Yuekai Sun

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