Yang Liu

ORCID

Publication Activity (10 Years)

Years Active: 2009-2024
Publications (10 Years): 108

Top Venues

Publications

Tongxin Yin, Jean-Francois Ton, Ruocheng Guo, Yuanshun Yao, Mingyan Liu, Yang Liu
Fair Classifiers that Abstain without Harm. ICLR (2024)
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
Toward Optimal LLM Alignments Using Two-Player Games. CoRR (2024)
Hao Cheng, Qingsong Wen, Yang Liu, Liang Sun
RobustTSF: Towards Theory and Design of Robust Time Series Forecasting with Anomalies. ICLR (2024)
Kun Jin, Tian Xie, Yang Liu, Xueru Zhang
Addressing Polarization and Unfairness in Performative Prediction. CoRR (2024)
Xiaoying Zhang, Hongning Wang, Yang Liu
Retention Depolarization in Recommender System. WWW (2024)
Reilly Raab, Ross Boczar, Maryam Fazel, Yang Liu
Fair Participation via Sequential Policies. AAAI (2024)
Tao Lin, Kun Jin, Andrew Estornell, Xiaoying Zhang, Yiling Chen, Yang Liu
User-Creator Feature Dynamics in Recommender Systems with Dual Influence. CoRR (2024)
Chentao Cao, Zhun Zhong, Zhanke Zhou, Yang Liu, Tongliang Liu, Bo Han
Envisioning Outlier Exposure by Large Language Models for Out-of-Distribution Detection. CoRR (2024)
Wei Shen, Xiaoying Zhang, Yuanshun Yao, Rui Zheng, Hongyi Guo, Yang Liu
Improving Reinforcement Learning from Human Feedback Using Contrastive Rewards. CoRR (2024)
Zhaowei Zhu, Jialu Wang, Hao Cheng, Yang Liu
Unmasking and Improving Data Credibility: A Study with Datasets for Training Harmless Language Models. ICLR (2024)
Zonghao Chen, Ruocheng Guo, Jean-Francois Ton, Yang Liu
Conformal Counterfactual Inference under Hidden Confounding. KDD (2024)
Yatong Chen, Jialu Wang, Yang Liu
Learning to Incentivize Improvements from Strategic Agents. Trans. Mach. Learn. Res. 2023 (2023)
Kun Jin, Tongxin Yin, Zhongzhu Chen, Zeyu Sun, Xueru Zhang, Yang Liu, Mingyan Liu
Performative Federated Learning: A Solution to Model-Dependent and Heterogeneous Distribution Shifts. CoRR (2023)
Jiaheng Wei, Harikrishna Narasimhan, Ehsan Amid, Wen-Sheng Chu, Yang Liu, Abhishek Kumar
Distributionally Robust Post-hoc Classifiers under Prior Shifts. ICLR (2023)
Andrew Estornell, Yatong Chen, Sanmay Das, Yang Liu, Yevgeniy Vorobeychik
Incentivizing Recourse through Auditing in Strategic Classification. IJCAI (2023)
Hao Cheng, Zhaowei Zhu, Xing Sun, Yang Liu
Mitigating Memorization of Noisy Labels via Regularization between Representations. ICLR (2023)
Zhaowei Zhu, Yuanshun Yao, Jiankai Sun, Hang Li, Yang Liu
Weak Proxies are Sufficient and Preferable for Fairness with Missing Sensitive Attributes. ICML (2023)
Shuo Yang, Songhua Wu, Erkun Yang, Bo Han, Yang Liu, Min Xu, Gang Niu, Tongliang Liu
A Parametrical Model for Instance-Dependent Label Noise. IEEE Trans. Pattern Anal. Mach. Intell. 45 (12) (2023)
Jayanth Yetukuri, Ian Hardy, Yang Liu
Towards User Guided Actionable Recourse. AIES (2023)
Tongxin Yin, Reilly Raab, Mingyan Liu, Yang Liu
Long-Term Fairness with Unknown Dynamics. CoRR (2023)
Ian Hardy, Jayanth Yetukuri, Yang Liu
Adaptive Adversarial Training Does Not Increase Recourse Costs. AIES (2023)
Tianyi Luo, Yang Liu
Machine truth serum: a surprisingly popular approach to improving ensemble methods. Mach. Learn. 112 (3) (2023)
Tongxin Yin, Reilly Raab, Mingyan Liu, Yang Liu
