Yang Liu

According to our database, Yang Liu authored at least 179 papers between 2009 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

ACC-Debate: An Actor-Critic Approach to Multi-Agent Debate.

Andrew Estornell, Jean-Francois Ton, Yuanshun Yao, Yang Liu

CoRR, 2024

LLM Unlearning via Loss Adjustment with Only Forget Data.

Yaxuan Wang, Jiaheng Wei, Chris Yuhao Liu, Jinlong Pang, Quan Liu, Ankit Parag Shah, Yujia Bao, Yang Liu, Wei Wei

CoRR, 2024

Improving Data Efficiency via Curating LLM-Driven Rating Systems.

Jinlong Pang, Jiaheng Wei, Ankit Parag Shah, Zhaowei Zhu, Yaxuan Wang, Chen Qian, Yang Liu, Yujia Bao, Wei Wei

CoRR, 2024

Mind Scramble: Unveiling Large Language Model Psychology Via Typoglycemia.

Miao Yu, Junyuan Mao, Guibin Zhang, Jingheng Ye, Junfeng Fang, Aoxiao Zhong, Yang Liu, Yuxuan Liang, Kun Wang, Qingsong Wen

CoRR, 2024

User-Creator Feature Dynamics in Recommender Systems with Dual Influence.

Tao Lin, Kun Jin, Andrew Estornell, Xiaoying Zhang, Yiling Chen, Yang Liu

CoRR, 2024

Addressing Polarization and Unfairness in Performative Prediction.

Kun Jin, Tian Xie, Yang Liu, Xueru Zhang

CoRR, 2024

Toward Optimal LLM Alignments Using Two-Player Games.

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

CoRR, 2024

Large Language Model Unlearning via Embedding-Corrupted Prompts.

Chris Yuhao Liu, Yaxuan Wang, Jeffrey Flanigan, Yang Liu

CoRR, 2024

Label Smoothing Improves Machine Unlearning.

Zonglin Di, Zhaowei Zhu, Jinghan Jia, Jiancheng Liu, Zafar Takhirov, Bo Jiang, Yuanshun Yao, Sijia Liu, Yang Liu

CoRR, 2024

Adversarial Machine Unlearning.

Zonglin Di, Sixie Yu, Yevgeniy Vorobeychik, Yang Liu

CoRR, 2024

Long-Term Fairness Inquiries and Pursuits in Machine Learning: A Survey of Notions, Methods, and Challenges.

Usman Gohar, Zeyu Tang, Jialu Wang, Kun Zhang, Peter L. Spirtes, Yang Liu, Lu Cheng

CoRR, 2024

Learning to Watermark LLM-generated Text via Reinforcement Learning.

Xiaojun Xu, Yuanshun Yao, Yang Liu

CoRR, 2024

Steering LLMs Towards Unbiased Responses: A Causality-Guided Debiasing Framework.

Jingling Li, Zeyu Tang, Xiaoyu Liu, Peter Spirtes, Kun Zhang, Liu Leqi, Yang Liu

CoRR, 2024

Improving Reinforcement Learning from Human Feedback Using Contrastive Rewards.

Wei Shen, Xiaoying Zhang, Yuanshun Yao, Rui Zheng, Hongyi Guo, Yang Liu

CoRR, 2024

Overcoming Reward Overoptimization via Adversarial Policy Optimization with Lightweight Uncertainty Estimation.

Xiaoying Zhang, Jean-Francois Ton, Wei Shen, Hongning Wang, Yang Liu

CoRR, 2024

Dataset Fairness: Achievable Fairness on Your Data With Utility Guarantees.

Muhammad Faaiz Taufiq, Jean-Francois Ton, Yang Liu

CoRR, 2024

Fair Classifiers Without Fair Training: An Influence-Guided Data Sampling Approach.

Jinlong Pang, Jialu Wang, Zhaowei Zhu, Yuanshun Yao, Chen Qian, Yang Liu

CoRR, 2024

Adversarial Curriculum Graph Contrastive Learning with Pair-wise Augmentation.

Xinjian Zhao, Liang Zhang, Yang Liu, Ruocheng Guo, Xiangyu Zhao

CoRR, 2024

Measuring and Reducing LLM Hallucination without Gold-Standard Answers via Expertise-Weighting.

