Xueru Zhang
21 papers · 2018–2026 · 6 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
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πΊοΈ Taxonomy Completionist (33) π Conference Polyglot Β· Silver π Academic Marathon Β· Sprint π Interdisciplinary Bridge Β· Silver π£ Hot Topic Early Bird
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Grand Slam
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Keyword Champion
(7)
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Triple Crown
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Deep Specialist
(11)
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Renaissance Researcher
(6)
π₯
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The Questioner
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Prolific Year Β· Productive
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Century Club Β· Bronze
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Trend Setter
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Keyword Collector
(96)
Top co-authors
Research topics
Machine Learning
(16)
Application Areas
(14)
Artificial Intelligence
(11)
Core AI
(9)
Optimization & Theory
(5)
Deep Learning
(3)
Core Methods
(3)
Computer Vision
(2)
Learning Paradigms
(2)
Learning Types
(2)
Models
(2)
Data Science & Analytics
(1)
Mathematics & Optimization
(1)
Reinforcement Learning
(1)
Security & Privacy
(1)
Keywords
algorithmic fairness
(7)
bias mitigation
(3)
representation learning
(3)
differential privacy
(3)
supervised learning
(2)
domain generalization
(2)
self-consuming loop
(2)
performative prediction
(2)
fairness constraint
(2)
equal opportunity
(2)
distribution shift
(2)
equilibrium analysis
(2)
synthetic data
(2)
deep learning
(1)
privacy preservation
(1)
in-context learning
(1)
non-convex optimization
(1)
causal inference
(1)
sequential decision making
(1)
markov decision process
(1)
Papers
Achieving Fairness Without Harm via Selective Demographic Experts
AAAI 2026
Addressing Polarization and Unfairness in Performative Prediction
AAAI 2026
Observations and Remedies for Large Language Model Bias in Self-Consuming Performative Loop
ACL 2026
Stabilizing Self-Consuming Diffusion Models with Latent Space Filtering
AAAI 2026
Understanding Structured Financial Data with LLMs: A Case Study on Fraud Detection
ACL 2026
DroughtSet: Understanding Drought Through Spatial-Temporal Learning
AAAI 2025
Open-Set Heterogeneous Domain Adaptation: Theoretical Analysis and Algorithm
AAAI 2025
Self-Consuming Generative Models with Adversarially Curated Data
ICML 2025
Automating Data Annotation under Strategic Human Agents: Risks and Potential Solutions
NeurIPS 2024
Non-stationary Domain Generalization: Theory and Algorithm
UAI 2024
Performative Federated Learning: A Solution to Model-Dependent and Heterogeneous Distribution Shifts
AAAI 2024
Privacy-Aware Randomized Quantization via Linear Programming
UAI 2024
Counterfactually Fair Representation
NeurIPS 2023
Fairness and Accuracy under Domain Generalization
ICLR 2023
Loss Balancing for Fair Supervised Learning
ICML 2023
Fairness Interventions as (Dis)Incentives for Strategic Manipulation
ICML 2022
Fair Sequential Selection Using Supervised Learning Models
NeurIPS 2021
Improving Fairness and Privacy in Selection Problems
AAAI 2021
How do fair decisions fare in long-term qualification?
NeurIPS 2020
Group Retention when Using Machine Learning in Sequential Decision Making: the Interplay between User Dynamics and Fairness
NeurIPS 2019
Improving the Privacy and Accuracy of ADMM-Based Distributed Algorithms
ICML 2018