| 2026 | AAAI | MegaCoin: Enhancing Medium-Grained Color Perception for Vision-Language Models. | Ming-Chang Chiu, Shicheng Wen, Pin-Yu Chen, Xuezhe Ma |
| 2026 | ACL | Why LLM Safety Guardrails Collapse After Fine-tuning: A Similarity Analysis Between Alignment and Fine-tuning Datasets. | Lei Hsiung, Tianyu Pang, Yung-Chen Tang, Linyue Song, Tsung-Yi Ho, Pin-Yu Chen, Yaoqing Yang |
| 2026 | ACL | Guardian-as-an-Advisor: Advancing Next-Generation Guardian Models for Trustworthy LLMs. | Yue Huang, Haomin Zhuang, Jiayi Ye, Han Bao, Yanbo Wang, Hang Hua, Siyuan Wu, Pin-Yu Chen, Xiangliang Zhang |
| 2026 | ACL | RiskLab: A Controlled Toolkit for Probing Emergent Risks in LLM-Based Multi-Agent Systems. | Yu Jiang, Wenjie Wang, Yue Huang, Yanbo Wang, Zhenhong Zhou, Xiuying Chen, Yang Liu, Pin-Yu Chen, Wei Wang, Xiangliang Zhang |
| 2026 | ACL | ImReasoner: Improving Memory-based Language Models for Reasoning-in-a-Haystack Tasks. | Ching-Yun Ko, Payel Das, Sihui Dai, Georgios Kollias, Subhajit Chaudhury, Aurlie C. Lozano, Pin-Yu Chen |
| 2026 | ACL | GRE Score: Generative Risk Evaluation for Large Language Models. | Zaitang Li, Pin-Yu Chen, Tsung-Yi Ho |
| 2026 | ACL | Hey, That's My Data! Token-Only Dataset Inference in Large Language Models. | Chen Xiong, Zihao Wang, Rui Zhu, Tsung-Yi Ho, Pin-Yu Chen, Jingwei Xiong, Haixu Tang |
| 2026 | ACL | ZoomR: Memory Efficient Reasoning through Multi-Granularity Key Value Retrieval. | David H. Yang, Yuxuan Zhu, Mohammad Mohammadi Amiri, Keerthiram Murugesan, Tejaswini Pedapati, Subhajit Chaudhury, Pin-Yu Chen |
| 2026 | ACL | OjaKV: Context-Aware Online Low-Rank KV Cache Compression. | Yuxuan Zhu, David H. Yang, Mohammad Mohammadi Amiri, Keerthiram Murugesan, Tejaswini Pedapati, Pin-Yu Chen |
| 2026 | DATE | FortiSky: Enhancing Adversarial and Bit-Error Robustness for Efficient and Secure Autonomous Systems. | Zishen Wan, Karthik Swaminathan, Nandhini Chandramoorthy, Pin-Yu Chen, Tushar Krishna, Vijay Janapa Reddi, Arijit Raychowdhury |
| 2026 | PAKDD | TabTokWak: Token(less)-Value Watermarking for Tabular Foundational Models. | Jeroen M. Galjaard, Chaoyi Zhu, Robert Birke, Pin-Yu Chen, Cornelis Bos, Lydia Y. Chen |
| 2026 | WACV | Data-Driven Lipschitz Continuity: A Cost-Effective Approach to Improve Adversarial Robustness. | Erh-Chung Chen, Pin-Yu Chen, I-Hsin Chung, Che-Rung Lee |
| 2025 | AAAI | Token Highlighter: Inspecting and Mitigating Jailbreak Prompts for Large Language Models. | Xiaomeng Hu, Pin-Yu Chen, Tsung-Yi Ho |
| 2025 | AAAI | Retention Score: Quantifying Jailbreak Risks for Vision Language Models. | Zaitang Li, Pin-Yu Chen, Tsung-Yi Ho |
| 2025 | AAAI | From PEFT to DEFT: Parameter Efficient Finetuning for Reducing Activation Density in Transformers. | Bharat Runwal, Tejaswini Pedapati, Pin-Yu Chen |
| 2025 | ACL | Combining Domain and Alignment Vectors Provides Better Knowledge-Safety Trade-offs in LLMs. | Megh Thakkar, Quentin Fournier, Matthew Riemer, Pin-Yu Chen, Amal Zouaq, Payel Das, Sarath Chandar |
| 2025 | ACL | Defensive Prompt Patch: A Robust and Generalizable Defense of Large Language Models against Jailbreak Attacks. | Chen Xiong, Xiangyu Qi, Pin-Yu Chen, Tsung-Yi Ho |
| 2025 | CVPR | PSBD: Prediction Shift Uncertainty Unlocks Backdoor Detection. | Wei Li, Pin-Yu Chen, Sijia Liu, Ren Wang |
| 2025 | ICASSP | VP-NTK: Exploring the Benefits of Visual Prompting in Differentially Private Data Synthesis. | Chia-Yi Hsu, Jia-You Chen, Yu-Lin Tsai, Chih-Hsun Lin, Pin-Yu Chen, Chia-Mu Yu, Chun-Ying Huang |
| 2025 | ICASSP | Modular Prompt Learning Improves Vision-Language Models. | Zhenhan Huang, Tejaswini Pedapati, Pin-Yu Chen, Jianxi Gao |
| 2025 | ICASSP | When Does Visual Prompting Outperform Linear Probing for Vision-Language Models? A Likelihood Perspective. | Hsi-Ai Tsao, Lei Hsiung, Pin-Yu Chen, Tsung-Yi Ho |
| 2025 | ICLR | REFINE: Inversion-Free Backdoor Defense via Model Reprogramming. | Yukun Chen, Shuo Shao, Enhao Huang, Yiming Li, Pin-Yu Chen, Zhan Qin, Kui Ren |