Jiaheng Wei, Yuanshun Yao, Jean-Francois Ton, Hongyi Guo, Andrew Estornell, Yang Liu

CoRR, 2024

Rethinking Machine Unlearning for Large Language Models.

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

CoRR, 2024

Human-Instruction-Free LLM Self-Alignment with Limited Samples.

Hongyi Guo, Yuanshun Yao, Wei Shen, Jiaheng Wei, Xiaoying Zhang, Zhaoran Wang, Yang Liu

CoRR, 2024

Retention Depolarization in Recommender System.

Xiaoying Zhang, Hongning Wang, Yang Liu

Proceedings of the ACM on Web Conference 2024, 2024

Conformal Counterfactual Inference under Hidden Confounding.

Zonghao Chen, Ruocheng Guo, Jean-Francois Ton, Yang Liu

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Performative Prediction with Bandit Feedback: Learning through Reparameterization.

Yatong Chen, Wei Tang, Chien-Ju Ho, Yang Liu

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Envisioning Outlier Exposure by Large Language Models for Out-of-Distribution Detection.

Chentao Cao, Zhun Zhong, Zhanke Zhou, Yang Liu, Tongliang Liu, Bo Han

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Unmasking and Improving Data Credibility: A Study with Datasets for Training Harmless Language Models.

Zhaowei Zhu, Jialu Wang, Hao Cheng, Yang Liu

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Fair Classifiers that Abstain without Harm.

Tongxin Yin, Jean-Francois Ton, Ruocheng Guo, Yuanshun Yao, Mingyan Liu, Yang Liu

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Procedural Fairness Through Decoupling Objectionable Data Generating Components.

Zeyu Tang, Jialu Wang, Yang Liu, Peter Spirtes, Kun Zhang

Proceedings of the Twelfth International Conference on Learning Representations, 2024

RobustTSF: Towards Theory and Design of Robust Time Series Forecasting with Anomalies.

Hao Cheng, Qingsong Wen, Yang Liu, Liang Sun

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Post-hoc bias scoring is optimal for fair classification.

Wenlong Chen, Yegor Klochkov, Yang Liu

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Multifaceted Reformulations for Null & Low queries and its parallelism with Counterfactuals.

Jayanth Yetukuri, Yuyan Wang, Ishita Khan, Liyang Hao, Zhe Wu, Yang Liu

Proceedings of the 40th IEEE International Conference on Data Engineering, 2024

Federated Learning with Local Openset Noisy Labels.

Zonglin Di, Zhaowei Zhu, Xiaoxiao Li, Yang Liu

Proceedings of the Computer Vision - ECCV 2024, 2024

Providing Fair Recourse over Plausible Groups.

Jayanth Yetukuri, Ian Hardy, Yevgeniy Vorobeychik, Berk Ustun, Yang Liu

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Fair Participation via Sequential Policies.

Reilly Raab, Ross Boczar, Maryam Fazel, Yang Liu

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Performative Federated Learning: A Solution to Model-Dependent and Heterogeneous Distribution Shifts.

Kun Jin, Tongxin Yin, Zhongzhu Chen, Zeyu Sun, Xueru Zhang, Yang Liu, Mingyan Liu

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

FedFixer: Mitigating Heterogeneous Label Noise in Federated Learning.

Xinyuan Ji, Zhaowei Zhu, Wei Xi, Olga Gadyatskaya, Zilong Song, Yong Cai, Yang Liu

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

A Parametrical Model for Instance-Dependent Label Noise.

Shuo Yang, Songhua Wu, Erkun Yang, Bo Han, Yang Liu, Min Xu, Gang Niu, Tongliang Liu

IEEE Trans. Pattern Anal. Mach. Intell., December, 2023

Machine truth serum: a surprisingly popular approach to improving ensemble methods.

Tianyi Luo, Yang Liu

Mach. Learn., March, 2023

Learning to Incentivize Improvements from Strategic Agents.

Yatong Chen, Jialu Wang, Yang Liu

Trans. Mach. Learn. Res., 2023

DMLR: Data-centric Machine Learning Research - Past, Present and Future.

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 D. Bollacker, Lora Aroyo, Ce Zhang, Joaquin Vanschoren, Isabelle Guyon, Peter Mattson

CoRR, 2023

Large Language Model Unlearning.

