Yang Liu - RankMe

277 papers A* 86A 11B 7C 5Misc 1Journal 141Unranked 25

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	From Failure to Mastery: Generating Hard Samples for Tool-use Agents. CoRR Bingguang Hao, Zengzhuang Xu, Yuntao Wen, Xinyi Xu, Yang Liu, Tong Zhao, Maolin Wang, Long Chen, Dong Wang, Yicheng Chen, Cunyin Peng, Xiangyu Zhao, Chenyi Zhuang, Ji Zhang
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`	Small-Margin Preferences Still Matter-If You Train Them Right. CoRR Jinlong Pang, Zhaowei Zhu, Na Di, Yichi Zhang, Yaxuan Wang, Chen Qian, Yang Liu
2025	A*	`conf`	ACC-Collab: An Actor-Critic Approach to Multi-Agent LLM Collaboration. ICLR Andrew Estornell, Jean-Francois Ton, Yuanshun Yao, Yang Liu
2025	J	`jnl`	Adaptive Bounded Exploration and Intermediate Actions for Data Debiasing. CoRR Yifan Yang, Yang Liu, Parinaz Naghizadeh
2025	A*	`conf`	Adversarial Machine Unlearning. ICLR Zonglin Di, Sixie Yu, Yevgeniy Vorobeychik, Yang Liu
2025	J	`jnl`	Evaluating LLM-corrupted Crowdsourcing Data Without Ground Truth. CoRR Yichi Zhang, Jinlong Pang, Zhaowei Zhu, Yang Liu
2025	J	`jnl`	FunReason-MT Technical Report: Overcoming the Complexity Barrier in Multi-Turn Function Calling. CoRR Zengzhuang Xu, Bingguang Hao, Zechuan Wang, Yuntao Wen, Maolin Wang, Yang Liu, Long Chen, Dong Wang, Yicheng Chen, Cunyin Peng, Chenyi Zhuang, Jinjie Gu, Leilei Gan, Xiangyu Zhao, Shi Gu
2025	A*	`conf`	Human and AI Perceptual Differences in Image Classification Errors. AAAI Minghao Liu, Jiaheng Wei, Yang Liu, James Davis
2025	A*	`conf`	Improving Data Efficiency via Curating LLM-Driven Rating Systems. ICLR Jinlong Pang, Jiaheng Wei, Ankit Shah, Zhaowei Zhu, Yaxuan Wang, Chen Qian, Yang Liu, Yujia Bao, Wei Wei
2025	J	`jnl`	Incentivizing High-quality Participation From Federated Learning Agents. CoRR Jinlong Pang, Jiaheng Wei, Yifan Hua, Chen Qian, Yang Liu
2025	A*	`conf`	LLM Unlearning via Loss Adjustment with Only Forget Data. ICLR Yaxuan Wang, Jiaheng Wei, Chris Yuhao Liu, Jinlong Pang, Quan Liu, Ankit Shah, Yujia Bao, Yang Liu, Wei Wei
2025	J	`jnl`	Learning Counterfactual Outcomes Under Rank Preservation. CoRR Peng Wu, Haoxuan Li, Chunyuan Zheng, Yan Zeng, Jiawei Chen, Yang Liu, Ruocheng Guo, Kun Zhang
2025	J	`jnl`	Long-Term Fairness Inquiries and Pursuits in Machine Learning: A Survey of Notions, Methods, and Challenges. Trans. Mach. Learn. Res. Usman Gohar, Zeyu Tang, Jialu Wang, Kun Zhang, Peter Spirtes, Yang Liu, Lu Cheng
2025	—	`conf`	Noise-Resilient Point-wise Anomaly Detection in Time Series Using Weak Segment Labels. KDD (1) Yaxuan Wang, Hao Cheng, Jing Xiong, Qingsong Wen, Han Jia, Ruixuan Song, Liyuan Zhang, Zhaowei Zhu, Yang Liu
2025	J	`jnl`	Noise-Resilient Point-wise Anomaly Detection in Time Series Using Weak Segment Labels. CoRR Yaxuan Wang, Hao Cheng, Jing Xiong, Qingsong Wen, Han Jia, Ruixuan Song, Liyuan Zhang, Zhaowei Zhu, Yang Liu
2025	A*	`conf`	Noisy Test-Time Adaptation in Vision-Language Models. ICLR Chentao Cao, Zhun Zhong, Zhanke Zhou, Tongliang Liu, Yang Liu, Kun Zhang, Bo Han
2025	J	`jnl`	Noisy Test-Time Adaptation in Vision-Language Models. CoRR Chentao Cao, Zhun Zhong, Zhanke Zhou, Tongliang Liu, Yang Liu, Kun Zhang, Bo Han
2025	A	`conf`	Nonparametric Factor Analysis and Beyond. AISTATS Yujia Zheng, Yang Liu, Jiaxiong Yao, Yingyao Hu, Kun Zhang
2025	J	`jnl`	Nonparametric Factor Analysis and Beyond. CoRR Yujia Zheng, Yang Liu, Jiaxiong Yao, Yingyao Hu, Kun Zhang
2025	A*	`conf`	Prompting Fairness: Integrating Causality to Debias Large Language Models. ICLR Jingling Li, Zeyu Tang, Xiaoyu Liu, Peter Spirtes, Kun Zhang, Liu Leqi, Yang Liu
2025	A*	`conf`	Regretful Decisions under Label Noise. ICLR Sujay Nagaraj, Yang Liu, Flávio P. Calmon, Berk Ustun
2025	J	`jnl`	Regretful Decisions under Label Noise. CoRR Sujay Nagaraj, Yang Liu, Flávio P. Calmon, Berk Ustun
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	A	`conf`	To Give or Not to Give? The Impacts of Strategically Withheld Recourse. AISTATS Yatong Chen, Andrew Estornell, Yevgeniy Vorobeychik, Yang Liu
2025	J	`jnl`	To Give or Not to Give? The Impacts of Strategically Withheld Recourse. CoRR Yatong Chen, Andrew Estornell, Yevgeniy Vorobeychik, Yang Liu
2025	A*	`conf`	Token Cleaning: Fine-Grained Data Selection for LLM Supervised Fine-Tuning. ICML Jinlong Pang, Na Di, Zhaowei Zhu, Jiaheng Wei, Hao Cheng, Chen Qian, Yang Liu
2025	J	`jnl`	Token Cleaning: Fine-Grained Data Selection for LLM Supervised Fine-Tuning. CoRR Jinlong Pang, Na Di, Zhaowei Zhu, Jiaheng Wei, Hao Cheng, Chen Qian, Yang Liu
2025	—	`conf`	Toward Optimal LLM Alignments Using Two-Player Games. EMNLP (Findings) Rui Zheng, Hongyi Guo, Zhihan Liu, Xiaoying Zhang, Yuanshun Yao, Xiaojun Xu, Zhaoran Wang, Zhiheng Xi, Tao Gui, Qi Zhang, Xuanjing Huang, Yang Liu, Hang Li
2025	A*	`conf`	Understanding Chain-of-Thought in LLMs through Information Theory. ICML Jean-Francois Ton, Muhammad Faaiz Taufiq, Yang Liu
