilot Study. | Sijia Liu, Sunyang Fu, Sungrim Moon, Andrew Wen, Hongfang Liu |
| 2020 | CISS | Guaranteed Convergence of Training Convolutional Neural Networks via Accelerated Gradient Descent. | Shuai Zhang, Meng Wang, Sijia Liu, Pin-Yu Chen, Jinjun Xiong |
| 2020 | CVPR | Adversarial Robustness: From Self-Supervised Pre-Training to Fine-Tuning. | Tianlong Chen, Sijia Liu, Shiyu Chang, Yu Cheng, Lisa Amini, Zhangyang Wang |
| 2020 | CVPR | Towards Verifying Robustness of Neural Networks Against A Family of Semantic Perturbations. | Jeet Mohapatra, Tsui-Wei Weng, Pin-Yu Chen, Sijia Liu, Luca Daniel |
| 2020 | ECCV | 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 |
| 2020 | ECCV | 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 |
| 2020 | ECCV | 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 |
| 2020 | ICASSP | Decentralized Min-Max Optimization: Formulations, Algorithms and Applications in Network Poisoning Attack. | Ioannis C. Tsaknakis, Mingyi Hong, Sijia Liu |
| 2020 | ICASSP | Towards an Efficient and General Framework of Robust Training for Graph Neural Networks. | Kaidi Xu, Sijia Liu, Pin-Yu Chen, Mengshu Sun, Caiwen Ding, Bhavya Kailkhura, Xue Lin |
| 2020 | ICLR | Sign-OPT: A Query-Efficient Hard-label Adversarial Attack. | Minhao Cheng, Simranjit Singh, Patrick H. Chen, Pin-Yu Chen, Sijia Liu, Cho-Jui Hsieh |
| 2020 | ICML | 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 |
| 2020 | ICML | Proper Network Interpretability Helps Adversarial Robustness in Classification. | Akhilan Boopathy, Sijia Liu, Gaoyuan Zhang, Cynthia Liu, Pin-Yu Chen, Shiyu Chang, Luca Daniel |
| 2020 | ICML | 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 R. Varshney |
| 2020 | ICML | Fast Learning of Graph Neural Networks with Guaranteed Generalizability: One-hidden-layer Case. | Shuai Zhang, Meng Wang, Sijia Liu, Pin-Yu Chen, Jinjun Xiong |
| 2020 | IJCNN | Survey on Automated End-to-End Data Science? | 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 | IUI | AutoAI: Automating the End-to-End AI Lifecycle with Humans-in-the-Loop. | 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 | WSDM | A Query Taxonomy Describes Performance of Patient-Level Retrieval from Electronic Health Record Data. | Steve Chamberlin, Steven Bedrick, Aaron M. Cohen, Yanshan Wang, Andrew Wen, Sijia Liu, Hongfang Liu, William R. Hersh |
| 2019 | AAAI | CNN-Cert: An Efficient Framework for Certifying Robustness of Convolutional Neural Networks. | Akhilan Boopathy, Tsui-Wei Weng, Pin-Yu Chen, Sijia Liu, Luca Daniel |
| 2019 | AAAI | 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 |
| 2019 | AMIA | Clinical Use of an Information Retrieval Framework for Cohort Discovery from Electronic Health Records. | Yanshan Wang, Andrew Wen, Sijia Liu, Jennifer L. St. Sauver, Adil E. Bharucha, Chunhua Weng, Hongfang Liu |
| 2019 | ASPDAC | ADMM attack: an enhanced adversarial attack for deep neural networks with undetectable distortions. | Pu Zhao, Kaidi Xu, Sijia Liu, Yanzhi Wang, Xue Lin |
| 2019 | CogSci | Active physical inference via reinforcement learning. | Shuaiji Li, Yu Sun, Sijia Liu, Tianyu Wang, Todd M. Gureckis, Neil Bramley |
