Yuekai Sun - RankMe

107 papers A* 29A 4Journal 65Unranked 7

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Maximin Relative Improvement: Fair Learning as a Bargaining Problem. CoRR Jiwoo Han, Moulinath Banerjee, Yuekai Sun
2025	J	`jnl`	A Latent Variable Framework for Scaling Laws in Large Language Models. CoRR Peiyao Cai, Chengyu Cui, Felipe Maia Polo, Seamus Somerstep, Leshem Choshen, Mikhail Yurochkin, Moulinath Banerjee, Yuekai Sun, Kean Ming Tan, Gongjun Xu
2025	A*	`conf`	A transfer learning framework for weak to strong generalization. ICLR Seamus Somerstep, Felipe Maia Polo, Moulinath Banerjee, Yaacov Ritov, Mikhail Yurochkin, Yuekai Sun
2025	J	`jnl`	Bridging Human and LLM Judgments: Understanding and Narrowing the Gap. CoRR Felipe Maia Polo, Xinhe Wang, Mikhail Yurochkin, Gongjun Xu, Moulinath Banerjee, Yuekai Sun
2025	J	`jnl`	Dynamic Pricing in the Linear Valuation Model using Shape Constraints. CoRR Daniele Bracale, Moulinath Banerjee, Yuekai Sun, Kevin Stoll, Salam Turki
2025	J	`jnl`	Dynamic Pricing in the Linear Valuation Model using Shape Constraints. Trans. Mach. Learn. Res. Daniele Bracale, Moulinath Banerjee, Yuekai Sun, Salam Turki, Kevin Stoll
2025	J	`jnl`	How does overparametrization affect performance on minority groups? Trans. Mach. Learn. Res. Saptarshi Roy, Subha Maity, Songkai Xue, Mikhail Yurochkin, Yuekai Sun
2025	J	`jnl`	Joint optimization of computation offloading and power control in user-centric networks based on dual layer mobile edge computing. Ad Hoc Networks Peiying Zhang, Yuekai Sun, Lizhuang Tan, Maher Guizani, Mohammad Kamrul Hasan, Jian Wang
2025	A	`conf`	Learning the Distribution Map in Reverse Causal Performative Prediction. AISTATS Daniele Bracale, Subha Maity, Yuekai Sun, Moulinath Banerjee
2025	J	`jnl`	Learning to Choose or Choosing to Learn: Best-of-N vs. Supervised Fine-Tuning for Bit String Generation. CoRR Seamus Somerstep, Vinod Raman, Unique Subedi, Yuekai Sun
2025	J	`jnl`	Likelihood-Free Estimation for Spatiotemporal Hawkes processes with missing data and application to predictive policing. CoRR Pramit Das, Moulinath Banerjee, Yuekai Sun
2025	J	`jnl`	Limitations of refinement methods for weak to strong generalization. CoRR Seamus Somerstep, Yaacov Ritov, Mikhail Yurochkin, Subha Maity, Yuekai Sun
2025	A*	`conf`	LiveXiv - A Multi-Modal live benchmark based on Arxiv papers content. ICLR Nimrod Shabtay, Felipe Maia Polo, Sivan Doveh, Wei Lin, Muhammad Jehanzeb Mirza, Leshem Choshen, Mikhail Yurochkin, Yuekai Sun, Assaf Arbelle, Leonid Karlinsky, Raja Giryes
2025	A	`conf`	Microfoundation inference for strategic prediction. AISTATS Daniele Bracale, Subha Maity, Felipe Maia Polo, Seamus Somerstep, Moulinath Banerjee, Yuekai Sun
2025	J	`jnl`	Online Price Competition under Generalized Linear Demands. CoRR Daniele Bracale, Moulinath Banerjee, Cong Shi, Yuekai Sun
2025	J	`jnl`	Optimal Intervention for Self-triggering Spatial Networks with Application to Urban Crime Analytics. CoRR Pramit Das, Moulinath Banerjee, Yuekai Sun
2025	J	`jnl`	Optimal Nonlinear Online Learning under Sequential Price Competition via s-Concavity. CoRR Daniele Bracale, Moulinath Banerjee, Cong Shi, Yuekai Sun
2024	J	`jnl`	A statistical framework for weak-to-strong generalization. CoRR Seamus Somerstep, Felipe Maia Polo, Moulinath Banerjee, Yaacov Ritov, Mikhail Yurochkin, Yuekai Sun
2024	—	`conf`	Algorithmic Fairness in Performative Policy Learning: Escaping the Impossibility of Group Fairness. FAccT Seamus Somerstep, Yaacov Ritov, Yuekai Sun
2024	J	`jnl`	Algorithmic Fairness in Performative Policy Learning: Escaping the Impossibility of Group Fairness. CoRR Seamus Somerstep, Yaacov Ritov, Yuekai Sun