Long-Term Fairness with Unknown Dynamics. NeurIPS (2023)
Jiaheng Wei, Zhaowei Zhu, Tianyi Luo, Ehsan Amid, Abhishek Kumar, Yang Liu
To Aggregate or Not? Learning with Separate Noisy Labels. KDD (2023)
Jiaheng Wei, Minghao Liu, Jiahao Luo, Andrew Zhu, James Davis, Yang Liu
DuelGAN: A Duel Between Two Discriminators Stabilizes the GAN Training. ECCV (23) (2022)
Jiaheng Wei, Zhaowei Zhu, Tianyi Luo, Ehsan Amid, Abhishek Kumar, Yang Liu
To Aggregate or Not? Learning with Separate Noisy Labels. CoRR (2022)
Shuo Yang, Erkun Yang, Bo Han, Yang Liu, Min Xu, Gang Niu, Tongliang Liu
Estimating Instance-dependent Bayes-label Transition Matrix using a Deep Neural Network. ICML (2022)
Yatong Chen, Reilly Raab, Jialu Wang, Yang Liu
Fairness Transferability Subject to Bounded Distribution Shift. NeurIPS (2022)
Jiaheng Wei, Zhaowei Zhu, Hao Cheng, Tongliang Liu, Gang Niu, Yang Liu
Learning with Noisy Labels Revisited: A Study Using Real-World Human Annotations. ICLR (2022)
Jayanth Yetukuri, Yang Liu
Robust Stochastic Bandit algorithms to defend against Oracle attack using Sample Dropout. Big Data (2022)
Yifan Yang, Yang Liu, Parinaz Naghizadeh
Adaptive Data Debiasing through Bounded Exploration. NeurIPS (2022)
Songhua Wu, Mingming Gong, Bo Han, Yang Liu, Tongliang Liu
Fair Classification with Instance-dependent Label Noise. CLeaR (2022)
Jiaheng Wei, Zuyue Fu, Yang Liu, Xingyu Li, Zhuoran Yang, Zhaoran Wang
Sample Elicitation. AISTATS (2021)
Hao Cheng, Zhaowei Zhu, Xingyu Li, Yifei Gong, Xing Sun, Yang Liu
Learning with Instance-Dependent Label Noise: A Sample Sieve Approach. ICLR (2021)
Wei Tang, Chien-Ju Ho, Yang Liu
Bandit Learning with Delayed Impact of Actions. NeurIPS (2021)
Shuo Yang, Erkun Yang, Bo Han, Yang Liu, Min Xu, Gang Niu, Tongliang Liu
Estimating Instance-dependent Label-noise Transition Matrix using DNNs. CoRR (2021)
Juntao Wang, Yang Liu, Yiling Chen
Forecast Aggregation via Peer Prediction. HCOMP (2021)
Yang Liu, Jialu Wang
Can Less be More? When Increasing-to-Balancing Label Noise Rates Considered Beneficial. NeurIPS (2021)
Jialu Wang, Yang Liu, Xin Eric Wang
Assessing Multilingual Fairness in Pre-trained Multimodal Representations. CoRR (2021)
Jiaheng Wei, Zhaowei Zhu, Hao Cheng, Tongliang Liu, Gang Niu, Yang Liu
Learning with Noisy Labels Revisited: A Study Using Real-World Human Annotations. CoRR (2021)
Jialu Wang, Yang Liu, Xin Eric Wang
Are Gender-Neutral Queries Really Gender-Neutral? Mitigating Gender Bias in Image Search. CoRR (2021)
Zhaowei Zhu, Yiwen Song, Yang Liu
Clusterability as an Alternative to Anchor Points When Learning with Noisy Labels. CoRR (2021)
Jingkang Wang, Hongyi Guo, Zhaowei Zhu, Yang Liu
Policy Learning Using Weak Supervision. NeurIPS (2021)
Zhaowei Zhu, Jingxuan Zhu, Ji Liu, Yang Liu
Federated Bandit: A Gossiping Approach. Proc. ACM Meas. Anal. Comput. Syst. 5 (1) (2021)
Yang Liu, Jialu Wang
Can Less be More? When Increasing-to-Balancing Label Noise Rates Considered Beneficial. CoRR (2021)
Zhaowei Zhu, Yiwen Song, Yang Liu
Clusterability as an Alternative to Anchor Points When Learning with Noisy Labels. ICML (2021)
Wei Tang, Chien-Ju Ho, Yang Liu
Optimal Query Complexity of Secure Stochastic Convex Optimization. CoRR (2021)
Reilly Raab, Yang Liu