| 2019 | ICASSP | Latent Heterogeneous Multilayer Community Detection. | Hafiz Tiomoko Ali, Sijia Liu, Yasin Yilmaz, Romain Couillet, Indika Rajapakse, Alfred O. Hero III |
| 2019 | ICCV | Adversarial Robustness vs. Model Compression, or Both? | Shaokai Ye, Xue Lin, Kaidi Xu, Sijia Liu, Hao Cheng, Jan-Henrik Lambrechts, Huan Zhang, Aojun Zhou, Kaisheng Ma, Yanzhi Wang |
| 2019 | ICCV | On the Design of Black-Box Adversarial Examples by Leveraging Gradient-Free Optimization and Operator Splitting Method. | Pu Zhao, Sijia Liu, Pin-Yu Chen, Nghia Hoang, Kaidi Xu, Bhavya Kailkhura, Xue Lin |
| 2019 | ICDM | Generation of Low Distortion Adversarial Attacks via Convex Programming. | Tianyun Zhang, Sijia Liu, Yanzhi Wang, Makan Fardad |
| 2019 | ICLR | On the Convergence of A Class of Adam-Type Algorithms for Non-Convex Optimization. | Xiangyi Chen, Sijia Liu, Ruoyu Sun, Mingyi Hong |
| 2019 | ICLR | signSGD via Zeroth-Order Oracle. | Sijia Liu, Pin-Yu Chen, Xiangyi Chen, Mingyi Hong |
| 2019 | ICLR | 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 |
| 2019 | ICML | Fast Incremental von Neumann Graph Entropy Computation: Theory, Algorithm, and Applications. | Pin-Yu Chen, Lingfei Wu, Sijia Liu, Indika Rajapakse |
| 2019 | IJCAI | 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 |
| 2019 | KDD | Recent Progress in Zeroth Order Optimization and Its Applications to Adversarial Robustness in Data Mining and Machine Learning. | Pin-Yu Chen, Sijia Liu |
| 2018 | AISTATS | Zeroth-Order Online Alternating Direction Method of Multipliers: Convergence Analysis and Applications. | Sijia Liu, Jie Chen, Pin-Yu Chen, Alfred O. Hero III |
| 2018 | AMIA | ARETA: A Corpus for Asthma Related Event Temporal Association. | Sijia Liu, Liwei Wang, Sunghwan Sohn, Liping Xia, Hongfang Liu |
| 2018 | AMIA | Leveraging Electronic Health Records for Identification of Features Associated with Sudden Death for Hypertrophic Cardiomyopathy Patients. | Sungrim Moon, Sijia Liu, Sujith Samudrala, Jane L. Shellum, Jeffrey B. Geske, Peter A. Noseworthy, Steve Ommen, Rajeev Chaudhry, Rick Nishimura, Hongfang Liu, Adelaide M. Arruda-Olson |
| 2018 | AMIA | EMIRS: An Electronic Medical Information Retrieval System by Leveraging both Structured and Unstructured Electronic Health Records. | Yanshan Wang, Andrew Wen, Sijia Liu, Hongfang Liu |
| 2018 | CIS | Improved Extended Polynomial-Based Secret Image Sharing Scheme Using QR Code. | Zhengxin Fu, Sijia Liu, Kun Xia, Bin Yu |
| 2018 | ICASSP | First-Order Bifurcation Detection for Dynamic Complex Networks. | Sijia Liu, Pin-Yu Chen, Indika Rajapakse, Alfred O. Hero III |
| 2018 | ICASSP | Zeroth-Order Diffusion Adaptation Over Networks. | Jie Chen, Sijia Liu, Pin-Yu Chen |
| 2018 | PIMRC | LAT-based Coexistence Scheme of LTE-U with WiFi in the Unlicensed Band. | Xiaoge Huang, Ke Xu, Sijia Liu, Qianbin Chen |
| 2017 | AMIA | Leveraging Collaborative Filtering to Accelerate Rare Disease Diagnosis. | Feichen Shen, Sijia Liu, Yanshan Wang, Liwei Wang, Naveed Afzal, Hongfang Liu |