Yuanshun Yao, Xiaojun Xu, Yang Liu

CoRR, 2023

Deep Concept Removal.

Yegor Klochkov, Jean-Francois Ton, Ruocheng Guo, Yang Liu, Hang Li

CoRR, 2023

Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' Alignment.

Yang Liu, Yuanshun Yao, Jean-Francois Ton, Xiaoying Zhang, Ruocheng Guo, Hao Cheng, Yegor Klochkov, Muhammad Faaiz Taufiq, Hang Li

CoRR, 2023

Understanding Unfairness via Training Concept Influence.

Yuanshun Yao, Yang Liu

CoRR, 2023

Fair Learning to Rank with Distribution-free Risk Control.

Ruocheng Guo, Jean-François Ton, Yang Liu

CoRR, 2023

T2IAT: Measuring Valence and Stereotypical Biases in Text-to-Image Generation.

Jialu Wang, Xinyue Gabby Liu, Zonglin Di, Yang Liu, Xin Eric Wang

CoRR, 2023

Do humans and machines have the same eyes? Human-machine perceptual differences on image classification.

Minghao Liu, Jiaheng Wei, Yang Liu, James Davis

CoRR, 2023

Model Sparsification Can Simplify Machine Unlearning.

Jinghan Jia, Jiancheng Liu, Parikshit Ram, Yuguang Yao, Gaowen Liu, Yang Liu, Pranay Sharma, Sijia Liu

CoRR, 2023

Fairness Improves Learning from Noisily Labeled Long-Tailed Data.

Jiaheng Wei, Zhaowei Zhu, Gang Niu, Tongliang Liu, Sijia Liu, Masashi Sugiyama, Yang Liu

CoRR, 2023

4th Crowd Science Workshop - CANDLE: Collaboration of Humans and Learning Algorithms for Data Labeling.

Dmitry Ustalov, Saiph Savage, Niels van Berkel, Yang Liu

Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining, 2023

Uncertainty-Aware Instance Reweighting for Off-Policy Learning.

Xiaoying Zhang, Junpu Chen, Hongning Wang, Hong Xie, Yang Liu, John C. S. Lui, Hang Li

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Long-Term Fairness with Unknown Dynamics.

Tongxin Yin, Reilly Raab, Mingyan Liu, Yang Liu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Model Sparsity Can Simplify Machine Unlearning.

Jinghan Jia, Jiancheng Liu, Parikshit Ram, Yuguang Yao, Gaowen Liu, Yang Liu, Pranay Sharma, Sijia Liu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Debiasing Recommendation by Learning Identifiable Latent Confounders.

Qing Zhang, Xiaoying Zhang, Yang Liu, Hongning Wang, Min Gao, Jiheng Zhang, Ruocheng Guo

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

The Importance of Human-Labeled Data in the Era of LLMs.

Yang Liu

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Incentivizing Recourse through Auditing in Strategic Classification.

Andrew Estornell, Yatong Chen, Sanmay Das, Yang Liu, Yevgeniy Vorobeychik

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Weak Proxies are Sufficient and Preferable for Fairness with Missing Sensitive Attributes.

Zhaowei Zhu, Yuanshun Yao, Jiankai Sun, Hang Li, Yang Liu

Proceedings of the International Conference on Machine Learning, 2023

Identifiability of Label Noise Transition Matrix.

Yang Liu, Hao Cheng, Kun Zhang

Proceedings of the International Conference on Machine Learning, 2023

Model Transferability with Responsive Decision Subjects.

Yatong Chen, Zeyu Tang, Kun Zhang, Yang Liu

Proceedings of the International Conference on Machine Learning, 2023

Distributionally Robust Post-hoc Classifiers under Prior Shifts.

Jiaheng Wei, Harikrishna Narasimhan, Ehsan Amid, Wen-Sheng Chu, Yang Liu, Abhishek Kumar

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Tier Balancing: Towards Dynamic Fairness over Underlying Causal Factors.

Zeyu Tang, Yatong Chen, Yang Liu, Kun Zhang

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Mitigating Memorization of Noisy Labels via Regularization between Representations.

