Yang Liu

Orcid: 0000-0001-8420-6011

Affiliations:
  • University of California, Santa Cruz, CA, USA
  • Harvard University, Cambridge, MA, USA (former)
  • University of Michigan, Department of EECS, Ann Arbor, MI, USA (PhD 2015)


According to our database1, Yang Liu authored at least 120 papers between 2009 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Online presence:

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Bibliography

2024
Human-Instruction-Free LLM Self-Alignment with Limited Samples.
CoRR, 2024

Fair Participation via Sequential Policies.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
A Parametrical Model for Instance-Dependent Label Noise.
IEEE Trans. Pattern Anal. Mach. Intell., December, 2023

Machine truth serum: a surprisingly popular approach to improving ensemble methods.
Mach. Learn., March, 2023

Performative Federated Learning: A Solution to Model-Dependent and Heterogeneous Distribution Shifts.
CoRR, 2023

Do humans and machines have the same eyes? Human-machine perceptual differences on image classification.
CoRR, 2023

Fairness Improves Learning from Noisily Labeled Long-Tailed Data.
CoRR, 2023

4th Crowd Science Workshop - CANDLE: Collaboration of Humans and Learning Algorithms for Data Labeling.
Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining, 2023

Long-Term Fairness with Unknown Dynamics.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

To Aggregate or Not? Learning with Separate Noisy Labels.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Incentivizing Recourse through Auditing in Strategic Classification.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Weak Proxies are Sufficient and Preferable for Fairness with Missing Sensitive Attributes.
Proceedings of the International Conference on Machine Learning, 2023

Distributionally Robust Post-hoc Classifiers under Prior Shifts.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Mitigating Memorization of Noisy Labels via Regularization between Representations.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Group-Fair Classification with Strategic Agents.
Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, 2023

Auditing for Federated Learning: A Model Elicitation Approach.
Proceedings of the Fifth International Conference on Distributed Artificial Intelligence, 2023

Towards User Guided Actionable Recourse.
Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society, 2023

Adaptive Adversarial Training Does Not Increase Recourse Costs.
Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society, 2023

2022
Surrogate Scoring Rules.
ACM Trans. Economics and Comput., September, 2022

Evaluating Fairness Without Sensitive Attributes: A Framework Using Only Auxiliary Models.
CoRR, 2022

Conjugate Natural Selection.
CoRR, 2022

Adaptive Data Debiasing through Bounded Exploration.
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.
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.
Proceedings of the 26th International Conference on Pattern Recognition, 2022

Beyond Images: Label Noise Transition Matrix Estimation for Tasks with Lower-Quality Features.
Proceedings of the International Conference on Machine Learning, 2022

Detecting Corrupted Labels Without Training a Model to Predict.
Proceedings of the International Conference on Machine Learning, 2022

Estimating Instance-dependent Bayes-label Transition Matrix using a Deep Neural Network.
Proceedings of the International Conference on Machine Learning, 2022

To Smooth or Not? When Label Smoothing Meets Noisy Labels.
Proceedings of the International Conference on Machine Learning, 2022

Understanding Instance-Level Impact of Fairness Constraints.
Proceedings of the International Conference on Machine Learning, 2022

The Rich Get Richer: Disparate Impact of Semi-Supervised Learning.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Learning with Noisy Labels Revisited: A Study Using Real-World Human Annotations.
Proceedings of the Tenth International Conference on Learning Representations, 2022

DuelGAN: A Duel Between Two Discriminators Stabilizes the GAN Training.
Proceedings of the Computer Vision - ECCV 2022, 2022

Fair Classification with Instance-dependent Label Noise.
Proceedings of the 1st Conference on Causal Learning and Reasoning, 2022

Learning and Mining with Noisy Labels.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

Robust Stochastic Bandit algorithms to defend against Oracle attack using Sample Dropout.
Proceedings of the IEEE International Conference on Big Data, 2022

Assessing Multilingual Fairness in Pre-trained Multimodal Representations.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2022, 2022

Interpretable Research Replication Prediction via Variational Contextual Consistency Sentence Masking.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2022, 2022

2021
Federated Bandit: A Gossiping Approach.
Proc. ACM Meas. Anal. Comput. Syst., 2021

Adaptive Data Debiasing through Bounded Exploration and Fairness.
CoRR, 2021

Demystifying How Self-Supervised Features Improve Training from Noisy Labels.
CoRR, 2021

A Good Representation Detects Noisy Labels.
CoRR, 2021

Induced Domain Adaptation.
CoRR, 2021

Understanding (Generalized) Label Smoothing when Learning with Noisy Labels.
CoRR, 2021

Estimating Instance-dependent Label-noise Transition Matrix using DNNs.
CoRR, 2021

PeerGAN: Generative Adversarial Networks with a Competing Peer Discriminator.
CoRR, 2021

Policy Learning Using Weak Supervision.
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.
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.
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.
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.
Proceedings of the 38th International Conference on Machine Learning, 2021

When Optimizing f-Divergence is Robust with Label Noise.
Proceedings of the 9th International Conference on Learning Representations, 2021

Learning with Instance-Dependent Label Noise: A Sample Sieve Approach.
Proceedings of the 9th International Conference on Learning Representations, 2021

Forecast Aggregation via Peer Prediction.
Proceedings of the Ninth AAAI Conference on Human Computation and Crowdsourcing, 2021

Fair Classification with Group-Dependent Label Noise.
Proceedings of the FAccT '21: 2021 ACM Conference on Fairness, 2021

Are Gender-Neutral Queries Really Gender-Neutral? Mitigating Gender Bias in Image Search.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

A Second-Order Approach to Learning With Instance-Dependent Label Noise.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