| 2025 | ICLR | Large Language Models can Become Strong Self-Detoxifiers. | Ching-Yun Ko, Pin-Yu Chen, Payel Das, Youssef Mroueh, Soham Dan, Georgios Kollias, Subhajit Chaudhury, Tejaswini Pedapati, Luca Daniel |
| 2025 | ICLR | Training Nonlinear Transformers for Chain-of-Thought Inference: A Theoretical Generalization Analysis. | Hongkang Li, Songtao Lu, Pin-Yu Chen, Xiaodong Cui, Meng Wang |
| 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 | ICLR | Revisiting Mode Connectivity in Neural Networks with Bezier Surface. | Jie Ren, Pin-Yu Chen, Ren Wang |
| 2025 | ICLR | SEAL: Safety-enhanced Aligned LLM Fine-tuning via Bilevel Data Selection. | Han Shen, Pin-Yu Chen, Payel Das, Tianyi Chen |
| 2025 | ICLR | Justice or Prejudice? Quantifying Biases in LLM-as-a-Judge. | Jiayi Ye, Yanbo Wang, Yue Huang, Dongping Chen, Qihui Zhang, Nuno Moniz, Tian Gao, Werner Geyer, Chao Huang, Pin-Yu Chen, Nitesh V. Chawla, Xiangliang Zhang |
| 2025 | ICLR | TabWak: A Watermark for Tabular Diffusion Models. | Chaoyi Zhu, Jiayi Tang, Jeroen M. Galjaard, Pin-Yu Chen, Robert Birke, Cornelis Bos, Lydia Y. Chen |
| 2025 | IJCAI | SPARC: An AI-Based Speech Processing and Real-Time Correction System. | TingRay Chung, Pin-Yu Chen |
| 2025 | IJCAI | Differentiable Prompt Learning for Vision Language Models. | Zhenhan Huang, Tejaswini Pedapati, Pin-Yu Chen, Jianxi Gao |
| 2025 | ISCAS | Quantum Machine Learning: An Interplay Between Quantum Computing and Machine Learning. | Jun Qi, Chao-Han Huck Yang, Samuel Yen-Chi Chen, Pin-Yu Chen |
| 2025 | NAACL | Attention Tracker: Detecting Prompt Injection Attacks in LLMs. | Kuo-Han Hung, Ching-Yun Ko, Ambrish Rawat, I-Hsin Chung, Winston H. Hsu, Pin-Yu Chen |
| 2025 | NAACL | STAR: Spectral Truncation and Rescale for Model Merging. | Yu-Ang Lee, Ching-Yun Ko, Tejaswini Pedapati, I-Hsin Chung, Mi-Yen Yeh, Pin-Yu Chen |
| 2025 | NDSS | CENSOR: Defense Against Gradient Inversion via Orthogonal Subspace Bayesian Sampling. | Kaiyuan Zhang, Siyuan Cheng, Guangyu Shen, Bruno Ribeiro, Shengwei An, Pin-Yu Chen, Xiangyu Zhang, Ninghui Li |
| 2025 | WACV | DiffuseKronA: A Parameter Efficient Fine-tuning Method for Personalized Diffusion Models. | Shyam Marjit, Harshit Singh, Nityanand Mathur, Sayak Paul, Chia-Mu Yu, Pin-Yu Chen |
| 2024 | AAAI | Elijah: Eliminating Backdoors Injected in Diffusion Models via Distribution Shift. | Shengwei An, Sheng-Yen Chou, Kaiyuan Zhang, Qiuling Xu, Guanhong Tao, Guangyu Shen, Siyuan Cheng, Shiqing Ma, Pin-Yu Chen, Tsung-Yi Ho, Xiangyu Zhang |
| 2024 | AAAI | Model Reprogramming: Resource-Efficient Cross-Domain Machine Learning. | Pin-Yu Chen |
| 2024 | ACCV | Latency Attack Resilience in Object Detectors: Insights from Computing Architecture. | Erh-Chung Chen, Pin-Yu Chen, I-Hsin Chung, Che-Rung Lee |
| 2024 | ACL | A Deep Dive into the Trade-Offs of Parameter-Efficient Preference Alignment Techniques. | Megh Thakkar, Quentin Fournier, Matthew Riemer, Pin-Yu Chen, Amal Zouaq, Payel Das, Sarath Chandar |
| 2024 | ACL | Duwak: Dual Watermarks in Large Language Models. | Chaoyi Zhu, Jeroen Galjaard, Pin-Yu Chen, Lydia Y. Chen |
| 2024 | ASPLOS | MulBERRY: Enabling Bit-Error Robustness for Energy-Efficient Multi-Agent Autonomous Systems. | Zishen Wan, Nandhini Chandramoorthy, Karthik Swaminathan, Pin-Yu Chen, Kshitij Bhardwaj, Vijay Janapa Reddi, Arijit Raychowdhury |
| 2024 | CVPR | Overload: Latency Attacks on Object Detection for Edge Devices. | Erh-Chung Chen, Pin-Yu Chen, I-Hsin Chung, Che-Rung Lee |
| 2024 | CVPR | Uncovering the Hidden Cost of Model Compression. | Diganta Misra, Muawiz Chaudhary, Agam Goyal, Bharat Runwal, Pin-Yu Chen |
| 2024 | ICASSP | DDI-CoCo: A Dataset for Understanding the Effect of Color Contrast in Machine-Assisted Skin Disease Detection. | Ming-Chang Chiu, Yingfei Wang, Yen-Ju Kuo, Pin-Yu Chen |
| 2024 | ICASSP | Variance Reduction Can Improve Trade-Off in Multi-Objective Learning. | Heshan Devaka Fernando, Lisha Chen, Songtao Lu, Pin-Yu Chen, Miao Liu, Subhajit Chaudhury, Keerthiram Murugesan, Gaowen Liu, Meng Wang, Tianyi Chen |
| 2024 | ICCAD | An Effective Analytical Placement Approach to Handle Fence Region Constraint. | Jai-Ming Lin, Wei-Yuan Lin, Yung-Chen Chen, Pin-Yu Chen, Chen-Fa Tsai, De-Shiun Fu, Che-Li Lin |