Hao Cheng, Zhaowei Zhu, Xing Sun, Yang Liu

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Group-Fair Classification with Strategic Agents.

Andrew Estornell, Sanmay Das, Yang Liu, Yevgeniy Vorobeychik

Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, 2023

Auditing for Federated Learning: A Model Elicitation Approach.

Yang Liu, Rixing Lou, Jiaheng Wei

Proceedings of the Fifth International Conference on Distributed Artificial Intelligence, 2023

To Aggregate or Not? Learning with Separate Noisy Labels.

Jiaheng Wei, Zhaowei Zhu, Tianyi Luo, Ehsan Amid, Abhishek Kumar, Yang Liu

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), 2023

Towards User Guided Actionable Recourse.

Jayanth Yetukuri, Ian Hardy, Yang Liu

Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society, 2023

Adaptive Adversarial Training Does Not Increase Recourse Costs.

Ian Hardy, Jayanth Yetukuri, Yang Liu

Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society, 2023

T2IAT: Measuring Valence and Stereotypical Biases in Text-to-Image Generation.

Jialu Wang, Xinyue Liu, Zonglin Di, Yang Liu, Xin Eric Wang

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

2022

Surrogate Scoring Rules.

Yang Liu, Juntao Wang, Yiling Chen

ACM Trans. Economics and Comput., September, 2022

Evaluating Fairness Without Sensitive Attributes: A Framework Using Only Auxiliary Models.

Zhaowei Zhu, Yuanshun Yao, Jiankai Sun, Yang Liu, Hang Li

CoRR, 2022

Conjugate Natural Selection.

Reilly Raab, Luca de Alfaro, Yang Liu

CoRR, 2022

Identifiability of Label Noise Transition Matrix.

Yang Liu

CoRR, 2022

Adaptive Data Debiasing through Bounded Exploration.

Yifan Yang, Yang Liu, Parinaz Naghizadeh

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Certifying Some Distributional Fairness with Subpopulation Decomposition.

Mintong Kang, Linyi Li, Maurice Weber, Yang Liu, Ce Zhang, Bo Li

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Fairness Transferability Subject to Bounded Distribution Shift.

Yatong Chen, Reilly Raab, Jialu Wang, Yang Liu

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Low-light Image Enhancement Using Chain-consistent Adversarial Networks.

Minghao Liu, Jiahao Luo, Xiaohan Zhang, Yang Liu, James Davis

Proceedings of the 26th International Conference on Pattern Recognition, 2022

Beyond Images: Label Noise Transition Matrix Estimation for Tasks with Lower-Quality Features.

Zhaowei Zhu, Jialu Wang, Yang Liu

Proceedings of the International Conference on Machine Learning, 2022

Detecting Corrupted Labels Without Training a Model to Predict.

Zhaowei Zhu, Zihao Dong, Yang Liu

Proceedings of the International Conference on Machine Learning, 2022

Estimating Instance-dependent Bayes-label Transition Matrix using a Deep Neural Network.

Shuo Yang, Erkun Yang, Bo Han, Yang Liu, Min Xu, Gang Niu, Tongliang Liu

Proceedings of the International Conference on Machine Learning, 2022

Metric-Fair Classifier Derandomization.

Jimmy Wu, Yatong Chen, Yang Liu

Proceedings of the International Conference on Machine Learning, 2022

To Smooth or Not? When Label Smoothing Meets Noisy Labels.

Jiaheng Wei, Hangyu Liu, Tongliang Liu, Gang Niu, Masashi Sugiyama, Yang Liu

Proceedings of the International Conference on Machine Learning, 2022

Understanding Instance-Level Impact of Fairness Constraints.

Jialu Wang, Xin Eric Wang, Yang Liu

Proceedings of the International Conference on Machine Learning, 2022

The Rich Get Richer: Disparate Impact of Semi-Supervised Learning.

Zhaowei Zhu, Tianyi Luo, Yang Liu

Proceedings of the Tenth International Conference on Learning Representations, 2022

Learning with Noisy Labels Revisited: A Study Using Real-World Human Annotations.

Jiaheng Wei, Zhaowei Zhu, Hao Cheng, Tongliang Liu, Gang Niu, Yang Liu

Proceedings of the Tenth International Conference on Learning Representations, 2022

DuelGAN: A Duel Between Two Discriminators Stabilizes the GAN Training.

