← Authors

Yuekai Sun

41 papers · 2012–2025 · 6 conferences · across top CS/AI conferences

Achievements

🧭 Keyword Pioneer 🐝 Cross-Pollinator (5) πŸƒ Academic Marathon (13) 🌍 Conference Polyglot (6) 🌈 Renaissance Researcher (5) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (17) 🐣 Hot Topic Early Bird 🌟 Keyword Trendsetter Combo (3) πŸ† Keyword Champion πŸ‘‘ Triple Crown πŸ”¬ Deep Specialist (11) 🀝 Dynamic Duo (25) πŸ”₯ Unstoppable (7) ❓ The Questioner πŸ—ƒοΈ Keyword Collector (137) πŸ’Ž Century Club (41) ⚑ Prolific Year (8) πŸ“ˆ Trend Setter

Conferences

ICLR (14) NIPS (13) ICML (6) AISTATS (4) JMLR (3) EMNLP (1)

Top co-authors

Mikhail Yurochkin (25) Subha Maity (12) Moulinath Banerjee (10) Felipe Maia Polo (8) Debarghya Mukherjee (6) Songkai Xue (4) Mayank Agarwal (3) Seamus Somerstep (3) Felix Petersen (3) Leshem Choshen (3)

Research topics

Statistics (1)

Keywords

algorithmic fairness (4) individual fairness (4) high-dimensional regression (4) distribution shift (3) sparse regression (3) convex optimization (3) domain adaptation (3) domain generalization (2) statistical inference (2) probabilistic model (2) communication efficiency (2) distributed learning (2) high-dimensional statistics (2) large language model (2) graph laplacian (1) benchmark evaluation (1) variable selection (1) image classification (1) stochastic optimization (1) model selection (1)

Papers

LiveXiv - A Multi-Modal live benchmark based on Arxiv papers content ICLR 2025
Learning the Distribution Map in Reverse Causal Performative Prediction AISTATS 2025
Microfoundation inference for strategic prediction AISTATS 2025
A transfer learning framework for weak to strong generalization ICLR 2025
Aligners: Decoupling LLMs and Alignment EMNLP 2024
Learning in reverse causal strategic environments with ramifications on two sided markets ICLR 2024
An Investigation of Representation and Allocation Harms in Contrastive Learning ICLR 2024
tinyBenchmarks: evaluating LLMs with fewer examples ICML 2024
Efficient multi-prompt evaluation of LLMs NIPS 2024
Distributionally Robust Performative Prediction NIPS 2024
Weak Supervision Performance Evaluation via Partial Identification NIPS 2024
Fusing Models with Complementary Expertise ICLR 2024
Understanding new tasks through the lens of training data via exponential tilting ICLR 2023
Simple Disentanglement of Style and Content in Visual Representations ICML 2023
Conditional independence testing under misspecified inductive biases NIPS 2023
Predictor-corrector algorithms for stochastic optimization under gradual distribution shift ICLR 2023
ISAAC Newton: Input-based Approximate Curvature for Newton's Method ICLR 2023
Minimax optimal approaches to the label shift problem in non-parametric settings JMLR 2022
Calibrated Data-Dependent Constraints with Exact Satisfaction Guarantees NIPS 2022
Domain Adaptation meets Individual Fairness. And they get along. NIPS 2022
Meta-analysis of heterogeneous data: integrative sparse regression in high-dimensions JMLR 2022
Statistical inference for individual fairness ICLR 2021
SenSeI: Sensitive Set Invariance for Enforcing Individual Fairness ICLR 2021
Individually Fair Gradient Boosting ICLR 2021
Post-processing for Individual Fairness NIPS 2021
Does enforcing fairness mitigate biases caused by subpopulation shift? NIPS 2021
On sensitivity of meta-learning to support data NIPS 2021
Outlier-Robust Optimal Transport ICML 2021
Individually Fair Rankings ICLR 2021
Auditing ML Models for Individual Bias and Unfairness AISTATS 2020
Two Simple Ways to Learn Individual Fairness Metrics from Data ICML 2020
Training individually fair ML models with sensitive subspace robustness ICLR 2020
Federated Learning with Matched Averaging ICLR 2020
Dirichlet Simplex Nest and Geometric Inference ICML 2019
Precision Matrix Estimation with Noisy and Missing Data AISTATS 2019
Communication-efficient Sparse Regression JMLR 2017
Feature-distributed sparse regression: a screen-and-clean approach NIPS 2016
Evaluating the statistical significance of biclusters NIPS 2015
Learning Mixtures of Linear Classifiers ICML 2014
On model selection consistency of penalized M-estimators: a geometric theory NIPS 2013
Proximal Newton-type methods for convex optimization NIPS 2012