| 2024 | ICLR | Time-LLM: Time Series Forecasting by Reprogramming Large Language Models. | Ming Jin, Shiyu Wang, Lintao Ma, Zhixuan Chu, James Y. Zhang, Xiaoming Shi, Pin-Yu Chen, Yuxuan Liang, Yuan-Fang Li, Shirui Pan, Qingsong Wen |
| 2024 | ICLR | It's Never Too Late: Fusing Acoustic Information into Large Language Models for Automatic Speech Recognition. | Chen Chen, Ruizhe Li, Yuchen Hu, Sabato Marco Siniscalchi, Pin-Yu Chen, Engsiong Chng, Chao-Han Huck Yang |
| 2024 | ICLR | Rethinking Backdoor Attacks on Dataset Distillation: A Kernel Method Perspective. | Ming-Yu Chung, Sheng-Yen Chou, Chia-Mu Yu, Pin-Yu Chen, Sy-Yen Kuo, Tsung-Yi Ho |
| 2024 | ICLR | Large Language Models are Efficient Learners of Noise-Robust Speech Recognition. | Yuchen Hu, Chen Chen, Chao-Han Huck Yang, Ruizhe Li, Chao Zhang, Pin-Yu Chen, Engsiong Chng |
| 2024 | ICLR | The Devil is in the Neurons: Interpreting and Mitigating Social Biases in Language Models. | Yan Liu, Yu Liu, Xiaokang Chen, Pin-Yu Chen, Daoguang Zan, Min-Yen Kan, Tsung-Yi Ho |
| 2024 | ICLR | Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To! | Xiangyu Qi, Yi Zeng, Tinghao Xie, Pin-Yu Chen, Ruoxi Jia, Prateek Mittal, Peter Henderson |
| 2024 | ICLR | Ring-A-Bell! How Reliable are Concept Removal Methods For Diffusion Models? | Yu-Lin Tsai, Chia-Yi Hsu, Chulin Xie, Chih-Hsun Lin, Jia-You Chen, Bo Li, Pin-Yu Chen, Chia-Mu Yu, Chun-Ying Huang |
| 2024 | ICLR | AutoVP: An Automated Visual Prompting Framework and Benchmark. | Hsi-Ai Tsao, Lei Hsiung, Pin-Yu Chen, Si Liu, Tsung-Yi Ho |
| 2024 | ICML | SF-DQN: Provable Knowledge Transfer using Successor Feature for Deep Reinforcement Learning. | Shuai Zhang, Heshan Devaka Fernando, Miao Liu, Keerthiram Murugesan, Songtao Lu, Pin-Yu Chen, Tianyi Chen, Meng Wang |
| 2024 | ICML | Prompting4Debugging: Red-Teaming Text-to-Image Diffusion Models by Finding Problematic Prompts. | Zhi-Yi Chin, Chieh-Ming Jiang, Ching-Chun Huang, Pin-Yu Chen, Wei-Chen Chiu |
| 2024 | ICML | A Provably Effective Method for Pruning Experts in Fine-tuned Sparse Mixture-of-Experts. | Mohammed Nowaz Rabbani Chowdhury, Meng Wang, Kaoutar El Maghraoui, Naigang Wang, Pin-Yu Chen, Christopher D. Carothers |
| 2024 | ICML | Larimar: Large Language Models with Episodic Memory Control. | Payel Das, Subhajit Chaudhury, Elliot Nelson, Igor Melnyk, Sarathkrishna Swaminathan, Sihui Dai, Aurlie C. Lozano, Georgios Kollias, Vijil Chenthamarakshan, Jir Navrtil, Soham Dan, Pin-Yu Chen |
| 2024 | ICML | Be Your Own Neighborhood: Detecting Adversarial Examples by the Neighborhood Relations Built on Self-Supervised Learning. | Zhiyuan He, Yijun Yang, Pin-Yu Chen, Qiang Xu, Tsung-Yi Ho |
| 2024 | ICML | Position: TrustLLM: Trustworthiness in Large Language Models. | Yue Huang, Lichao Sun, Haoran Wang, Siyuan Wu, Qihui Zhang, Yuan Li, Chujie Gao, Yixin Huang, Wenhan Lyu, Yixuan Zhang, Xiner Li, Hanchi Sun, Zhengliang Liu, Yixin Liu, Yijue Wang, Zhikun Zhang, Bertie Vidgen, Bhavya Kailkhura, Caiming Xiong, Chaowei Xiao, Chunyuan Li, Eric P. Xing, Furong Huang, Hao Liu, Heng Ji, Hongyi Wang, Huan Zhang, Huaxiu Yao, Manolis Kellis, Marinka Zitnik, Meng Jiang, Mohit Bansal, James Zou, Jian Pei, Jian Liu, Jianfeng Gao, Jiawei Han, Jieyu Zhao, Jiliang Tang, Jindong Wang, Joaquin Vanschoren, John C. Mitchell, Kai Shu, Kaidi Xu, Kai-Wei Chang, Lifang He, Lifu Huang, Michael Backes, Neil Zhenqiang Gong, Philip S. Yu, Pin-Yu Chen, Quanquan Gu, Ran Xu, Rex Ying, Shuiwang Ji, Suman Jana, Tianlong Chen, Tianming Liu, Tianyi Zhou, William Wang, Xiang Li, Xiangliang Zhang, Xiao Wang, Xing Xie, Xun Chen, Xuyu Wang, Yan Liu, Yanfang Ye, Yinzhi Cao, Yong Chen, Yue Zhao |
| 2024 | ICML | What Would Gauss Say About Representations? Probing Pretrained Image Models using Synthetic Gaussian Benchmarks. | Ching-Yun Ko, Pin-Yu Chen, Payel Das, Jeet Mohapatra, Luca Daniel |
| 2024 | ICML | How Do Nonlinear Transformers Learn and Generalize in In-Context Learning? | Hongkang Li, Meng Wang, Songtao Lu, Xiaodong Cui, Pin-Yu Chen |