Jiaheng Wei, Minghao Liu, Jiahao Luo, Andrew Zhu, James Davis, Yang Liu

Proceedings of the Computer Vision - ECCV 2022, 2022

Fair Classification with Instance-dependent Label Noise.

Songhua Wu, Mingming Gong, Bo Han, Yang Liu, Tongliang Liu

Proceedings of the 1st Conference on Causal Learning and Reasoning, 2022

Learning and Mining with Noisy Labels.

Masashi Sugiyama, Tongliang Liu, Bo Han, Yang Liu, Gang Niu

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

Robust Stochastic Bandit algorithms to defend against Oracle attack using Sample Dropout.

Jayanth Yetukuri, Yang Liu

Proceedings of the IEEE International Conference on Big Data, 2022

Assessing Multilingual Fairness in Pre-trained Multimodal Representations.

Jialu Wang, Yang Liu, Xin Eric Wang

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2022, 2022

Interpretable Research Replication Prediction via Variational Contextual Consistency Sentence Masking.

Tianyi Luo, Rui Meng, Xin Wang, Yang Liu

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2022, 2022

2021

Federated Bandit: A Gossiping Approach.

Zhaowei Zhu, Jingxuan Zhu, Ji Liu, Yang Liu

Proc. ACM Meas. Anal. Comput. Syst., 2021

Unfairness Despite Awareness: Group-Fair Classification with Strategic Agents.

Andrew Estornell, Sanmay Das, Yang Liu, Yevgeniy Vorobeychik

CoRR, 2021

Adaptive Data Debiasing through Bounded Exploration and Fairness.

Yifan Yang, Yang Liu, Parinaz Naghizadeh

CoRR, 2021

Demystifying How Self-Supervised Features Improve Training from Noisy Labels.

Hao Cheng, Zhaowei Zhu, Xing Sun, Yang Liu

CoRR, 2021

A Good Representation Detects Noisy Labels.

Zhaowei Zhu, Zihao Dong, Yang Liu

CoRR, 2021

Induced Domain Adaptation.

Yang Liu, Yatong Chen, Jiaheng Wei

CoRR, 2021

Understanding (Generalized) Label Smoothing when Learning with Noisy Labels.

Jiaheng Wei, Hangyu Liu, Tongliang Liu, Gang Niu, Yang Liu

CoRR, 2021

Estimating Instance-dependent Label-noise Transition Matrix using DNNs.

Shuo Yang, Erkun Yang, Bo Han, Yang Liu, Min Xu, Gang Niu, Tongliang Liu

CoRR, 2021

PeerGAN: Generative Adversarial Networks with a Competing Peer Discriminator.

Jiaheng Wei, Minghao Liu, Jiahao Luo, Qiutong Li, James Davis, Yang Liu

CoRR, 2021

Policy Learning Using Weak Supervision.

Jingkang Wang, Hongyi Guo, Zhaowei Zhu, Yang Liu

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Bandit Learning with Delayed Impact of Actions.

Wei Tang, Chien-Ju Ho, Yang Liu

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Unintended Selection: Persistent Qualification Rate Disparities and Interventions.

Reilly Raab, Yang Liu

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Can Less be More? When Increasing-to-Balancing Label Noise Rates Considered Beneficial.

Yang Liu, Jialu Wang

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Clusterability as an Alternative to Anchor Points When Learning with Noisy Labels.

Zhaowei Zhu, Yiwen Song, Yang Liu

Proceedings of the 38th International Conference on Machine Learning, 2021

Understanding Instance-Level Label Noise: Disparate Impacts and Treatments.

Yang Liu

Proceedings of the 38th International Conference on Machine Learning, 2021

When Optimizing f-Divergence is Robust with Label Noise.

Jiaheng Wei, Yang Liu

Proceedings of the 9th International Conference on Learning Representations, 2021

Learning with Instance-Dependent Label Noise: A Sample Sieve Approach.

Hao Cheng, Zhaowei Zhu, Xingyu Li, Yifei Gong, Xing Sun, Yang Liu

Proceedings of the 9th International Conference on Learning Representations, 2021

Forecast Aggregation via Peer Prediction.