2024	J	`jnl`	ACC-Debate: An Actor-Critic Approach to Multi-Agent Debate. CoRR Andrew Estornell, Jean-Francois Ton, Yuanshun Yao, Yang Liu
2024	A*	`conf`	Achievable Fairness on Your Data With Utility Guarantees. NeurIPS Muhammad Faaiz Taufiq, Jean-Francois Ton, Yang Liu
2024	J	`jnl`	Addressing Polarization and Unfairness in Performative Prediction. CoRR Kun Jin, Tian Xie, Yang Liu, Xueru Zhang
2024	J	`jnl`	Adversarial Curriculum Graph Contrastive Learning with Pair-wise Augmentation. CoRR Xinjian Zhao, Liang Zhang, Yang Liu, Ruocheng Guo, Xiangyu Zhao
2024	J	`jnl`	Adversarial Machine Unlearning. CoRR Zonglin Di, Sixie Yu, Yevgeniy Vorobeychik, Yang Liu
2024	A*	`conf`	Conformal Counterfactual Inference under Hidden Confounding. KDD Zonghao Chen, Ruocheng Guo, Jean-Francois Ton, Yang Liu
2024	J	`jnl`	Conformal Counterfactual Inference under Hidden Confounding. CoRR Zonghao Chen, Ruocheng Guo, Jean-François Ton, Yang Liu
2024	J	`jnl`	DMLR: Data-centric Machine Learning Research - Past, Present and Future. J. Data-centric Mach. Learn. Res. Luis Oala, Manil Maskey, Lilith Bat-Leah, Alicia Parrish, Nezihe Merve Gürel, Tzu-Sheng Kuo, Yang Liu, Rotem Dror, Danilo Brajovic, Xiaozhe Yao, Max Bartolo, William Gaviria Rojas, Ryan Hileman, Rainier Aliment, Michael W. Mahoney, Meg Risdal, Matthew Lease, Wojciech Samek, Debojyoti Dutta, Curtis G. Northcutt, Cody Coleman, Braden Hancock, Bernard Koch, Girmaw Abebe Tadesse, Bojan Karlas, Ahmed Alaa, Adji Bousso Dieng, Natasha F. Noy, Vijay Janapa Reddi, James Zou, Praveen K. Paritosh, Mihaela van der Schaar, Kurt Bollacker, Lora Aroyo, Ce Zhang, Joaquin Vanschoren, Isabelle Guyon, Peter Mattson
2024	J	`jnl`	Dataset Fairness: Achievable Fairness on Your Data With Utility Guarantees. CoRR Muhammad Faaiz Taufiq, Jean-Francois Ton, Yang Liu
2024	A*	`conf`	Envisioning Outlier Exposure by Large Language Models for Out-of-Distribution Detection. ICML Chentao Cao, Zhun Zhong, Zhanke Zhou, Yang Liu, Tongliang Liu, Bo Han
2024	J	`jnl`	Envisioning Outlier Exposure by Large Language Models for Out-of-Distribution Detection. CoRR Chentao Cao, Zhun Zhong, Zhanke Zhou, Yang Liu, Tongliang Liu, Bo Han
2024	J	`jnl`	Fair Classifiers Without Fair Training: An Influence-Guided Data Sampling Approach. CoRR Jinlong Pang, Jialu Wang, Zhaowei Zhu, Yuanshun Yao, Chen Qian, Yang Liu
2024	A*	`conf`	Fair Classifiers that Abstain without Harm. ICLR Tongxin Yin, Jean-Francois Ton, Ruocheng Guo, Yuanshun Yao, Mingyan Liu, Yang Liu
2024	A*	`conf`	Fair Participation via Sequential Policies. AAAI Reilly Raab, Ross Boczar, Maryam Fazel, Yang Liu
2024	A*	`conf`	Fairness without Harm: An Influence-Guided Active Sampling Approach. NeurIPS Jinlong Pang, Jialu Wang, Zhaowei Zhu, Yuanshun Yao, Chen Qian, Yang Liu
2024	A*	`conf`	FedFixer: Mitigating Heterogeneous Label Noise in Federated Learning. AAAI Xinyuan Ji, Zhaowei Zhu, Wei Xi, Olga Gadyatskaya, Zilong Song, Yong Cai, Yang Liu
2024	J	`jnl`	FedFixer: Mitigating Heterogeneous Label Noise in Federated Learning. CoRR Xinyuan Ji, Zhaowei Zhu, Wei Xi, Olga Gadyatskaya, Zilong Song, Yong Cai, Yang Liu
2024	—	`conf`	Federated Learning with Local Openset Noisy Labels. ECCV (34) Zonglin Di, Zhaowei Zhu, Xiaoxiao Li, Yang Liu
2024	J	`jnl`	Human-Instruction-Free LLM Self-Alignment with Limited Samples. CoRR Hongyi Guo, Yuanshun Yao, Wei Shen, Jiaheng Wei, Xiaoying Zhang, Zhaoran Wang, Yang Liu
2024	J	`jnl`	Improving Data Efficiency via Curating LLM-Driven Rating Systems. CoRR Jinlong Pang, Jiaheng Wei, Ankit Parag Shah, Zhaowei Zhu, Yaxuan Wang, Chen Qian, Yang Liu, Yujia Bao, Wei Wei
2024	J	`jnl`	Improving Reinforcement Learning from Human Feedback Using Contrastive Rewards. CoRR Wei Shen, Xiaoying Zhang, Yuanshun Yao, Rui Zheng, Hongyi Guo, Yang Liu
2024	J	`jnl`	LLM Unlearning via Loss Adjustment with Only Forget Data. CoRR Yaxuan Wang, Jiaheng Wei, Chris Yuhao Liu, Jinlong Pang, Quan Liu, Ankit Parag Shah, Yujia Bao, Yang Liu, Wei Wei
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	A*	`conf`	Large Language Model Unlearning via Embedding-Corrupted Prompts. NeurIPS Chris Yuhao Liu, Yaxuan Wang, Jeffrey Flanigan, Yang Liu
2024	J	`jnl`	Large Language Model Unlearning via Embedding-Corrupted Prompts. CoRR Chris Yuhao Liu, Yaxuan Wang, Jeffrey Flanigan, Yang Liu
2024	A*	`conf`	Learning the Optimal Policy for Balancing Short-Term and Long-Term Rewards. NeurIPS Qinwei Yang, Xueqing Liu, Yan Zeng, Ruocheng Guo, Yang Liu, Peng Wu
2024	J	`jnl`	Learning to Watermark LLM-generated Text via Reinforcement Learning. CoRR Xiaojun Xu, Yuanshun Yao, Yang Liu
2024	J	`jnl`	Long-Term Fairness Inquiries and Pursuits in Machine Learning: A Survey of Notions, Methods, and Challenges. CoRR Usman Gohar, Zeyu Tang, Jialu Wang, Kun Zhang, Peter L. Spirtes, Yang Liu, Lu Cheng
2024	J	`jnl`	Measuring and Reducing LLM Hallucination without Gold-Standard Answers via Expertise-Weighting. CoRR Jiaheng Wei, Yuanshun Yao, Jean-Francois Ton, Hongyi Guo, Andrew Estornell, Yang Liu