| 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 | Learning Optimal Projection for Forecast Reconciliation of Hierarchical Time Series. | Asterios Tsiourvas, Wei Sun, Georgia Perakis, Pin-Yu Chen, Yada Zhu |
| 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 | IJCAI | Computational Complexity of Verifying the Group No-show Paradox. | Farhad Mohsin, Qishen Han, Sikai Ruan, Pin-Yu Chen, Francesca Rossi, Lirong Xia |
| 2024 | KDD | SepsisLab: Early Sepsis Prediction with Uncertainty Quantification and Active Sensing. | Changchang Yin, Pin-Yu Chen, Bingsheng Yao, Dakuo Wang, Jeffrey M. Caterino, Ping Zhang |
| 2024 | NAACL | Language Agnostic Code Embeddings. | Saiteja Utpala, Alex Gu, Pin-Yu Chen |
| 2024 | PAKDD | On Dark Knowledge for Distilling Generators. | Chi Hong, Robert Birke, Pin-Yu Chen, Lydia Y. Chen |
| 2024 | WACV | Masking Improves Contrastive Self-Supervised Learning for ConvNets, and Saliency Tells You Where. | Zhi-Yi Chin, Chieh-Ming Jiang, Ching-Chun Huang, Pin-Yu Chen, Wei-Chen Chiu |
| 2023 | AAAI | Holistic Adversarial Robustness of Deep Learning Models. | Pin-Yu Chen, Sijia Liu |
| 2023 | AAAI | NCTV: Neural Clamping Toolkit and Visualization for Neural Network Calibration. | Lei Hsiung, Yung-Chen Tang, Pin-Yu Chen, Tsung-Yi Ho |
| 2023 | AAAI | When Neural Networks Fail to Generalize? A Model Sensitivity Perspective. | Jiajin Zhang, Hanqing Chao, Amit Dhurandhar, Pin-Yu Chen, Ali Tajer, Yangyang Xu, Pingkun Yan |
| 2023 | AISTATS | Convex Bounds on the Softmax Function with Applications to Robustness Verification. | Dennis Wei, Haoze Wu, Min Wu, Pin-Yu Chen, Clark W. Barrett, Eitan Farchi |
| 2023 | CCS | Unraveling the Connections between Privacy and Certified Robustness in Federated Learning Against Poisoning Attacks. | Chulin Xie, Yunhui Long, Pin-Yu Chen, Qinbin Li, Sanmi Koyejo, Bo Li |
| 2023 | CVPR | Understanding and Improving Visual Prompting: A Label-Mapping Perspective. | Aochuan Chen, Yuguang Yao, Pin-Yu Chen, Yihua Zhang, Sijia Liu |
| 2023 | CVPR | How to Backdoor Diffusion Models? | Sheng-Yen Chou, Pin-Yu Chen, Tsung-Yi Ho |
| 2023 | CVPR | Towards Compositional Adversarial Robustness: Generalizing Adversarial Training to Composite Semantic Perturbations. | Lei Hsiung, Yun-Yun Tsai, Pin-Yu Chen, Tsung-Yi Ho |
| 2023 | CVPR | Causalainer: Causal Explainer for Automatic Video Summarization. | Jia-Hong Huang, Chao-Han Huck Yang, Pin-Yu Chen, Min-Hung Chen, Marcel Worring |
| 2023 | DAC | BERRY: Bit Error Robustness for Energy-Efficient Reinforcement Learning-Based Autonomous Systems. | Zishen Wan, Nandhini Chandramoorthy, Karthik Swaminathan, Pin-Yu Chen, Vijay Janapa Reddi, Arijit Raychowdhury |
| 2023 | EMNLP | Locally Differentially Private Document Generation Using Zero Shot Prompting. | Saiteja Utpala, Sara Hooker, Pin-Yu Chen |
| 2023 | ICASSP | Lost In Translation: Generating Adversarial Examples Robust to Round-Trip Translation. | Neel Bhandari, Pin-Yu Chen |
| 2023 | ICASSP | Visual Prompting for Adversarial Robustness. | Aochuan Chen, Peter Lorenz, Yuguang Yao, Pin-Yu Chen, Sijia Liu |
| 2023 | ICASSP | Certified Robustness of Quantum Classifiers Against Adversarial Examples Through Quantum Noise. | Jhih-Cing Huang, Yu-Lin Tsai, Chao-Han Huck Yang, Cheng-Fang Su, Chia-Mu Yu, Pin-Yu Chen, Sy-Yen Kuo |
| 2023 | ICASSP | Low-Resource Music Genre Classification with Cross-Modal Neural Model Reprogramming. | Yun-Ning Hung, Chao-Han Huck Yang, Pin-Yu Chen, Alexander Lerch |
| 2023 | ICCV | Better May Not Be Fairer: A Study on Subgroup Discrepancy in Image Classification. | Ming-Chang Chiu, Pin-Yu Chen, Xuezhe Ma |
| 2023 | ICCV | Exploring the Benefits of Visual Prompting in Differential Privacy. | Yizhe Li, Yu-Lin Tsai, Chia-Mu Yu, Pin-Yu Chen, Xuebin Ren |
| 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 | ICLR | FLIP: A Provable Defense Framework for Backdoor Mitigation in Federated Learning. | Kaiyuan Zhang, Guanhong Tao, Qiuling Xu, Siyuan Cheng, Shengwei An, Yingqi Liu, Shiwei Feng, Guangyu Shen, Pin-Yu Chen, Shiqing Ma, Xiangyu Zhang |