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

Linear Models are Robust Optimal Under Strategic Behavior.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
Strategic Recourse in Linear Classification.
CoRR, 2020

Incentives for Federated Learning: a Hypothesis Elicitation Approach.
CoRR, 2020

Replication Markets: Results, Lessons, Challenges and Opportunities in AI Replication.
CoRR, 2020

Fair Bandit Learning with Delayed Impact of Actions.
CoRR, 2020

Distributed learning of average belief over networks using sequential observations.
Autom., 2020

How do fairness definitions fare? Testing public attitudes towards three algorithmic definitions of fairness in loan allocations.
Artif. Intell., 2020

How do fair decisions fare in long-term qualification?
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.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Learning Strategy-Aware Linear Classifiers.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Research Replication Prediction Using Weakly Supervised Learning.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020

Differentially Private Contextual Dynamic Pricing.
Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, 2020

Reinforcement Learning with Perturbed Rewards.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Grinding the Space: Learning to Classify Against Strategic Agents.
CoRR, 2019

Credible Sample Elicitation by Deep Learning, for Deep Learning.
CoRR, 2019

Machine Truth Serum.
CoRR, 2019

Fairness without Harm: Decoupled Classifiers with Preference Guarantees.
Proceedings of the 36th International Conference on Machine Learning, 2019

Actionable Recourse in Linear Classification.
Proceedings of the Conference on Fairness, Accountability, and Transparency, 2019

How Do Fairness Definitions Fare?: Examining Public Attitudes Towards Algorithmic Definitions of Fairness.
Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, 2019

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

Randomized Wagering Mechanisms.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
To regularize or not: Revisiting SGD with simple algorithms and experimental studies.
Expert Syst. Appl., 2018

Inference Aided Reinforcement Learning for Incentive Mechanism Design in Crowdsourcing.
CoRR, 2018

Surrogate Scoring Rules and a Dominant Truth Serum for Information Elicitation.
CoRR, 2018

From Patching Delays to Infection Symptoms: Using Risk Profiles for an Early Discovery of Vulnerabilities Exploited in the Wild.
Proceedings of the 27th USENIX Security Symposium, 2018

Active Information Acquisition for Linear Optimization.
Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

Inference Aided Reinforcement Learning for Incentive Mechanism Design in Crowdsourcing.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Differentially Private Gossip Gradient Descent.
Proceedings of the 57th IEEE Conference on Decision and Control, 2018

Gossip Gradient Descent.
Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems, 2018

Incentivizing High Quality User Contributions: New Arm Generation in Bandit Learning.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
An Online Learning Approach to Improving the Quality of Crowd-Sourcing.
IEEE/ACM Trans. Netw., 2017

A Note on the Unification of Adaptive Online Learning.
IEEE Trans. Neural Networks Learn. Syst., 2017

Calibrated Fairness in Bandits.
CoRR, 2017

Subjective fairness: Fairness is in the eye of the beholder.
CoRR, 2017

Fair Optimal Stopping Policy for Matching with Mediator.
Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, 2017

Machine-Learning Aided Peer Prediction.
Proceedings of the 2017 ACM Conference on Economics and Computation, 2017

Crowd Learning: Improving Online Decision Making Using Crowdsourced Data.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

An approach to distributed parametric learning with streaming data.
Proceedings of the 56th IEEE Annual Conference on Decision and Control, 2017

Distributed belief averaging using sequential observations.
Proceedings of the 2017 American Control Conference, 2017

Sequential Peer Prediction: Learning to Elicit Effort using Posted Prices.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
Risky business: Fine-grained data breach prediction using business profiles.
J. Cybersecur., 2016

A Bandit Framework for Strategic Regression.
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.
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

Finding One's Best Crowd: Online Learning By Exploiting Source Similarity.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015
To Stay or To Switch: Multiuser Multi-Channel Dynamic Access.
IEEE Trans. Mob. Comput., 2015

Prioritizing Security Spending: A Quantitative Analysis of Risk Distributions for Different Business Profiles.
Proceedings of the 14th Annual Workshop on the Economics of Information Security, 2015

Cloudy with a Chance of Breach: Forecasting Cyber Security Incidents.
Proceedings of the 24th USENIX Security Symposium, 2015

An Online Approach to Dynamic Channel Access and Transmission Scheduling.
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.
Proceedings of the 2015 IEEE Conference on Computer Communications Workshops, 2015

Optimal relay selection with non-negligible probing time.
Proceedings of the 2015 IEEE International Conference on Communications, 2015

Detecting hidden cliques from noisy observations.
Proceedings of the 2015 IEEE International Conference on Acoustics, 2015

Predicting Cyber Security Incidents Using Feature-Based Characterization of Network-Level Malicious Activities.
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.
IEEE Trans. Inf. Theory, 2014

Revisiting optimal power control: Dual effects of SNR and contention.
Proceedings of the 12th International Symposium on Modeling and Optimization in Mobile, 2014

Detecting hidden propagation structure and its application to analyzing phishing.
Proceedings of the International Conference on Data Science and Advanced Analytics, 2014

2013
Evaluating Opportunistic Multi-Channel MAC: Is Diversity Gain Worth the Pain?
IEEE J. Sel. Areas Commun., 2013

Revisiting Optimal Power Control: its Dual Effect on SNR and Contention.
CoRR, 2013

To stay or to switch: Multiuser dynamic channel access.
Proceedings of the IEEE INFOCOM 2013, Turin, Italy, April 14-19, 2013, 2013

Group learning and opinion diffusion in a broadcast network.
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.
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.
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.
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.
Proceedings of the IEEE 20th International Symposium on Personal, 2009


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