2024	J	`jnl`	Mind Scramble: Unveiling Large Language Model Psychology Via Typoglycemia. CoRR Miao Yu, Junyuan Mao, Guibin Zhang, Jingheng Ye, Junfeng Fang, Aoxiao Zhong, Yang Liu, Yuxuan Liang, Kun Wang, Qingsong Wen
2024	A*	`conf`	Mitigating Reward Overoptimization via Lightweight Uncertainty Estimation. NeurIPS Xiaoying Zhang, Jean-Francois Ton, Wei Shen, Hongning Wang, Yang Liu
2024	A*	`conf`	Multi-LLM Debate: Framework, Principals, and Interventions. NeurIPS Andrew Estornell, Yang Liu
2024	A*	`conf`	Multifaceted Reformulations for Null & Low queries and its parallelism with Counterfactuals. ICDE Jayanth Yetukuri, Yuyan Wang, Ishita K. Khan, Liyang Hao, Zhe Wu, Yang Liu
2024	J	`jnl`	Overcoming Reward Overoptimization via Adversarial Policy Optimization with Lightweight Uncertainty Estimation. CoRR Xiaoying Zhang, Jean-Francois Ton, Wei Shen, Hongning Wang, Yang Liu
2024	A*	`conf`	Performative Federated Learning: A Solution to Model-Dependent and Heterogeneous Distribution Shifts. AAAI Kun Jin, Tongxin Yin, Zhongzhu Chen, Zeyu Sun, Xueru Zhang, Yang Liu, Mingyan Liu
2024	A*	`conf`	Performative Prediction with Bandit Feedback: Learning through Reparameterization. ICML Yatong Chen, Wei Tang, Chien-Ju Ho, Yang Liu
2024	A*	`conf`	Post-hoc bias scoring is optimal for fair classification. ICLR Wenlong Chen, Yegor Klochkov, Yang Liu
2024	A*	`conf`	Procedural Fairness Through Decoupling Objectionable Data Generating Components. ICLR Zeyu Tang, Jialu Wang, Yang Liu, Peter Spirtes, Kun Zhang
2024	A*	`conf`	Providing Fair Recourse over Plausible Groups. AAAI Jayanth Yetukuri, Ian Hardy, Yevgeniy Vorobeychik, Berk Ustun, Yang Liu
2024	A*	`conf`	Retention Depolarization in Recommender System. WWW Xiaoying Zhang, Hongning Wang, Yang Liu
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	A*	`conf`	RobustTSF: Towards Theory and Design of Robust Time Series Forecasting with Anomalies. ICLR Hao Cheng, Qingsong Wen, Yang Liu, Liang Sun
2024	J	`jnl`	RobustTSF: Towards Theory and Design of Robust Time Series Forecasting with Anomalies. CoRR Hao Cheng, Qingsong Wen, Yang Liu, Liang Sun
2024	J	`jnl`	Steering LLMs Towards Unbiased Responses: A Causality-Guided Debiasing Framework. CoRR Jingling Li, Zeyu Tang, Xiaoyu Liu, Peter Spirtes, Kun Zhang, Liu Leqi, Yang Liu
2024	J	`jnl`	Toward Optimal LLM Alignments Using Two-Player Games. CoRR Rui Zheng, Hongyi Guo, Zhihan Liu, Xiaoying Zhang, Yuanshun Yao, Xiaojun Xu, Zhaoran Wang, Zhiheng Xi, Tao Gui, Qi Zhang, Xuanjing Huang, Hang Li, Yang Liu
2024	J	`jnl`	Understanding Chain-of-Thought in LLMs through Information Theory. CoRR Jean-Francois Ton, Muhammad Faaiz Taufiq, Yang Liu
2024	A*	`conf`	Unmasking and Improving Data Credibility: A Study with Datasets for Training Harmless Language Models. ICLR Zhaowei Zhu, Jialu Wang, Hao Cheng, Yang Liu
2024	J	`jnl`	User-Creator Feature Dynamics in Recommender Systems with Dual Influence. CoRR Tao Lin, Kun Jin, Andrew Estornell, Xiaoying Zhang, Yiling Chen, Yang Liu
2024	A*	`conf`	User-Creator Feature Polarization in Recommender Systems with Dual Influence. NeurIPS Tao Lin, Kun Jin, Andrew Estornell, Xiaoying Zhang, Yiling Chen, Yang Liu
2023	A	`conf`	4th Crowd Science Workshop - CANDLE: Collaboration of Humans and Learning Algorithms for Data Labeling. WSDM Dmitry Ustalov, Saiph Savage, Niels van Berkel, Yang Liu
2023	J	`jnl`	A Parametrical Model for Instance-Dependent Label Noise. IEEE Trans. Pattern Anal. Mach. Intell. Shuo Yang, Songhua Wu, Erkun Yang, Bo Han, Yang Liu, Min Xu, Gang Niu, Tongliang Liu
2023	C	`conf`	Adaptive Adversarial Training Does Not Increase Recourse Costs. AIES Ian Hardy, Jayanth Yetukuri, Yang Liu
2023	J	`jnl`	Adaptive Adversarial Training Does Not Increase Recourse Costs. CoRR Ian Hardy, Jayanth Yetukuri, Yang Liu
2023	—	`conf`	Auditing for Federated Learning: A Model Elicitation Approach. DAI Yang Liu, Rixing Lou, Jiaheng Wei
2023	J	`jnl`	DMLR: Data-centric Machine Learning Research - Past, Present and Future. CoRR Luis Oala, Manil Maskey, Lilith Bat-Leah, Alicia Parrish, Nezihe Merve Gürel, Tzu-Sheng Kuo, Yang Liu, Rotem Dror, Danilo Brajovic, Xiaozhe Yao, Max Bartolo, William Gaviria Rojas, Ryan Hileman, Rainier Aliment, Michael W. Mahoney, Meg Risdal, Matthew Lease, Wojciech Samek, Debojyoti Dutta, Curtis G. Northcutt, Cody Coleman, Braden Hancock, Bernard Koch, Girmaw Abebe Tadesse, Bojan Karlas, Ahmed M. Alaa, Adji Bousso Dieng, Natasha F. Noy, Vijay Janapa Reddi, James Zou, Praveen K. Paritosh, Mihaela van der Schaar, Kurt Bollacker, Lora Aroyo, Ce Zhang, Joaquin Vanschoren, Isabelle Guyon, Peter Mattson
2023	A*	`conf`	Debiasing Recommendation by Learning Identifiable Latent Confounders. KDD Qing Zhang, Xiaoying Zhang, Yang Liu, Hongning Wang, Min Gao, Jiheng Zhang, Ruocheng Guo
2023	J	`jnl`	Debiasing Recommendation by Learning Identifiable Latent Confounders. CoRR Qing Zhang, Xiaoying Zhang, Yang Liu, Hongning Wang, Min Gao, Jiheng Zhang, Ruocheng Guo