| 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 | A Theoretical Understanding of Shallow Vision Transformers: Learning, Generalization, and Sample Complexity. | Hongkang Li, Meng Wang, Sijia Liu, Pin-Yu Chen |
| 2023 | ICML | Identification of the Adversary from a Single Adversarial Example. | Minhao Cheng, Rui Min, Haochen Sun, Pin-Yu Chen |
| 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 | MultiRobustBench: Benchmarking Robustness Against Multiple Attacks. | Sihui Dai, Saeed Mahloujifar, Chong Xiang, Vikash Sehwag, Pin-Yu Chen, Prateek Mittal |
| 2023 | ICML | Reprogramming Pretrained Language Models for Antibody Sequence Infilling. | Igor Melnyk, Vijil Chenthamarakshan, Pin-Yu Chen, Payel Das, Amit Dhurandhar, Inkit Padhi, Devleena Das |
| 2023 | ICML | Which Features are Learnt by Contrastive Learning? On the Role of Simplicity Bias in Class Collapse and Feature Suppression. | Yihao Xue, Siddharth Joshi, Eric Gan, Pin-Yu Chen, Baharan Mirzasoleiman |
| 2023 | ICML | Compressed Decentralized Proximal Stochastic Gradient Method for Nonconvex Composite Problems with Heterogeneous Data. | Yonggui Yan, Jie Chen, Pin-Yu Chen, Xiaodong Cui, Songtao Lu, Yangyang Xu |
| 2023 | IJCAI | Learning to Design Fair and Private Voting Rules (Extended Abstract). | Farhad Mohsin, Ao Liu, Pin-Yu Chen, Francesca Rossi, Lirong Xia |
| 2023 | Interspeech | Neural Model Reprogramming with Similarity Based Mapping for Low-Resource Spoken Command Recognition. | Hao Yen, Pin-Jui Ku, Chao-Han Huck Yang, Hu Hu, Sabato Marco Siniscalchi, Pin-Yu Chen, Yu Tsao |
| 2023 | IROS | MENTOR: Multilingual Text Detection Toward Learning by Analogy. | Hsin-Ju Lin, Tsu-Chun Chung, Ching-Chun Hsiao, Pin-Yu Chen, Wei-Chen Chiu, Ching-Chun Huang |
| 2023 | MICCAI | Spectral Adversarial MixUp for Few-Shot Unsupervised Domain Adaptation. | Jiajin Zhang, Hanqing Chao, Amit Dhurandhar, Pin-Yu Chen, Ali Tajer, Yangyang Xu, Pingkun Yan |
| 2023 | WACV | Treatment Learning Causal Transformer for Noisy Image Classification. | Chao-Han Huck Yang, I-Te Danny Hung, Yi-Chieh Liu, Pin-Yu Chen |
| 2023 | UAI | Pessimistic Model Selection for Offline Deep Reinforcement Learning. | Chao-Han Huck Yang, Zhengling Qi, Yifan Cui, Pin-Yu Chen |
| 2022 | AAAI | AI Explainability 360: Impact and Design. | Vijay Arya, Rachel K. E. Bellamy, Pin-Yu Chen, Amit Dhurandhar, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Q. Vera Liao, Ronny Luss, Aleksandra Mojsilovic, Sami Mourad, Pablo Pedemonte, Ramya Raghavendra, John T. Richards, Prasanna Sattigeri, Karthikeyan Shanmugam, Moninder Singh, Kush R. Varshney, Dennis Wei, Yunfeng Zhang |
| 2022 | AAAI | SenSE: A Toolkit for Semantic Change Exploration via Word Embedding Alignment. | Maurcio Gruppi, Sibel Adali, Pin-Yu Chen |
| 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 | AAAI | Vision Transformers Are Robust Learners. | Sayak Paul, Pin-Yu Chen |
| 2022 | AAAI | Training a Resilient Q-network against Observational Interference. | Chao-Han Huck Yang, I-Te Danny Hung, Yi Ouyang, Pin-Yu Chen |
| 2022 | ECCV | A Spectral View of Randomized Smoothing Under Common Corruptions: Benchmarking and Improving Certified Robustness. | Jiachen Sun, Akshay Mehra, Bhavya Kailkhura, Pin-Yu Chen, Dan Hendrycks, Jihun Hamm, Z. Morley Mao |
| 2022 | ICASSP | Real-World Adversarial Examples Via Makeup. | Chang-Sheng Lin, Chia-Yi Hsu, Pin-Yu Chen, Chia-Mu Yu |
| 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 | ICASSP | When BERT Meets Quantum Temporal Convolution Learning for Text Classification in Heterogeneous Computing. | Chao-Han Huck Yang, Jun Qi, Samuel Yen-Chi Chen, Yu Tsao, Pin-Yu Chen |
| 2022 | ICCAD | Analyzing and Improving Resilience and Robustness of Autonomous Systems. | Zishen Wan, Karthik Swaminathan, Pin-Yu Chen, Nandhini Chandramoorthy, Arijit Raychowdhury |
| 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 | MAML is a Noisy Contrastive Learner in Classification. | Chia-Hsiang Kao, Wei-Chen Chiu, Pin-Yu Chen |
| 2022 | ICLR | Auto-Transfer: Learning to Route Transferable Representations. | Keerthiram Murugesan, Vijay Sadashivaiah, Ronny Luss, Karthikeyan Shanmugam, Pin-Yu Chen, Amit Dhurandhar |