Juntao Wang, Yang Liu, Yiling Chen

Proceedings of the Ninth AAAI Conference on Human Computation and Crowdsourcing, 2021

Fair Classification with Group-Dependent Label Noise.

Jialu Wang, Yang Liu, Caleb C. Levy

Proceedings of the FAccT '21: 2021 ACM Conference on Fairness, 2021

Are Gender-Neutral Queries Really Gender-Neutral? Mitigating Gender Bias in Image Search.

Jialu Wang, Yang Liu, Xin Eric Wang

Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

A Second-Order Approach to Learning With Instance-Dependent Label Noise.

Zhaowei Zhu, Tongliang Liu, Yang Liu

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Sample Elicitation.

Jiaheng Wei, Zuyue Fu, Yang Liu, Xingyu Li, Zhuoran Yang, Zhaoran Wang

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Linear Models are Robust Optimal Under Strategic Behavior.

Wei Tang, Chien-Ju Ho, Yang Liu

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Strategic Recourse in Linear Classification.

Yatong Chen, Jialu Wang, Yang Liu

CoRR, 2020

Incentives for Federated Learning: a Hypothesis Elicitation Approach.

Yang Liu, Jiaheng Wei

CoRR, 2020

Distributional Individual Fairness in Clustering.

Nihesh Anderson, Suman K. Bera, Syamantak Das, Yang Liu

CoRR, 2020

Replication Markets: Results, Lessons, Challenges and Opportunities in AI Replication.

Yang Liu, Michael Gordon, Juntao Wang, Michael Bishop, Yiling Chen, Thomas Pfeiffer, Charles Twardy, Domenico Viganola

CoRR, 2020

Fair Bandit Learning with Delayed Impact of Actions.

Wei Tang, Chien-Ju Ho, Yang Liu

CoRR, 2020

Distributed learning of average belief over networks using sequential observations.

Kaiqing Zhang, Yang Liu, Ji Liu, Mingyan Liu, Tamer Basar

Autom., 2020

How do fairness definitions fare? Testing public attitudes towards three algorithmic definitions of fairness in loan allocations.

Nripsuta Ani Saxena, Karen Huang, Evan DeFilippis, Goran Radanovic, David C. Parkes, Yang Liu

Artif. Intell., 2020

How do fair decisions fare in long-term qualification?

Xueru Zhang, Ruibo Tu, Yang Liu, Mingyan Liu, Hedvig Kjellström, Kun Zhang, Cheng Zhang

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Optimal Query Complexity of Secure Stochastic Convex Optimization.

Wei Tang, Chien-Ju Ho, Yang Liu

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Learning Strategy-Aware Linear Classifiers.

Yiling Chen, Yang Liu, Chara Podimata

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Peer Loss Functions: Learning from Noisy Labels without Knowing Noise Rates.

Yang Liu, Hongyi Guo

Proceedings of the 37th International Conference on Machine Learning, 2020

Research Replication Prediction Using Weakly Supervised Learning.

Tianyi Luo, Xingyu Li, Hainan Wang, Yang Liu

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020

Differentially Private Contextual Dynamic Pricing.

Wei Tang, Chien-Ju Ho, Yang Liu

Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, 2020

Online Learning Using Only Peer Prediction.

Yang Liu, David P. Helmbold

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Reinforcement Learning with Perturbed Rewards.

Jingkang Wang, Yang Liu, Bo Li

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Grinding the Space: Learning to Classify Against Strategic Agents.

Yiling Chen, Yang Liu, Chara Podimata

CoRR, 2019

Online Learning Using Only Peer Assessment.

Yang Liu, David P. Helmbold

CoRR, 2019

Credible Sample Elicitation by Deep Learning, for Deep Learning.

Yang Liu, Zuyue Fu, Zhuoran Yang, Zhaoran Wang

CoRR, 2019

Machine Truth Serum.

Tianyi Luo, Yang Liu

CoRR, 2019

Fairness without Harm: Decoupled Classifiers with Preference Guarantees.

Berk Ustun, Yang Liu, David C. Parkes

Proceedings of the 36th International Conference on Machine Learning, 2019

Actionable Recourse in Linear Classification.

Berk Ustun, Alexander Spangher, Yang Liu

Proceedings of the Conference on Fairness, Accountability, and Transparency, 2019

How Do Fairness Definitions Fare?: Examining Public Attitudes Towards Algorithmic Definitions of Fairness.