2023	J	`jnl`	Deep Concept Removal. CoRR Yegor Klochkov, Jean-Francois Ton, Ruocheng Guo, Yang Liu, Hang Li
2023	A*	`conf`	Distributionally Robust Post-hoc Classifiers under Prior Shifts. ICLR Jiaheng Wei, Harikrishna Narasimhan, Ehsan Amid, Wen-Sheng Chu, Yang Liu, Abhishek Kumar
2023	J	`jnl`	Distributionally Robust Post-hoc Classifiers under Prior Shifts. CoRR Jiaheng Wei, Harikrishna Narasimhan, Ehsan Amid, Wen-Sheng Chu, Yang Liu, Abhishek Kumar
2023	J	`jnl`	Do humans and machines have the same eyes? Human-machine perceptual differences on image classification. CoRR Minghao Liu, Jiaheng Wei, Yang Liu, James Davis
2023	J	`jnl`	Fair Classifiers that Abstain without Harm. CoRR Tongxin Yin, Jean-François Ton, Ruocheng Guo, Yuanshun Yao, Mingyan Liu, Yang Liu
2023	J	`jnl`	Fair Learning to Rank with Distribution-free Risk Control. CoRR Ruocheng Guo, Jean-François Ton, Yang 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	—	`conf`	Group-Fair Classification with Strategic Agents. FAccT Andrew Estornell, Sanmay Das, Yang Liu, Yevgeniy Vorobeychik
2023	A*	`conf`	Identifiability of Label Noise Transition Matrix. ICML Yang Liu, Hao Cheng, Kun Zhang
2023	A*	`conf`	Incentivizing Recourse through Auditing in Strategic Classification. IJCAI Andrew Estornell, Yatong Chen, Sanmay Das, Yang Liu, Yevgeniy Vorobeychik
2023	J	`jnl`	Large Language Model Unlearning. CoRR Yuanshun Yao, Xiaojun Xu, Yang Liu
2023	J	`jnl`	Learning to Incentivize Improvements from Strategic Agents. Trans. Mach. Learn. Res. Yatong Chen, Jialu Wang, Yang Liu
2023	A*	`conf`	Long-Term Fairness with Unknown Dynamics. NeurIPS Tongxin Yin, Reilly Raab, Mingyan Liu, Yang Liu
2023	J	`jnl`	Long-Term Fairness with Unknown Dynamics. CoRR Tongxin Yin, Reilly Raab, Mingyan Liu, Yang Liu
2023	J	`jnl`	Machine truth serum: a surprisingly popular approach to improving ensemble methods. Mach. Learn. Tianyi Luo, Yang Liu
2023	A*	`conf`	Mitigating Memorization of Noisy Labels via Regularization between Representations. ICLR Hao Cheng, Zhaowei Zhu, Xing Sun, Yang Liu
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	A*	`conf`	Model Transferability with Responsive Decision Subjects. ICML Yatong Chen, Zeyu Tang, Kun Zhang, Yang Liu
2023	J	`jnl`	Performative Federated Learning: A Solution to Model-Dependent and Heterogeneous Distribution Shifts. CoRR Kun Jin, Tongxin Yin, Zhongzhu Chen, Zeyu Sun, Xueru Zhang, Yang Liu, Mingyan Liu
2023	J	`jnl`	Performative Prediction with Bandit Feedback: Learning through Reparameterization. CoRR Yatong Chen, Wei Tang, Chien-Ju Ho, Yang Liu
2023	J	`jnl`	Post-hoc Bias Scoring Is Optimal For Fair Classification. CoRR Wenlong Chen, Yegor Klochkov, Yang Liu
2023	J	`jnl`	Procedural Fairness Through Decoupling Objectionable Data Generating Components. CoRR Zeyu Tang, Jialu Wang, Yang Liu, Peter Spirtes, Kun Zhang
2023	—	`ed.`	Proceedings of the 4th Crowd Science Workshop on Collaboration of Humans and Learning Algorithms for Data Labeling co-located with ACM International WSDM Conference (WSDM 2023), Singapore, March 3, 2023. CSW@WSDM Dmitry Ustalov, Saiph Savage, Niels van Berkel, Yang Liu, Alisa Smirnova
2023	—	`conf`	T2IAT: Measuring Valence and Stereotypical Biases in Text-to-Image Generation. ACL (Findings) Jialu Wang, Xinyue Liu, Zonglin Di, Yang Liu, Xin Eric Wang
2023	J	`jnl`	T2IAT: Measuring Valence and Stereotypical Biases in Text-to-Image Generation. CoRR Jialu Wang, Xinyue Gabby Liu, Zonglin Di, Yang Liu, Xin Eric Wang
2023	A*	`conf`	The Importance of Human-Labeled Data in the Era of LLMs. IJCAI Yang Liu
2023	J	`jnl`	The Importance of Human-Labeled Data in the Era of LLMs. CoRR Yang Liu
2023	A*	`conf`	Tier Balancing: Towards Dynamic Fairness over Underlying Causal Factors. ICLR Zeyu Tang, Yatong Chen, Yang Liu, Kun Zhang
2023	J	`jnl`	Tier Balancing: Towards Dynamic Fairness over Underlying Causal Factors. CoRR Zeyu Tang, Yatong Chen, Yang Liu, Kun Zhang
2023	—	`conf`	To Aggregate or Not? Learning with Separate Noisy Labels. CSW@WSDM Jiaheng Wei, Zhaowei Zhu, Tianyi Luo, Ehsan Amid, Abhishek Kumar, Yang Liu
2023	A*	`conf`	To Aggregate or Not? Learning with Separate Noisy Labels. KDD Jiaheng Wei, Zhaowei Zhu, Tianyi Luo, Ehsan Amid, Abhishek Kumar, Yang Liu
2023	C	`conf`	Towards User Guided Actionable Recourse. AIES Jayanth Yetukuri, Ian Hardy, Yang Liu
2023	J	`jnl`	Towards User Guided Actionable Recourse. CoRR Jayanth Yetukuri, Ian Hardy, Yang Liu
2023	J	`jnl`	Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' Alignment. CoRR Yang Liu, Yuanshun Yao, Jean-Francois Ton, Xiaoying Zhang, Ruocheng Guo, Hao Cheng, Yegor Klochkov, Muhammad Faaiz Taufiq, Hang Li
2023	A*	`conf`	Uncertainty-Aware Instance Reweighting for Off-Policy Learning. NeurIPS Xiaoying Zhang, Junpu Chen, Hongning Wang, Hong Xie, Yang Liu, John C. S. Lui, Hang Li
2023	J	`jnl`	Understanding Unfairness via Training Concept Influence. CoRR Yuanshun Yao, Yang Liu
2023	J	`jnl`	Unmasking and Improving Data Credibility: A Study with Datasets for Training Harmless Language Models. CoRR Zhaowei Zhu, Jialu Wang, Hao Cheng, Yang Liu
