Sun, Yuekai

49 publications

ICLR 2025 A Transfer Learning Framework for Weak to Strong Generalization Seamus Somerstep, Felipe Maia Polo, Moulinath Banerjee, Yaacov Ritov, Mikhail Yurochkin, Yuekai Sun

NeurIPS 2025 Bridging Human and LLM Judgments: Understanding and Narrowing the Gap Felipe Maia Polo, Xinhe Wang, Mikhail Yurochkin, Gongjun Xu, Moulinath Banerjee, Yuekai Sun

TMLR 2025 Dynamic Pricing in the Linear Valuation Model Using Shape Constraints Daniele Bracale, Moulinath Banerjee, Yuekai Sun, Salam Turki, Kevin Stoll

TMLR 2025 How Does Overparametrization Affect Performance on Minority Groups? Saptarshi Roy, Subha Maity, Songkai Xue, Mikhail Yurochkin, Yuekai Sun

AISTATS 2025 Learning the Distribution mAP in Reverse Causal Performative Prediction Daniele Bracale, Subha Maity, Yuekai Sun, Moulinath Banerjee

ICLR 2025 LiveXiv - A Multi-Modal Live Benchmark Based on arXiv Papers Content Nimrod Shabtay, Felipe Maia Polo, Sivan Doveh, Wei Lin, Muhammad Jehanzeb Mirza, Leshem Choshen, Mikhail Yurochkin, Yuekai Sun, Assaf Arbelle, Leonid Karlinsky, Raja Giryes

AISTATS 2025 Microfoundation Inference for Strategic Prediction Daniele Bracale, Subha Maity, Felipe Maia Polo, Seamus Somerstep, Moulinath Banerjee, Yuekai Sun

NeurIPS 2025 Sloth: Scaling Laws for LLM Skills to Predict Multi-Benchmark Performance Across Families Felipe Maia Polo, Seamus Somerstep, Leshem Choshen, Yuekai Sun, Mikhail Yurochkin

ICMLW 2024 A Statistical Framework for Weak-to-Strong Generalization Seamus Somerstep, Felipe Maia Polo, Moulinath Banerjee, Yaacov Ritov, Mikhail Yurochkin, Yuekai Sun

ICLR 2024 An Investigation of Representation and Allocation Harms in Contrastive Learning Subha Maity, Mayank Agarwal, Mikhail Yurochkin, Yuekai Sun

NeurIPS 2024 Distributionally Robust Performative Prediction Songkai Xue, Yuekai Sun

NeurIPS 2024 Efficient Multi-Prompt Evaluation of LLMs Felipe Maia Polo, Ronald Xu, Lucas Weber, Mírian Silva, Onkar Bhardwaj, Leshem Choshen, Allysson Flavio Melo de Oliveira, Yuekai Sun, Mikhail Yurochkin

ICMLW 2024 Efficient Multi-Prompt Evaluation of LLMs Felipe Maia Polo, Ronald Xu, Lucas Weber, Mírian Silva, Onkar Bhardwaj, Leshem Choshen, Allysson Flavio Melo de Oliveira, Yuekai Sun, Mikhail Yurochkin

ICLR 2024 Fusing Models with Complementary Expertise Hongyi Wang, Felipe Maia Polo, Yuekai Sun, Souvik Kundu, Eric Xing, Mikhail Yurochkin

ICLR 2024 Learning in Reverse Causal Strategic Environments with Ramifications on Two Sided Markets Seamus Somerstep, Yuekai Sun, Yaacov Ritov

NeurIPS 2024 Weak Supervision Performance Evaluation via Partial Identification Felipe Maia Polo, Subha Maity, Mikhail Yurochkin, Moulinath Banerjee, Yuekai Sun

ICML 2024 tinyBenchmarks: Evaluating LLMs with Fewer Examples Felipe Maia Polo, Lucas Weber, Leshem Choshen, Yuekai Sun, Gongjun Xu, Mikhail Yurochkin

NeurIPS 2023 Conditional Independence Testing Under Misspecified Inductive Biases Felipe Maia Polo, Yuekai Sun, Moulinath Banerjee

NeurIPSW 2023 Estimating Fréchet Bounds for Validating Programmatic Weak Supervision Felipe Maia Polo, Mikhail Yurochkin, Moulinath Banerjee, Subha Maity, Yuekai Sun

NeurIPSW 2023 Fusing Models with Complementary Expertise Hongyi Wang, Felipe Maia Polo, Yuekai Sun, Souvik Kundu, Eric P. Xing, Mikhail Yurochkin

ICLR 2023 ISAAC Newton: Input-Based Approximate Curvature for Newton's Method Felix Petersen, Tobias Sutter, Christian Borgelt, Dongsung Huh, Hilde Kuehne, Yuekai Sun, Oliver Deussen