Unintended Selection: Persistent Qualification Rate Disparities and Interventions. NeurIPS (2021)
Wei Tang, Chien-Ju Ho, Yang Liu
Linear Models are Robust Optimal Under Strategic Behavior. AISTATS (2021)
Zhaowei Zhu, Tongliang Liu, Yang Liu
A Second-Order Approach to Learning With Instance-Dependent Label Noise. CVPR (2021)
Jiaheng Wei, Hangyu Liu, Tongliang Liu, Gang Niu, Yang Liu
Understanding (Generalized) Label Smoothing when Learning with Noisy Labels. CoRR (2021)
Jialu Wang, Yang Liu, Caleb C. Levy
Fair Classification with Group-Dependent Label Noise. FAccT (2021)
Zhaowei Zhu, Jingxuan Zhu, Ji Liu, Yang Liu
Federated Bandit: A Gossiping Approach. SIGMETRICS (Abstracts) (2021)
Jialu Wang, Yang Liu, Xin Eric Wang
Are Gender-Neutral Queries Really Gender-Neutral? Mitigating Gender Bias in Image Search. EMNLP (1) (2021)
Yang Liu, Juntao Wang, Yiling Chen
Surrogate Scoring Rules. EC (2020)
Nripsuta Ani Saxena, Karen Huang, Evan DeFilippis, Goran Radanovic, David C. Parkes, Yang Liu
How do fairness definitions fare? Testing public attitudes towards three algorithmic definitions of fairness in loan allocations. Artif. Intell. 283 (2020)
Wei Tang, Chien-Ju Ho, Yang Liu
Optimal Query Complexity of Secure Stochastic Convex Optimization. NeurIPS (2020)
Kaiqing Zhang, Yang Liu, Ji Liu, Mingyan Liu, Tamer Basar
Distributed learning of average belief over networks using sequential observations. Autom. 115 (2020)
Hao Cheng, Zhaowei Zhu, Xingyu Li, Yifei Gong, Xing Sun, Yang Liu
Learning with Instance-Dependent Label Noise: A Sample Sieve Approach. CoRR (2020)
Jingkang Wang, Yang Liu, Bo Li
Reinforcement Learning with Perturbed Rewards. AAAI (2020)
Zhaowei Zhu, Jingxuan Zhu, Ji Liu, Yang Liu
Federated Bandit: A Gossiping Approach. CoRR (2020)
Yatong Chen, Jialu Wang, Yang Liu
Strategic Recourse in Linear Classification. CoRR (2020)
Tianyi Luo, Xingyu Li, Hainan Wang, Yang Liu
Research Replication Prediction Using Weakly Supervised Learning. EMNLP (Findings) (2020)
Jialu Wang, Yang Liu, Caleb C. Levy
Fair Classification with Group-Dependent Label Noise. CoRR (2020)
Jingkang Wang, Hongyi Guo, Zhaowei Zhu, Yang Liu
Policy Learning Using Weak Supervision. CoRR (2020)
Wei Tang, Chien-Ju Ho, Yang Liu
Differentially Private Contextual Dynamic Pricing. AAMAS (2020)
Yiling Chen, Yang Liu, Chara Podimata
Learning Strategy-Aware Linear Classifiers. NeurIPS (2020)
Yang Liu, Michael Gordon, Juntao Wang, Michael Bishop, Yiling Chen, Thomas Pfeiffer, Charles Twardy, Domenico Viganola
Replication Markets: Results, Lessons, Challenges and Opportunities in AI Replication. CoRR (2020)
Zhaowei Zhu, Tongliang Liu, Yang Liu
A Second-Order Approach to Learning with Instance-Dependent Label Noise. CoRR (2020)
Wei Tang, Chien-Ju Ho, Yang Liu
Fair Bandit Learning with Delayed Impact of Actions. CoRR (2020)
Berk Ustun, Alexander Spangher, Yang Liu
Actionable Recourse in Linear Classification. FAT (2019)
Yiling Chen, Yang Liu, Juntao Wang
Randomized Wagering Mechanisms. AAAI (2019)
Berk Ustun, Yang Liu, David C. Parkes
Fairness without Harm: Decoupled Classifiers with Preference Guarantees. ICML (2019)
Nripsuta Ani Saxena, Karen Huang, Evan DeFilippis, Goran Radanovic, David C. Parkes, Yang Liu
How Do Fairness Definitions Fare?: Examining Public Attitudes Towards Algorithmic Definitions of Fairness. AIES (2019)