2023	A*	`conf`	Weak Proxies are Sufficient and Preferable for Fairness with Missing Sensitive Attributes. ICML Zhaowei Zhu, Yuanshun Yao, Jiankai Sun, Hang Li, Yang Liu
2022	A*	`conf`	Adaptive Data Debiasing through Bounded Exploration. NeurIPS Yifan Yang, Yang Liu, Parinaz Naghizadeh
2022	—	`conf`	Assessing Multilingual Fairness in Pre-trained Multimodal Representations. ACL (Findings) Jialu Wang, Yang Liu, Xin Eric Wang
2022	A*	`conf`	Beyond Images: Label Noise Transition Matrix Estimation for Tasks with Lower-Quality Features. ICML Zhaowei Zhu, Jialu Wang, Yang Liu
2022	J	`jnl`	Beyond Images: Label Noise Transition Matrix Estimation for Tasks with Lower-Quality Features. CoRR Zhaowei Zhu, Jialu Wang, Yang Liu
2022	A*	`conf`	Certifying Some Distributional Fairness with Subpopulation Decomposition. NeurIPS Mintong Kang, Linyi Li, Maurice Weber, Yang Liu, Ce Zhang, Bo Li
2022	J	`jnl`	Certifying Some Distributional Fairness with Subpopulation Decomposition. CoRR Mintong Kang, Linyi Li, Maurice Weber, Yang Liu, Ce Zhang, Bo Li
2022	J	`jnl`	Conjugate Natural Selection. CoRR Reilly Raab, Luca de Alfaro, Yang Liu
2022	A*	`conf`	Detecting Corrupted Labels Without Training a Model to Predict. ICML Zhaowei Zhu, Zihao Dong, Yang Liu
2022	—	`conf`	DuelGAN: A Duel Between Two Discriminators Stabilizes the GAN Training. ECCV (23) Jiaheng Wei, Minghao Liu, Jiahao Luo, Andrew Zhu, James Davis, Yang Liu
2022	A*	`conf`	Estimating Instance-dependent Bayes-label Transition Matrix using a Deep Neural Network. ICML Shuo Yang, Erkun Yang, Bo Han, Yang Liu, Min Xu, Gang Niu, Tongliang Liu
2022	J	`jnl`	Evaluating Fairness Without Sensitive Attributes: A Framework Using Only Auxiliary Models. CoRR Zhaowei Zhu, Yuanshun Yao, Jiankai Sun, Yang Liu, Hang Li
2022	—	`conf`	Fair Classification with Instance-dependent Label Noise. CLeaR Songhua Wu, Mingming Gong, Bo Han, Yang Liu, Tongliang Liu
2022	A*	`conf`	Fairness Transferability Subject to Bounded Distribution Shift. NeurIPS Yatong Chen, Reilly Raab, Jialu Wang, Yang Liu
2022	J	`jnl`	Fairness Transferability Subject to Bounded Distribution Shift. CoRR Yatong Chen, Reilly Raab, Jialu Wang, Yang Liu
2022	J	`jnl`	Identifiability of Label Noise Transition Matrix. CoRR Yang Liu
2022	—	`conf`	Interpretable Research Replication Prediction via Variational Contextual Consistency Sentence Masking. ACL (Findings) Tianyi Luo, Rui Meng, Xin Wang, Yang Liu
2022	J	`jnl`	Interpretable Research Replication Prediction via Variational Contextual Consistency Sentence Masking. CoRR Tianyi Luo, Rui Meng, Xin Eric Wang, Yang Liu
2022	A	`conf`	Learning and Mining with Noisy Labels. CIKM Masashi Sugiyama, Tongliang Liu, Bo Han, Yang Liu, Gang Niu
2022	A*	`conf`	Learning with Noisy Labels Revisited: A Study Using Real-World Human Annotations. ICLR Jiaheng Wei, Zhaowei Zhu, Hao Cheng, Tongliang Liu, Gang Niu, Yang Liu
2022	B	`conf`	Low-light Image Enhancement Using Chain-consistent Adversarial Networks. ICPR Minghao Liu, Jiahao Luo, Xiaohan Zhang, Yang Liu, James Davis
2022	A*	`conf`	Metric-Fair Classifier Derandomization. ICML Jimmy Wu, Yatong Chen, Yang Liu
2022	J	`jnl`	Metric-Fair Classifier Derandomization. CoRR Jimmy Wu, Yatong Chen, Yang Liu
2022	B	`conf`	Robust Stochastic Bandit algorithms to defend against Oracle attack using Sample Dropout. IEEE Big Data Jayanth Yetukuri, Yang Liu
2022	J	`jnl`	Surrogate Scoring Rules. ACM Trans. Economics and Comput. Yang Liu, Juntao Wang, Yiling Chen
2022	A*	`conf`	The Rich Get Richer: Disparate Impact of Semi-Supervised Learning. ICLR Zhaowei Zhu, Tianyi Luo, Yang Liu
2022	J	`jnl`	To Aggregate or Not? Learning with Separate Noisy Labels. CoRR Jiaheng Wei, Zhaowei Zhu, Tianyi Luo, Ehsan Amid, Abhishek Kumar, Yang Liu
2022	A*	`conf`	To Smooth or Not? When Label Smoothing Meets Noisy Labels. ICML Jiaheng Wei, Hangyu Liu, Tongliang Liu, Gang Niu, Masashi Sugiyama, Yang Liu
2022	A*	`conf`	Understanding Instance-Level Impact of Fairness Constraints. ICML Jialu Wang, Xin Eric Wang, Yang Liu
2022	J	`jnl`	Understanding Instance-Level Impact of Fairness Constraints. CoRR Jialu Wang, Xin Eric Wang, Yang Liu
2021	J	`jnl`	A Good Representation Detects Noisy Labels. CoRR Zhaowei Zhu, Zihao Dong, Yang Liu
2021	A*	`conf`	A Second-Order Approach to Learning With Instance-Dependent Label Noise. CVPR Zhaowei Zhu, Tongliang Liu, Yang Liu
2021	J	`jnl`	Adaptive Data Debiasing through Bounded Exploration and Fairness. CoRR Yifan Yang, Yang Liu, Parinaz Naghizadeh
2021	—	`conf`	Are Gender-Neutral Queries Really Gender-Neutral? Mitigating Gender Bias in Image Search. EMNLP (1) Jialu Wang, Yang Liu, Xin Eric Wang
2021	J	`jnl`	Are Gender-Neutral Queries Really Gender-Neutral? Mitigating Gender Bias in Image Search. CoRR Jialu Wang, Yang Liu, Xin Eric Wang
2021	J	`jnl`	Assessing Multilingual Fairness in Pre-trained Multimodal Representations. CoRR Jialu Wang, Yang Liu, Xin Eric Wang