NeurIPSW 2023 LLM Routing with Benchmark Datasets Tal Shnitzer, Anthony Ou, Mírian Silva, Kate Soule, Yuekai Sun, Justin Solomon, Neil Thompson, Mikhail Yurochkin

ICLR 2023 Predictor-Corrector Algorithms for Stochastic Optimization Under Gradual Distribution Shift Subha Maity, Debarghya Mukherjee, Moulinath Banerjee, Yuekai Sun

ICML 2023 Simple Disentanglement of Style and Content in Visual Representations Lilian Ngweta, Subha Maity, Alex Gittens, Yuekai Sun, Mikhail Yurochkin

ICLR 2023 Understanding New Tasks Through the Lens of Training Data via Exponential Tilting Subha Maity, Mikhail Yurochkin, Moulinath Banerjee, Yuekai Sun

NeurIPS 2022 Calibrated Data-Dependent Constraints with Exact Satisfaction Guarantees Songkai Xue, Yuekai Sun, Mikhail Yurochkin

NeurIPS 2022 Domain Adaptation Meets Individual Fairness. and They Get Along. Debarghya Mukherjee, Felix Petersen, Mikhail Yurochkin, Yuekai Sun

JMLR 2022 Meta-Analysis of Heterogeneous Data: Integrative Sparse Regression in High-Dimensions Subha Maity, Yuekai Sun, Moulinath Banerjee

JMLR 2022 Minimax Optimal Approaches to the Label Shift Problem in Non-Parametric Settings Subha Maity, Yuekai Sun, Moulinath Banerjee

NeurIPS 2021 Does Enforcing Fairness Mitigate Biases Caused by Subpopulation Shift? Subha Maity, Debarghya Mukherjee, Mikhail Yurochkin, Yuekai Sun

ICLR 2021 Individually Fair Gradient Boosting Alexander Vargo, Fan Zhang, Mikhail Yurochkin, Yuekai Sun

ICLR 2021 Individually Fair Rankings Amanda Bower, Hamid Eftekhari, Mikhail Yurochkin, Yuekai Sun

NeurIPS 2021 On Sensitivity of Meta-Learning to Support Data Mayank Agarwal, Mikhail Yurochkin, Yuekai Sun

ICML 2021 Outlier-Robust Optimal Transport Debarghya Mukherjee, Aritra Guha, Justin M Solomon, Yuekai Sun, Mikhail Yurochkin

NeurIPS 2021 Post-Processing for Individual Fairness Felix Petersen, Debarghya Mukherjee, Yuekai Sun, Mikhail Yurochkin

ICLR 2021 SenSeI: Sensitive Set Invariance for Enforcing Individual Fairness Mikhail Yurochkin, Yuekai Sun

ICLR 2021 Statistical Inference for Individual Fairness Subha Maity, Songkai Xue, Mikhail Yurochkin, Yuekai Sun

AISTATS 2020 Auditing ML Models for Individual Bias and Unfairness Songkai Xue, Mikhail Yurochkin, Yuekai Sun

ICLR 2020 Federated Learning with Matched Averaging Hongyi Wang, Mikhail Yurochkin, Yuekai Sun, Dimitris Papailiopoulos, Yasaman Khazaeni

ICLR 2020 Training Individually Fair ML Models with Sensitive Subspace Robustness Mikhail Yurochkin, Amanda Bower, Yuekai Sun

ICML 2020 Two Simple Ways to Learn Individual Fairness Metrics from Data Debarghya Mukherjee, Mikhail Yurochkin, Moulinath Banerjee, Yuekai Sun

ICML 2019 Dirichlet Simplex Nest and Geometric Inference Mikhail Yurochkin, Aritra Guha, Yuekai Sun, Xuanlong Nguyen

AISTATS 2019 Precision Matrix Estimation with Noisy and Missing Data Roger Fan, Byoungwook Jang, Yuekai Sun, Shuheng Zhou

JMLR 2017 Communication-Efficient Sparse Regression Jason D. Lee, Qiang Liu, Yuekai Sun, Jonathan E. Taylor

NeurIPS 2016 Feature-Distributed Sparse Regression: A Screen-and-Clean Approach Jiyan Yang, Michael W. Mahoney, Michael Saunders, Yuekai Sun

NeurIPS 2015 Evaluating the Statistical Significance of Biclusters Jason Lee, Yuekai Sun, Jonathan E Taylor

ICML 2014 Learning Mixtures of Linear Classifiers Yuekai Sun, Stratis Ioannidis, Andrea Montanari

NeurIPS 2013 On Model Selection Consistency of Penalized M-Estimators: A Geometric Theory Jason Lee, Yuekai Sun, Jonathan E Taylor

NeurIPS 2012 Proximal Newton-Type Methods for Convex Optimization Jason Lee, Yuekai Sun, Michael Saunders