Yiling Chen, Yang Liu, Chara Podimata
Grinding the Space: Learning to Classify Against Strategic Agents. CoRR (2019)
Christos Dimitrakakis, Yang Liu, David C. Parkes, Goran Radanovic
Bayesian Fairness. AAAI (2019)
Juntao Wang, Yang Liu, Yiling Chen
Forecast Aggregation via Peer Prediction. CoRR (2019)
Wenwu He, Yang Liu
To regularize or not: Revisiting SGD with simple algorithms and experimental studies. Expert Syst. Appl. 112 (2018)
Yang Liu, Ji Liu, Tamer Basar
Differentially Private Gossip Gradient Descent. CDC (2018)
Shuran Zheng, Bo Waggoner, Yang Liu, Yiling Chen
Active Information Acquisition for Linear Optimization. UAI (2018)
Jingkang Wang, Yang Liu, Bo Li
Reinforcement Learning with Perturbed Rewards. CoRR (2018)
Yang Liu, Ji Liu, Tamer Basar
Gossip Gradient Descent. AAMAS (2018)
Zehong Hu, Yitao Liang, Yang Liu, Jie Zhang
Inference Aided Reinforcement Learning for Incentive Mechanism Design in Crowdsourcing. CoRR (2018)
Berk Ustun, Alexander Spangher, Yang Liu
Actionable Recourse in Linear Classification. CoRR (2018)
Yang Liu, Chien-Ju Ho
Incentivizing High Quality User Contributions: New Arm Generation in Bandit Learning. AAAI (2018)
Nripsuta Saxena, Karen Huang, Evan DeFilippis, Goran Radanovic, David C. Parkes, Yang Liu
How Do Fairness Definitions Fare? Examining Public Attitudes Towards Algorithmic Definitions of Fairness. CoRR (2018)
Yang Liu, Yiling Chen
Surrogate Scoring Rules and a Dominant Truth Serum for Information Elicitation. CoRR (2018)
Chaowei Xiao, Armin Sarabi, Yang Liu, Bo Li, Mingyan Liu, Tudor Dumitras
From Patching Delays to Infection Symptoms: Using Risk Profiles for an Early Discovery of Vulnerabilities Exploited in the Wild. USENIX Security Symposium (2018)
Yiling Chen, Yang Liu, Juntao Wang
Randomized Wagering Mechanisms. CoRR (2018)
Kaiqing Zhang, Yang Liu, Ji Liu, Mingyan Liu, Tamer Basar
Distributed Learning of Average Belief Over Networks Using Sequential Observations. CoRR (2018)
Zehong Hu, Yitao Liang, Jie Zhang, Zhao Li, Yang Liu
Inference Aided Reinforcement Learning for Incentive Mechanism Design in Crowdsourcing. NeurIPS (2018)
Ji Liu, Yang Liu, Angelia Nedic, Tamer Basar
An approach to distributed parametric learning with streaming data. CDC (2017)
Yang Liu, Ji Liu, Tamer Basar, Mingyan Liu
Distributed belief averaging using sequential observations. ACC (2017)
Yang Liu, Yiling Chen
Machine-Learning Aided Peer Prediction. EC (2017)
Yang Liu
Fair Optimal Stopping Policy for Matching with Mediator. UAI (2017)
Yang Liu, Yiling Chen
Sequential Peer Prediction: Learning to Elicit Effort using Posted Prices. AAAI (2017)
Yang Liu, Goran Radanovic, Christos Dimitrakakis, Debmalya Mandal, David C. Parkes
Calibrated Fairness in Bandits. CoRR (2017)
Wenwu He, James Tin-Yau Kwok, Ji Zhu, Yang Liu
A Note on the Unification of Adaptive Online Learning. IEEE Trans. Neural Networks Learn. Syst. 28 (5) (2017)
Yang Liu, Mingyan Liu
Crowd Learning: Improving Online Decision Making Using Crowdsourced Data. IJCAI (2017)
Shuran Zheng, Bo Waggoner, Yang Liu, Yiling Chen
Active Information Acquisition for Linear Optimization. CoRR (2017)

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Publication Activity (10 Years)

Top Topics

Top Venues

Yang Liu