2021	A*	`conf`	Bandit Learning with Delayed Impact of Actions. NeurIPS Wei Tang, Chien-Ju Ho, Yang Liu
2021	A*	`conf`	Can Less be More? When Increasing-to-Balancing Label Noise Rates Considered Beneficial. NeurIPS Yang Liu, Jialu Wang
2021	J	`jnl`	Can Less be More? When Increasing-to-Balancing Label Noise Rates Considered Beneficial. CoRR Yang Liu, Jialu Wang
2021	A*	`conf`	Clusterability as an Alternative to Anchor Points When Learning with Noisy Labels. ICML Zhaowei Zhu, Yiwen Song, Yang Liu
2021	J	`jnl`	Clusterability as an Alternative to Anchor Points When Learning with Noisy Labels. CoRR Zhaowei Zhu, Yiwen Song, Yang Liu
2021	J	`jnl`	Demystifying How Self-Supervised Features Improve Training from Noisy Labels. CoRR Hao Cheng, Zhaowei Zhu, Xing Sun, Yang Liu
2021	J	`jnl`	Estimating Instance-dependent Label-noise Transition Matrix using DNNs. CoRR Shuo Yang, Erkun Yang, Bo Han, Yang Liu, Min Xu, Gang Niu, Tongliang Liu
2021	—	`conf`	Fair Classification with Group-Dependent Label Noise. FAccT Jialu Wang, Yang Liu, Caleb C. Levy
2021	—	`conf`	Federated Bandit: A Gossiping Approach. SIGMETRICS (Abstracts) Zhaowei Zhu, Jingxuan Zhu, Ji Liu, Yang Liu
2021	J	`jnl`	Federated Bandit: A Gossiping Approach. Proc. ACM Meas. Anal. Comput. Syst. Zhaowei Zhu, Jingxuan Zhu, Ji Liu, Yang Liu
2021	B	`conf`	Forecast Aggregation via Peer Prediction. HCOMP Juntao Wang, Yang Liu, Yiling Chen
2021	J	`jnl`	Induced Domain Adaptation. CoRR Yang Liu, Yatong Chen, Jiaheng Wei
2021	A*	`conf`	Learning with Instance-Dependent Label Noise: A Sample Sieve Approach. ICLR Hao Cheng, Zhaowei Zhu, Xingyu Li, Yifei Gong, Xing Sun, Yang Liu
2021	J	`jnl`	Learning with Noisy Labels Revisited: A Study Using Real-World Human Annotations. CoRR Jiaheng Wei, Zhaowei Zhu, Hao Cheng, Tongliang Liu, Gang Niu, Yang Liu
2021	A	`conf`	Linear Models are Robust Optimal Under Strategic Behavior. AISTATS Wei Tang, Chien-Ju Ho, Yang Liu
2021	J	`jnl`	Optimal Query Complexity of Secure Stochastic Convex Optimization. CoRR Wei Tang, Chien-Ju Ho, Yang Liu
2021	J	`jnl`	PeerGAN: Generative Adversarial Networks with a Competing Peer Discriminator. CoRR Jiaheng Wei, Minghao Liu, Jiahao Luo, Qiutong Li, James Davis, Yang Liu
2021	A*	`conf`	Policy Learning Using Weak Supervision. NeurIPS Jingkang Wang, Hongyi Guo, Zhaowei Zhu, Yang Liu
2021	A	`conf`	Sample Elicitation. AISTATS Jiaheng Wei, Zuyue Fu, Yang Liu, Xingyu Li, Zhuoran Yang, Zhaoran Wang
2021	J	`jnl`	The Rich Get Richer: Disparate Impact of Semi-Supervised Learning. CoRR Zhaowei Zhu, Tianyi Luo, Yang Liu
2021	J	`jnl`	Understanding (Generalized) Label Smoothing when Learning with Noisy Labels. CoRR Jiaheng Wei, Hangyu Liu, Tongliang Liu, Gang Niu, Yang Liu
2021	A*	`conf`	Understanding Instance-Level Label Noise: Disparate Impacts and Treatments. ICML Yang Liu
2021	J	`jnl`	Unfairness Despite Awareness: Group-Fair Classification with Strategic Agents. CoRR Andrew Estornell, Sanmay Das, Yang Liu, Yevgeniy Vorobeychik
2021	A*	`conf`	Unintended Selection: Persistent Qualification Rate Disparities and Interventions. NeurIPS Reilly Raab, Yang Liu
2021	J	`jnl`	Unintended Selection: Persistent Qualification Rate Disparities and Interventions. CoRR Reilly Raab, Yang Liu
2021	A*	`conf`	When Optimizing f-Divergence is Robust with Label Noise. ICLR Jiaheng Wei, Yang Liu
2020	J	`jnl`	A Second-Order Approach to Learning with Instance-Dependent Label Noise. CoRR Zhaowei Zhu, Tongliang Liu, Yang Liu
2020	A	`conf`	Differentially Private Contextual Dynamic Pricing. AAMAS Wei Tang, Chien-Ju Ho, Yang Liu
2020	J	`jnl`	Distributed learning of average belief over networks using sequential observations. Autom. Kaiqing Zhang, Yang Liu, Ji Liu, Mingyan Liu, Tamer Basar
2020	J	`jnl`	Distributional Individual Fairness in Clustering. CoRR Nihesh Anderson, Suman K. Bera, Syamantak Das, Yang Liu
2020	J	`jnl`	Fair Bandit Learning with Delayed Impact of Actions. CoRR Wei Tang, Chien-Ju Ho, Yang Liu
2020	J	`jnl`	Fair Classification with Group-Dependent Label Noise. CoRR Jialu Wang, Yang Liu, Caleb C. Levy
2020	J	`jnl`	Federated Bandit: A Gossiping Approach. CoRR Zhaowei Zhu, Jingxuan Zhu, Ji Liu, Yang Liu
2020	J	`jnl`	How Do Fair Decisions Fare in Long-term Qualification? CoRR Xueru Zhang, Ruibo Tu, Yang Liu, Mingyan Liu, Hedvig Kjellström, Kun Zhang, Cheng Zhang
2020	A*	`conf`	How do fair decisions fare in long-term qualification? NeurIPS Xueru Zhang, Ruibo Tu, Yang Liu, Mingyan Liu, Hedvig Kjellström, Kun Zhang, Cheng Zhang
2020	J	`jnl`	How do fairness definitions fare? Testing public attitudes towards three algorithmic definitions of fairness in loan allocations. Artif. Intell. Nripsuta Ani Saxena, Karen Huang, Evan DeFilippis, Goran Radanovic, David C. Parkes, Yang Liu
2020	J	`jnl`	Incentives for Federated Learning: a Hypothesis Elicitation Approach. CoRR Yang Liu, Jiaheng Wei
2020	A*	`conf`	Learning Strategy-Aware Linear Classifiers. NeurIPS Yiling Chen, Yang Liu, Chara Podimata