| 2022 | ICML | Sharp-MAML: Sharpness-Aware Model-Agnostic Meta Learning. | Momin Abbas, Quan Xiao, Lisha Chen, Pin-Yu Chen, Tianyi Chen |
| 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 | IJCAI | CAT: Customized Adversarial Training for Improved Robustness. | Minhao Cheng, Qi Lei, Pin-Yu Chen, Inderjit S. Dhillon, Cho-Jui Hsieh |
| 2022 | IJCAI | Towards Creativity Characterization of Generative Models via Group-Based Subset Scanning. | Celia Cintas, Payel Das, Brian Quanz, Girmaw Abebe Tadesse, Skyler Speakman, Pin-Yu Chen |
| 2022 | IJCAI | CARBEN: Composite Adversarial Robustness Benchmark. | Lei Hsiung, Yun-Yun Tsai, Pin-Yu Chen, Tsung-Yi Ho |
| 2022 | IPCCC | Iterative Qubits Management for Quantum Index Searching in a Hybrid System. | Wenrui Mu, Ying Mao, Long Cheng, Qingle Wang, Weiwen Jiang, Pin-Yu Chen |
| 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 | 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 |
| 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 | Fake it Till You Make it: Self-Supervised Semantic Shifts for Monolingual Word Embedding Tasks. | Maurcio Gruppi, Pin-Yu Chen, Sibel Adali |
| 2021 | AAAI | Curse or Redemption? How Data Heterogeneity Affects the Robustness of Federated Learning. | Syed Zawad, Ahsan Ali, Pin-Yu Chen, Ali Anwar, Yi Zhou, Nathalie Baracaldo, Yuan Tian, Feng Yan |
| 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 | COMAD | AI Explainability 360 Toolkit. | Vijay Arya, Rachel K. E. Bellamy, Pin-Yu Chen, Amit Dhurandhar, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Q. Vera Liao, Ronny Luss, Aleksandra Mojsilovic, Sami Mourad, Pablo Pedemonte, Ramya Raghavendra, John T. Richards, Prasanna Sattigeri, Karthikeyan Shanmugam, Moninder Singh, Kush R. Varshney, Dennis Wei, Yunfeng Zhang |
| 2021 | CVPR | How Robust Are Randomized Smoothing Based Defenses to Data Poisoning? | Akshay Mehra, Bhavya Kailkhura, Pin-Yu Chen, Jihun Hamm |
| 2021 | DAC | AID: Attesting the Integrity of Deep Neural Networks. | Omid Aramoon, Pin-Yu Chen, Gang Qu |
| 2021 | ICASSP | Active Estimation From Multimodal Data. | Arpan Mukherjee, Ali Tajer, Pin-Yu Chen, Payel Das |
| 2021 | ICASSP | Domain Adaptation for Learning Generator From Paired Few-Shot Data. | Chun-Chih Teng, Pin-Yu Chen, Wei-Chen Chiu |
| 2021 | ICASSP | Non-Singular Adversarial Robustness of Neural Networks. | Yu-Lin Tsai, Chia-Yi Hsu, Chia-Mu Yu, Pin-Yu Chen |
| 2021 | ICASSP | Decentralizing Feature Extraction with Quantum Convolutional Neural Network for Automatic Speech Recognition. | Chao-Han Huck Yang, Jun Qi, Samuel Yen-Chi Chen, Pin-Yu Chen, Sabato Marco Siniscalchi, Xiaoli Ma, Chin-Hui Lee |
| 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 | ICML | Fold2Seq: A Joint Sequence(1D)-Fold(3D) Embedding-based Generative Model for Protein Design. | Yue Cao, Payel Das, Vijil Chenthamarakshan, Pin-Yu Chen, Igor Melnyk, Yang Shen |
| 2021 | ICML | CRFL: Certifiably Robust Federated Learning against Backdoor Attacks. | Chulin Xie, Minghao Chen, Pin-Yu Chen, Bo Li |
| 2021 | ICML | Voice2Series: Reprogramming Acoustic Models for Time Series Classification. | Chao-Han Huck Yang, Yun-Yun Tsai, Pin-Yu Chen |
| 2021 | IJCAI | Characteristic Examples: High-Robustness, Low-Transferability Fingerprinting of Neural Networks. | Siyue Wang, Xiao Wang, Pin-Yu Chen, Pu Zhao, Xue Lin |
| 2021 | IJCNN | Self-Attentive Recommendation for Multi-Source Review Package. | Pin-Yu Chen, Yu-Hsiu Chen, Hong-Han Shuai, Yung-Ju Chang |
| 2021 | ISIT | Active Binary Classification of Random Fields. | Arpan Mukherjee, Ali Tajer, Pin-Yu Chen, Payel Das |
| 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 | KDD | Leveraging Latent Features for Local Explanations. | Ronny Luss, Pin-Yu Chen, Amit Dhurandhar, Prasanna Sattigeri, Yunfeng Zhang, Karthikeyan Shanmugam, Chun-Chen Tu |
| 2020 | AAAI | TemPEST: Soft Template-Based Personalized EDM Subject Generation through Collaborative Summarization. | Yu-Hsiu Chen, Pin-Yu Chen, Hong-Han Shuai, Wen-Chih Peng |