Nripsuta Ani Saxena, Karen Huang, Evan DeFilippis, Goran Radanovic, David C. Parkes, Yang Liu

Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, 2019

Bayesian Fairness.

Christos Dimitrakakis, Yang Liu, David C. Parkes, Goran Radanovic

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

Randomized Wagering Mechanisms.

Yiling Chen, Yang Liu, Juntao Wang

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

To regularize or not: Revisiting SGD with simple algorithms and experimental studies.

Wenwu He, Yang Liu

Expert Syst. Appl., 2018

Inference Aided Reinforcement Learning for Incentive Mechanism Design in Crowdsourcing.

Zehong Hu, Yitao Liang, Yang Liu, Jie Zhang

CoRR, 2018

Surrogate Scoring Rules and a Dominant Truth Serum for Information Elicitation.

Yang Liu, Yiling Chen

CoRR, 2018

From Patching Delays to Infection Symptoms: Using Risk Profiles for an Early Discovery of Vulnerabilities Exploited in the Wild.

Chaowei Xiao, Armin Sarabi, Yang Liu, Bo Li, Mingyan Liu, Tudor Dumitras

Proceedings of the 27th USENIX Security Symposium, 2018

Active Information Acquisition for Linear Optimization.

Shuran Zheng, Bo Waggoner, Yang Liu, Yiling Chen

Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

Inference Aided Reinforcement Learning for Incentive Mechanism Design in Crowdsourcing.

Zehong Hu, Yitao Liang, Jie Zhang, Zhao Li, Yang Liu

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Differentially Private Gossip Gradient Descent.

Yang Liu, Ji Liu, Tamer Basar

Proceedings of the 57th IEEE Conference on Decision and Control, 2018

Gossip Gradient Descent.

Yang Liu, Ji Liu, Tamer Basar

Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems, 2018

Incentivizing High Quality User Contributions: New Arm Generation in Bandit Learning.

Yang Liu, Chien-Ju Ho

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

An Online Learning Approach to Improving the Quality of Crowd-Sourcing.

Yang Liu, Mingyan Liu

IEEE/ACM Trans. Netw., 2017

A Note on the Unification of Adaptive Online Learning.

Wenwu He, James Tin-Yau Kwok, Ji Zhu, Yang Liu

IEEE Trans. Neural Networks Learn. Syst., 2017

Calibrated Fairness in Bandits.

Yang Liu, Goran Radanovic, Christos Dimitrakakis, Debmalya Mandal, David C. Parkes

CoRR, 2017

Subjective fairness: Fairness is in the eye of the beholder.

Christos Dimitrakakis, Yang Liu, David C. Parkes, Goran Radanovic

CoRR, 2017

Fair Optimal Stopping Policy for Matching with Mediator.

Yang Liu

Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, 2017

Machine-Learning Aided Peer Prediction.

Yang Liu, Yiling Chen

Proceedings of the 2017 ACM Conference on Economics and Computation, 2017

Crowd Learning: Improving Online Decision Making Using Crowdsourced Data.

Yang Liu, Mingyan Liu

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

An approach to distributed parametric learning with streaming data.

Ji Liu, Yang Liu, Angelia Nedic, Tamer Basar

Proceedings of the 56th IEEE Annual Conference on Decision and Control, 2017

Distributed belief averaging using sequential observations.

Yang Liu, Ji Liu, Tamer Basar, Mingyan Liu

Proceedings of the 2017 American Control Conference, 2017

Sequential Peer Prediction: Learning to Elicit Effort using Posted Prices.

Yang Liu, Yiling Chen

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016

Risky business: Fine-grained data breach prediction using business profiles.

Armin Sarabi, Parinaz Naghizadeh, Yang Liu, Mingyan Liu

J. Cybersecur., 2016

A Bandit Framework for Strategic Regression.

Yang Liu, Yiling Chen

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Learning to Incentivize: Eliciting Effort via Output Agreement.

Yang Liu, Yiling Chen

Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

Finding One's Best Crowd: Online Learning By Exploiting Source Similarity.

Yang Liu, Mingyan Liu

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015

To Stay or To Switch: Multiuser Multi-Channel Dynamic Access.