2020	J	`jnl`	Learning with Instance-Dependent Label Noise: A Sample Sieve Approach. CoRR Hao Cheng, Zhaowei Zhu, Xingyu Li, Yifei Gong, Xing Sun, Yang Liu
2020	A	`conf`	Online Learning Using Only Peer Prediction. AISTATS Yang Liu, David P. Helmbold
2020	A*	`conf`	Optimal Query Complexity of Secure Stochastic Convex Optimization. NeurIPS Wei Tang, Chien-Ju Ho, Yang Liu
2020	A*	`conf`	Peer Loss Functions: Learning from Noisy Labels without Knowing Noise Rates. ICML Yang Liu, Hongyi Guo
2020	J	`jnl`	Policy Learning Using Weak Supervision. CoRR Jingkang Wang, Hongyi Guo, Zhaowei Zhu, Yang Liu
2020	A*	`conf`	Reinforcement Learning with Perturbed Rewards. AAAI Jingkang Wang, Yang Liu, Bo Li
2020	J	`jnl`	Replication Markets: Results, Lessons, Challenges and Opportunities in AI Replication. CoRR Yang Liu, Michael Gordon, Juntao Wang, Michael Bishop, Yiling Chen, Thomas Pfeiffer, Charles Twardy, Domenico Viganola
2020	—	`conf`	Research Replication Prediction Using Weakly Supervised Learning. EMNLP (Findings) Tianyi Luo, Xingyu Li, Hainan Wang, Yang Liu
2020	J	`jnl`	Strategic Recourse in Linear Classification. CoRR Yatong Chen, Jialu Wang, Yang Liu
2020	A*	`conf`	Surrogate Scoring Rules. EC Yang Liu, Juntao Wang, Yiling Chen
2020	J	`jnl`	When Optimizing f-divergence is Robust with Label Noise. CoRR Jiaheng Wei, Yang Liu
2019	—	`conf`	Actionable Recourse in Linear Classification. FAT Berk Ustun, Alexander Spangher, Yang Liu
2019	A*	`conf`	Bayesian Fairness. AAAI Christos Dimitrakakis, Yang Liu, David C. Parkes, Goran Radanovic
2019	J	`jnl`	Credible Sample Elicitation by Deep Learning, for Deep Learning. CoRR Yang Liu, Zuyue Fu, Zhuoran Yang, Zhaoran Wang
2019	A*	`conf`	Fairness without Harm: Decoupled Classifiers with Preference Guarantees. ICML Berk Ustun, Yang Liu, David C. Parkes
2019	J	`jnl`	Forecast Aggregation via Peer Prediction. CoRR Juntao Wang, Yang Liu, Yiling Chen
2019	J	`jnl`	Grinding the Space: Learning to Classify Against Strategic Agents. CoRR Yiling Chen, Yang Liu, Chara Podimata
2019	C	`conf`	How Do Fairness Definitions Fare?: Examining Public Attitudes Towards Algorithmic Definitions of Fairness. AIES Nripsuta Ani Saxena, Karen Huang, Evan DeFilippis, Goran Radanovic, David C. Parkes, Yang Liu
2019	J	`jnl`	Machine Truth Serum. CoRR Tianyi Luo, Yang Liu
2019	J	`jnl`	Online Learning Using Only Peer Assessment. CoRR Yang Liu, David P. Helmbold
2019	J	`jnl`	Peer Loss Functions: Learning from Noisy Labels without Knowing Noise Rates. CoRR Yang Liu, Hongyi Guo
2019	A*	`conf`	Randomized Wagering Mechanisms. AAAI Yiling Chen, Yang Liu, Juntao Wang
2018	J	`jnl`	Actionable Recourse in Linear Classification. CoRR Berk Ustun, Alexander Spangher, Yang Liu
2018	A	`conf`	Active Information Acquisition for Linear Optimization. UAI Shuran Zheng, Bo Waggoner, Yang Liu, Yiling Chen
2018	—	`conf`	Differentially Private Gossip Gradient Descent. CDC Yang Liu, Ji Liu, Tamer Basar
2018	J	`jnl`	Distributed Learning of Average Belief Over Networks Using Sequential Observations. CoRR Kaiqing Zhang, Yang Liu, Ji Liu, Mingyan Liu, Tamer Basar
2018	A*	`conf`	From Patching Delays to Infection Symptoms: Using Risk Profiles for an Early Discovery of Vulnerabilities Exploited in the Wild. USENIX Security Symposium Chaowei Xiao, Armin Sarabi, Yang Liu, Bo Li, Mingyan Liu, Tudor Dumitras
2018	A	`conf`	Gossip Gradient Descent. AAMAS Yang Liu, Ji Liu, Tamer Basar
2018	J	`jnl`	How Do Fairness Definitions Fare? Examining Public Attitudes Towards Algorithmic Definitions of Fairness. CoRR Nripsuta Saxena, Karen Huang, Evan DeFilippis, Goran Radanovic, David C. Parkes, Yang Liu
2018	A*	`conf`	Incentivizing High Quality User Contributions: New Arm Generation in Bandit Learning. AAAI Yang Liu, Chien-Ju Ho
2018	A*	`conf`	Inference Aided Reinforcement Learning for Incentive Mechanism Design in Crowdsourcing. NeurIPS Zehong Hu, Yitao Liang, Jie Zhang, Zhao Li, Yang Liu
2018	J	`jnl`	Inference Aided Reinforcement Learning for Incentive Mechanism Design in Crowdsourcing. CoRR Zehong Hu, Yitao Liang, Yang Liu, Jie Zhang
2018	J	`jnl`	Randomized Wagering Mechanisms. CoRR Yiling Chen, Yang Liu, Juntao Wang
2018	J	`jnl`	Reinforcement Learning with Perturbed Rewards. CoRR Jingkang Wang, Yang Liu, Bo Li
2018	J	`jnl`	Surrogate Scoring Rules and a Dominant Truth Serum for Information Elicitation. CoRR Yang Liu, Yiling Chen
2018	J	`jnl`	To regularize or not: Revisiting SGD with simple algorithms and experimental studies. Expert Syst. Appl. Wenwu He, Yang Liu
2017	J	`jnl`	A Note on the Unification of Adaptive Online Learning. IEEE Trans. Neural Networks Learn. Syst. Wenwu He, James Tin-Yau Kwok, Ji Zhu, Yang Liu
2017	J	`jnl`	Active Information Acquisition for Linear Optimization. CoRR Shuran Zheng, Bo Waggoner, Yang Liu, Yiling Chen
2017	J	`jnl`	An Online Learning Approach to Improving the Quality of Crowd-Sourcing. IEEE/ACM Trans. Netw. Yang Liu, Mingyan Liu
2017	—	`conf`	An approach to distributed parametric learning with streaming data. CDC Ji Liu, Yang Liu, Angelia Nedic, Tamer Basar