| 2020 | AAAI | Seq2Sick: Evaluating the Robustness of Sequence-to-Sequence Models with Adversarial Examples. | Minhao Cheng, Jinfeng Yi, Pin-Yu Chen, Huan Zhang, Cho-Jui Hsieh |
| 2020 | AAAI | Towards Certificated Model Robustness Against Weight Perturbations. | Tsui-Wei Weng, Pu Zhao, Sijia Liu, Pin-Yu Chen, Xue Lin, Luca Daniel |
| 2020 | AAAI | Reinforcement-Learning Based Portfolio Management with Augmented Asset Movement Prediction States. | Yunan Ye, Hengzhi Pei, Boxin Wang, Pin-Yu Chen, Yada Zhu, Ju Xiao, Bo Li |
| 2020 | AAAI | Towards Query-Efficient Black-Box Adversary with Zeroth-Order Natural Gradient Descent. | Pu Zhao, Pin-Yu Chen, Siyue Wang, Xue Lin |
| 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 | 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 | 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 | AdvMS: A Multi-Source Multi-Cost Defense Against Adversarial Attacks. | Xiao Wang, Siyue Wang, Pin-Yu Chen, Xue Lin, Peter Chin |
| 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 | ICASSP | Characterizing Speech Adversarial Examples Using Self-Attention U-Net Enhancement. | Chao-Han Huck Yang, Jun Qi, Pin-Yu Chen, Xiaoli Ma, Chin-Hui Lee |
| 2020 | ICASSP | Enhanced Adversarial Strategically-Timed Attacks Against Deep Reinforcement Learning. | Chao-Han Huck Yang, Jun Qi, Pin-Yu Chen, Yi Ouyang, I-Te Danny Hung, Chin-Hui Lee, Xiaoli Ma |
| 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 | ICLR | DBA: Distributed Backdoor Attacks against Federated Learning. | Chulin Xie, Keli Huang, Pin-Yu Chen, Bo Li |
| 2020 | ICLR | Bridging Mode Connectivity in Loss Landscapes and Adversarial Robustness. | Pu Zhao, Pin-Yu Chen, Payel Das, Karthikeyan Natesan Ramamurthy, Xue Lin |
| 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 | Transfer Learning without Knowing: Reprogramming Black-box Machine Learning Models with Scarce Data and Limited Resources. | Yun-Yun Tsai, Pin-Yu Chen, Tsung-Yi Ho |
| 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 | IJCAI | Toward a neuro-inspired creative decoder. | Payel Das, Brian Quanz, Pin-Yu Chen, Jae-wook Ahn, Dhruv Shah |
| 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 | CCS | Characterizing Adversarial Subspaces by Mutual Information. | Chia-Yi Hsu, Pin-Yu Chen, Chia-Mu Yu |
| 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 | ICIP | When Causal Intervention Meets Adversarial Examples and Image Masking for Deep Neural Networks. | Chao-Han Huck Yang, Yi-Chieh Liu, Pin-Yu Chen, Xiaoli Ma, Yi-Chang James Tsai |
| 2019 | ICLR | Query-Efficient Hard-label Black-box Attack: An Optimization-based Approach. | Minhao Cheng, Thong Le, Pin-Yu Chen, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh |
| 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 | ICLR | Characterizing Audio Adversarial Examples Using Temporal Dependency. | Zhuolin Yang, Bo Li, Pin-Yu Chen, Dawn Song |
| 2019 | ICML | Fast Incremental von Neumann Graph Entropy Computation: Theory, Algorithm, and Applications. | Pin-Yu Chen, Lingfei Wu, Sijia Liu, Indika Rajapakse |
| 2019 | ICML | PROVEN: Verifying Robustness of Neural Networks with a Probabilistic Approach. | Lily Weng, Pin-Yu Chen, Lam M. Nguyen, Mark S. Squillante, Akhilan Boopathy, Ivan V. Oseledets, Luca Daniel |
| 2019 | IJCAI | Protecting Neural Networks with Hierarchical Random Switching: Towards Better Robustness-Accuracy Trade-off for Stochastic Defenses. | Xiao Wang, Siyue Wang, Pin-Yu Chen, Yanzhi Wang, Brian Kulis, Xue Lin, Sang Chin |
| 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 | AAAI | EAD: Elastic-Net Attacks to Deep Neural Networks via Adversarial Examples. | Pin-Yu Chen, Yash Sharma, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh |
| 2018 | ACL | Attacking Visual Language Grounding with Adversarial Examples: A Case Study on Neural Image Captioning. | Hongge Chen, Huan Zhang, Pin-Yu Chen, Jinfeng Yi, Cho-Jui Hsieh |
| 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 | DSN | On the Limitation of MagNet Defense Against L1-Based Adversarial Examples. | Pei-Hsuan Lu, Pin-Yu Chen, Kang-Cheng Chen, Chia-Mu Yu |