Yang Liu, Mingyan Liu

IEEE Trans. Mob. Comput., 2015

Prioritizing Security Spending: A Quantitative Analysis of Risk Distributions for Different Business Profiles.

Armin Sarabi, Parinaz Naghizadeh, Yang Liu, Mingyan Liu

Proceedings of the 14th Annual Workshop on the Economics of Information Security, 2015

Cloudy with a Chance of Breach: Forecasting Cyber Security Incidents.

Yang Liu, Armin Sarabi, Jing Zhang, Parinaz Naghizadeh, Manish Karir, Michael D. Bailey, Mingyan Liu

Proceedings of the 24th USENIX Security Symposium, 2015

An Online Approach to Dynamic Channel Access and Transmission Scheduling.

Yang Liu, Mingyan Liu

Proceedings of the 16th ACM International Symposium on Mobile Ad Hoc Networking and Computing, 2015

A regulated oligopoly multi-market model for trading smart data.

Shang-Pin Sheng, Yang Liu, Mingyan Liu

Proceedings of the 2015 IEEE Conference on Computer Communications Workshops, 2015

Optimal relay selection with non-negligible probing time.

Yang Liu, Yi Ouyang, Mingyan Liu

Proceedings of the 2015 IEEE International Conference on Communications, 2015

Detecting hidden cliques from noisy observations.

Yang Liu, Mingyan Liu

Proceedings of the 2015 IEEE International Conference on Acoustics, 2015

Predicting Cyber Security Incidents Using Feature-Based Characterization of Network-Level Malicious Activities.

Yang Liu, Jing Zhang, Armin Sarabi, Mingyan Liu, Manish Karir, Michael D. Bailey

Proceedings of the 2015 ACM International Workshop on International Workshop on Security and Privacy Analytics, 2015

2014

Sufficient Conditions on the Optimality of Myopic Sensing in Opportunistic Channel Access: A Unifying Framework.

Yang Liu, Mingyan Liu, Sahand Haji Ali Ahmad

IEEE Trans. Inf. Theory, 2014

Revisiting optimal power control: Dual effects of SNR and contention.

Yang Liu, Mingyan Liu, Jing Deng

Proceedings of the 12th International Symposium on Modeling and Optimization in Mobile, 2014

Detecting hidden propagation structure and its application to analyzing phishing.

Yang Liu, Mingyan Liu

Proceedings of the International Conference on Data Science and Advanced Analytics, 2014

2013

Evaluating Opportunistic Multi-Channel MAC: Is Diversity Gain Worth the Pain?

Yang Liu, Mingyan Liu, Jing Deng

IEEE J. Sel. Areas Commun., 2013

Revisiting Optimal Power Control: its Dual Effect on SNR and Contention.

Yang Liu, Mingyan Liu, Jing Deng

CoRR, 2013

To stay or to switch: Multiuser dynamic channel access.

Yang Liu, Mingyan Liu

Proceedings of the IEEE INFOCOM 2013, Turin, Italy, April 14-19, 2013, 2013

Group learning and opinion diffusion in a broadcast network.

Yang Liu, Mingyan Liu

Proceedings of the 51st Annual Allerton Conference on Communication, 2013

2012

Is diversity gain worth the pain: A delay comparison between opportunistic multi-channel MAC and single-channel MAC.

Yang Liu, Mingyan Liu, Jing Deng

Proceedings of the IEEE INFOCOM 2012, Orlando, FL, USA, March 25-30, 2012, 2012

2010

Design and Construction of a Prototype Secure Wireless Mesh Network Testbed.

Donglai Sun, Yue Wu, Tian Wu, Yang Liu, Ning Liu, Junhua Tang

Proceedings of the 24th IEEE International Conference on Advanced Information Networking and Applications Workshops, 2010

Two tier detection model for misbehavior of low-power nodes in virtual MIMO based wireless networks.

Yang Liu, Yue Wu, Junhua Tang

Proceedings of the Sixth International Conference on Information Assurance and Security, 2010

2009

Efficient implementation of FIR type time domain equalizers for MIMO wireless channels via M-LESQ.

Yang Liu, Ping Yi, Yue Wu

Proceedings of the IEEE 20th International Symposium on Personal, 2009