2017	J	`jnl`	Calibrated Fairness in Bandits. CoRR Yang Liu, Goran Radanovic, Christos Dimitrakakis, Debmalya Mandal, David C. Parkes
2017	A*	`conf`	Crowd Learning: Improving Online Decision Making Using Crowdsourced Data. IJCAI Yang Liu, Mingyan Liu
2017	C	`conf`	Distributed belief averaging using sequential observations. ACC Yang Liu, Ji Liu, Tamer Basar, Mingyan Liu
2017	A	`conf`	Fair Optimal Stopping Policy for Matching with Mediator. UAI Yang Liu
2017	A*	`conf`	Machine-Learning Aided Peer Prediction. EC Yang Liu, Yiling Chen
2017	A*	`conf`	Sequential Peer Prediction: Learning to Elicit Effort using Posted Prices. AAAI Yang Liu, Yiling Chen
2017	J	`jnl`	Subjective fairness: Fairness is in the eye of the beholder. CoRR Christos Dimitrakakis, Yang Liu, David C. Parkes, Goran Radanovic
2016	—	`conf`	A Bandit Framework for Strategic Regression. NIPS Yang Liu, Yiling Chen
2016	A*	`conf`	Finding One's Best Crowd: Online Learning By Exploiting Source Similarity. AAAI Yang Liu, Mingyan Liu
2016	A*	`conf`	Learning to Incentivize: Eliciting Effort via Output Agreement. IJCAI Yang Liu, Yiling Chen
2016	J	`jnl`	Learning to Incentivize: Eliciting Effort via Output Agreement. CoRR Yang Liu, Yiling Chen
2016	J	`jnl`	Risky business: Fine-grained data breach prediction using business profiles. J. Cybersecur. Armin Sarabi, Parinaz Naghizadeh, Yang Liu, Mingyan Liu
2016	J	`jnl`	Sequential Peer Prediction: Learning to Elicit Effort using Posted Prices. CoRR Yang Liu, Yiling Chen
2015	—	`conf`	A regulated oligopoly multi-market model for trading smart data. INFOCOM Workshops Shang-Pin Sheng, Yang Liu, Mingyan Liu
2015	B	`conf`	An Online Approach to Dynamic Channel Access and Transmission Scheduling. MobiHoc Yang Liu, Mingyan Liu
2015	J	`jnl`	An Online Approach to Dynamic Channel Access and Transmission Scheduling. CoRR Yang Liu, Mingyan Liu
2015	A*	`conf`	An Online Learning Approach to Improving the Quality of Crowd-Sourcing. SIGMETRICS Yang Liu, Mingyan Liu
2015	A*	`conf`	Cloudy with a Chance of Breach: Forecasting Cyber Security Incidents. USENIX Security Symposium Yang Liu, Armin Sarabi, Jing Zhang, Parinaz Naghizadeh, Manish Karir, Michael D. Bailey, Mingyan Liu
2015	Misc	`conf`	Detecting hidden cliques from noisy observations. ICASSP Yang Liu, Mingyan Liu
2015	J	`jnl`	Optimal Relay Selection with Non-negligible Probing Time. CoRR Yang Liu, Yi Ouyang, Mingyan Liu
2015	—	`conf`	Optimal relay selection with non-negligible probing time. ICC Yang Liu, Yi Ouyang, Mingyan Liu
2015	—	`conf`	Predicting Cyber Security Incidents Using Feature-Based Characterization of Network-Level Malicious Activities. IWSPA@CODASPY Yang Liu, Jing Zhang, Armin Sarabi, Mingyan Liu, Manish Karir, Michael D. Bailey
2015	—	`conf`	Prioritizing Security Spending: A Quantitative Analysis of Risk Distributions for Different Business Profiles. WEIS Armin Sarabi, Parinaz Naghizadeh, Yang Liu, Mingyan Liu
2015	J	`jnl`	To Stay or To Switch: Multiuser Multi-Channel Dynamic Access. IEEE Trans. Mob. Comput. Yang Liu, Mingyan Liu
2014	B	`conf`	Detecting hidden propagation structure and its application to analyzing phishing. DSAA Yang Liu, Mingyan Liu
2014	B	`conf`	Revisiting optimal power control: Dual effects of SNR and contention. WiOpt Yang Liu, Mingyan Liu, Jing Deng
2014	J	`jnl`	Sufficient Conditions on the Optimality of Myopic Sensing in Opportunistic Channel Access: A Unifying Framework. IEEE Trans. Inf. Theory Yang Liu, Mingyan Liu, Sahand Haji Ali Ahmad
2013	J	`jnl`	Evaluating Opportunistic Multi-Channel MAC: Is Diversity Gain Worth the Pain? IEEE J. Sel. Areas Commun. Yang Liu, Mingyan Liu, Jing Deng
2013	J	`jnl`	Group Learning and Opinion Diffusion in a Broadcast Network. CoRR Yang Liu, Mingyan Liu
2013	—	`conf`	Group learning and opinion diffusion in a broadcast network. Allerton Yang Liu, Mingyan Liu
2013	J	`jnl`	Revisiting Optimal Power Control: its Dual Effect on SNR and Contention. CoRR Yang Liu, Mingyan Liu, Jing Deng
2013	J	`jnl`	Sufficient Conditions on the Optimality of Myopic Sensing in Opportunistic Channel Access: A Unifying Framework. CoRR Yang Liu, Mingyan Liu, Sahand Haji Ali Ahmad
2013	J	`jnl`	To Stay Or To Switch: Multiuser Dynamic Channel Access. CoRR Yang Liu, Mingyan Liu
2013	A*	`conf`	To stay or to switch: Multiuser dynamic channel access. INFOCOM Yang Liu, Mingyan Liu
2012	A*	`conf`	Is diversity gain worth the pain: A delay comparison between opportunistic multi-channel MAC and single-channel MAC. INFOCOM Yang Liu, Mingyan Liu, Jing Deng
2010	—	`conf`	Design and Construction of a Prototype Secure Wireless Mesh Network Testbed. AINA Workshops Donglai Sun, Yue Wu, Tian Wu, Yang Liu, Ning Liu, Junhua Tang
2010	C	`conf`	Two tier detection model for misbehavior of low-power nodes in virtual MIMO based wireless networks. IAS Yang Liu, Yue Wu, Junhua Tang
2009	B	`conf`	Efficient implementation of FIR type time domain equalizers for MIMO wireless channels via M-LESQ. PIMRC Yang Liu, Ping Yi, Yue Wu