| 2018 | ECCV | Is Robustness the Cost of Accuracy? - A Comprehensive Study on the Robustness of 18 Deep Image Classification Models. | Dong Su, Huan Zhang, Hongge Chen, Jinfeng Yi, Pin-Yu Chen, Yupeng Gao |
| 2018 | EMNLP | Word Mover's Embedding: From Word2Vec to Document Embedding. | Lingfei Wu, Ian En-Hsu Yen, Kun Xu, Fangli Xu, Avinash Balakrishnan, Pin-Yu Chen, Pradeep Ravikumar, Michael J. Witbrock |
| 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 | ICASSP | On the Supermodularity of Active Graph-Based Semi-Supervised Learning with Stieltjes Matrix Regularization. | Pin-Yu Chen, Dennis Wei |
| 2018 | ICLR | On the Limitation of Local Intrinsic Dimensionality for Characterizing the Subspaces of Adversarial Examples. | Pei-Hsuan Lu, Pin-Yu Chen, Chia-Mu Yu |
| 2018 | ICLR | Attacking the Madry Defense Model with $L_1$-based Adversarial Examples. | Yash Sharma, Pin-Yu Chen |
| 2018 | ICLR | Evaluating the Robustness of Neural Networks: An Extreme Value Theory Approach. | Tsui-Wei Weng, Huan Zhang, Pin-Yu Chen, Jinfeng Yi, Dong Su, Yupeng Gao, Cho-Jui Hsieh, Luca Daniel |
| 2018 | KDD | Scalable Spectral Clustering Using Random Binning Features. | Lingfei Wu, Pin-Yu Chen, Ian En-Hsu Yen, Fangli Xu, Yinglong Xia, Charu C. Aggarwal |
| 2017 | AINA | FEAST: An Automated Feature Selection Framework for Compilation Tasks. | Pai-Shun Ting, Chun-Chen Tu, Pin-Yu Chen, Ya-Yun Lo, Shin-Ming Cheng |
| 2017 | CCS | ZOO: Zeroth Order Optimization Based Black-box Attacks to Deep Neural Networks without Training Substitute Models. | Pin-Yu Chen, Huan Zhang, Yash Sharma, Jinfeng Yi, Cho-Jui Hsieh |
| 2017 | ICASSP | AMOS: An automated model order selection algorithm for spectral graph clustering. | Pin-Yu Chen, Thibaut Gensollen, Alfred O. Hero III |
| 2017 | ICASSP | Distributed optimization for evolving networks of growing connectivity. | Sijia Liu, Pin-Yu Chen, Alfred O. Hero III |
| 2017 | ICDM | Revisiting Spectral Graph Clustering with Generative Community Models. | Pin-Yu Chen, Lingfei Wu |
| 2017 | ICDM | Principled Multilayer Network Embedding. | Weiyi Liu, Pin-Yu Chen, Sailung Yeung, Toyotaro Suzumura, Lingli Chen |
| 2016 | ICASSP | Multi-centrality graph spectral decompositions and their application to cyber intrusion detection. | Pin-Yu Chen, Sutanay Choudhury, Alfred O. Hero III |
| 2016 | SP | Ecology-Based DoS Attack in Cognitive Radio Networks. | Shin-Ming Cheng, Pin-Yu Chen |
| 2015 | CCS | DEMO: Action Recommendation for Cyber Resilience. | Luke Rodriguez, Darren S. Curtis, Sutanay Choudhury, Kiri Oler, Peter Nordquist, Pin-Yu Chen, Indrajit Ray |
| 2015 | GLOBECOM | Supervised Collective Classification for Crowdsourcing. | Pin-Yu Chen, Chia-Wei Lien, Fu-Jen Chu, Pai-Shun Ting, Shin-Ming Cheng |
| 2015 | ICASSP | Phase transitions in spectral community detection of large noisy networks. | Pin-Yu Chen, Alfred O. Hero III |
| 2014 | ICASSP | Local Fiedler vector centrality for detection of deep and overlapping communities in networks. | Pin-Yu Chen, Alfred O. Hero III |
| 2014 | VTC | Modeling Dynamics of Malware with Incubation Period from the View of Individual. | Pin-Yu Chen, Han-Feng Lin, Ko-Hsuan Hsu, Shin-Ming Cheng |
| 2011 | GLOBECOM | Reciprocal spectrum sharing game and mechanism in cellular systems with Cognitive Radio users. | Pin-Yu Chen, Weng-Chon Ao, Shih-Chun Lin, Kwang-Cheng Chen |
| 2011 | GLOBECOM | Intentional Attack and Fusion-Based Defense Strategy in Complex Networks. | Pin-Yu Chen, Kwang-Cheng Chen |
| 2011 | GLOBECOM | Optimal Control of Epidemic Information Dissemination in Mobile Ad Hoc Networks. | Pin-Yu Chen, Kwang-Cheng Chen |
| 2011 | GLOBECOM | Network synchronization among femtocells. | Shao-Yu Lien, Hou-Hsun Lee, Sung-Yin Shih, Pin-Yu Chen, Kwang-Cheng Chen |
| 2011 | ISCC | Topology control in multi-channel cognitive radio networks with non-uniform node arrangements. | Pin-Yu Chen, Vasileios Karyotis, Symeon Papavassiliou, Kwang-Cheng Chen |
| 2010 | GLOBECOM | Information Epidemics in Complex Networks with Opportunistic Links and Dynamic Topology. | Pin-Yu Chen, Kwang-Cheng Chen |