| 2017 | AMIA | Accelerating Rare Disease Diagnosis with Collaborative Filtering. | Feichen Shen, Sijia Liu, Yanshan Wang, Liwei Wang, Naveed Afzal, Hongfang Liu |
| 2017 | AMIA | Recommending education materials for diabetic questions using information retrieval approaches. | Yuqun Zeng, Yanshan Wang, Feichen Shen, Sijia Liu, Liwei Wang, Majid Rastegar-Mojarad, Xusheng Liu, Hongfang Liu |
| 2017 | ASPDAC | Algorithm-hardware co-optimization of the memristor-based framework for solving SOCP and homogeneous QCQP problems. | Ao Ren, Sijia Liu, Ruizhe Cai, Wujie Wen, Pramod K. Varshney, Yanzhi Wang |
| 2017 | ICASSP | Learning sparse graphs under smoothness prior. | Sundeep Prabhakar Chepuri, Sijia Liu, Geert Leus, Alfred O. Hero III |
| 2017 | ICASSP | Distributed optimization for evolving networks of growing connectivity. | Sijia Liu, Pin-Yu Chen, Alfred O. Hero III |
| 2017 | ICASSP | Distributed sensor selection for field estimation. | Sijia Liu, Sundeep Prabhakar Chepuri, Geert Leus, Alfred O. Hero III |
| 2017 | ICASSP | Ultra-fast robust compressive sensing based on memristor crossbars. | Sijia Liu, Ao Ren, Yanzhi Wang, Pramod K. Varshney |
| 2016 | AMIA | A Topic-modeling Based Framework for Drug-drug Interaction Classification from Biomedical Text. | Dingcheng Li, Sijia Liu, Majid Rastegar-Mojarad, Yanshan Wang, Xiaodi Li, Vipin Chaudhary, Terry M. Therneau, Hongfang Liu |
| 2016 | AMIA | Drug-drug Interaction Detection with A Topic-modeling Based Framework Augmented with Distant-supervision. | Dingcheng Li, Sijia Liu, Majid Rastegar-Mojarad, Yanshan Wang, Xiaodi Li, Vipin Chaudhary, Terry M. Therneau, Hongfang Liu |
| 2016 | CISS | Optimal energy allocation and storage control for distributed estimation with sensor collaboration. | Sijia Liu, Yanzhi Wang, Makan Fardad, Pramod K. Varshney |
| 2016 | PIMRC | Dynamic cell selection and resource allocation in cognitive small cell networks. | Xiaoge Huang, Sijia Liu, Yangyang Li, Fan Zhu, Qianbin Chen |
| 2015 | ACSSC | Joint sparsity pattern recovery with 1-bit compressive sensing in sensor networks. | Vipul Gupta, Bhavya Kailkhura, Thakshila Wimalajeewa, Sijia Liu, Pramod K. Varshney |
| 2015 | ACSSC | On optimal sensor collaboration for distributed estimation with individual power constraints. | Sijia Liu, Swarnendu Kar, Makan Fardad, Pramod K. Varshney |
| 2015 | FUSION | Sparsity-promoting sensor management for estimation: An energy balance point of view. | Sijia Liu, Feishe Chen, Aditya Vempaty, Makan Fardad, Lixin Shen, Pramod K. Varshney |
| 2015 | ICASSP | Sensor selection with correlated measurements for target tracking in wireless sensor networks. | Sijia Liu, Engin Masazade, Makan Fardad, Pramod K. Varshney |
| 2014 | ICASSP | Sparsity-aware field estimation via ordinary Kriging. | Sijia Liu, Engin Masazade, Makan Fardad, Pramod K. Varshney |
| 2014 | ISIT | On optimal sensor collaboration topologies for linear coherent estimation. | Sijia Liu, Makan Fardad, Swarnendu Kar, Pramod K. Varshney |
| 2013 | ACSSC | Adaptive non-myopic quantizer design for target tracking in wireless sensor networks. | Sijia Liu, Engin Masazade, Xiaojing Shen, Pramod K. Varshney |