2024	—	`conf`	Aligners: Decoupling LLMs and Alignment. EMNLP (Findings) Lilian Ngweta, Mayank Agarwal, Subha Maity, Alex Gittens, Yuekai Sun, Mikhail Yurochkin
2024	—	`conf`	Aligners: Decoupling LLMs and Alignment. Tiny Papers @ ICLR Lilian Ngweta, Mayank Agarwal, Subha Maity, Alex Gittens, Yuekai Sun, Mikhail Yurochkin
2024	J	`jnl`	Aligners: Decoupling LLMs and Alignment. CoRR Lilian Ngweta, Mayank Agarwal, Subha Maity, Alex Gittens, Yuekai Sun, Mikhail Yurochkin
2024	A*	`conf`	An Investigation of Representation and Allocation Harms in Contrastive Learning. ICLR Subha Maity, Mayank Agarwal, Mikhail Yurochkin, Yuekai Sun
2024	A*	`conf`	Distributionally Robust Performative Prediction. NeurIPS Songkai Xue, Yuekai Sun
2024	J	`jnl`	Distributionally Robust Performative Prediction. CoRR Songkai Xue, Yuekai Sun
2024	A*	`conf`	Efficient multi-prompt evaluation of LLMs. NeurIPS Felipe Maia Polo, Ronald Xu, Lucas Weber, Mírian Silva, Onkar Bhardwaj, Leshem Choshen, Allysson Flavio Melo de Oliveira, Yuekai Sun, Mikhail Yurochkin
2024	J	`jnl`	Efficient multi-prompt evaluation of LLMs. CoRR Felipe Maia Polo, Ronald Xu, Lucas Weber, Mírian Silva, Onkar Bhardwaj, Leshem Choshen, Allysson Flavio Melo de Oliveira, Yuekai Sun, Mikhail Yurochkin
2024	A*	`conf`	Fusing Models with Complementary Expertise. ICLR Hongyi Wang, Felipe Maia Polo, Yuekai Sun, Souvik Kundu, Eric P. Xing, Mikhail Yurochkin
2024	J	`jnl`	Learning In Reverse Causal Strategic Environments With Ramifications on Two Sided Markets. CoRR Seamus Somerstep, Yuekai Sun, Yaacov Ritov
2024	A*	`conf`	Learning in reverse causal strategic environments with ramifications on two sided markets. ICLR Seamus Somerstep, Yuekai Sun, Yaacov Ritov
2024	J	`jnl`	Learning the Distribution Map in Reverse Causal Performative Prediction. CoRR Daniele Bracale, Subha Maity, Moulinath Banerjee, Yuekai Sun
2024	J	`jnl`	LiveXiv - A Multi-Modal Live Benchmark Based on Arxiv Papers Content. CoRR Nimrod Shabtay, Felipe Maia Polo, Sivan Doveh, Wei Lin, Muhammad Jehanzeb Mirza, Leshem Choshen, Mikhail Yurochkin, Yuekai Sun, Assaf Arbelle, Leonid Karlinsky, Raja Giryes
2024	J	`jnl`	Microfoundation Inference for Strategic Prediction. CoRR Daniele Bracale, Subha Maity, Felipe Maia Polo, Seamus Somerstep, Moulinath Banerjee, Yuekai Sun
2024	J	`jnl`	Prompt Exploration with Prompt Regression. CoRR Michael Feffer, Ronald Xu, Yuekai Sun, Mikhail Yurochkin
2024	J	`jnl`	Sloth: scaling laws for LLM skills to predict multi-benchmark performance across families. CoRR Felipe Maia Polo, Seamus Somerstep, Leshem Choshen, Yuekai Sun, Mikhail Yurochkin
2024	A*	`conf`	Weak Supervision Performance Evaluation via Partial Identification. NeurIPS Felipe Maia Polo, Subha Maity, Mikhail Yurochkin, Moulinath Banerjee, Yuekai Sun
2024	A*	`conf`	tinyBenchmarks: evaluating LLMs with fewer examples. ICML Felipe Maia Polo, Lucas Weber, Leshem Choshen, Yuekai Sun, Gongjun Xu, Mikhail Yurochkin
2024	J	`jnl`	tinyBenchmarks: evaluating LLMs with fewer examples. CoRR Felipe Maia Polo, Lucas Weber, Leshem Choshen, Yuekai Sun, Gongjun Xu, Mikhail Yurochkin
2023	J	`jnl`	An Investigation of Representation and Allocation Harms in Contrastive Learning. CoRR Subha Maity, Mayank Agarwal, Mikhail Yurochkin, Yuekai Sun
2023	J	`jnl`	Calibrated Data-Dependent Constraints with Exact Satisfaction Guarantees. CoRR Songkai Xue, Yuekai Sun, Mikhail Yurochkin
2023	A*	`conf`	Conditional independence testing under misspecified inductive biases. NeurIPS Felipe Maia Polo, Yuekai Sun, Moulinath Banerjee
2023	J	`jnl`	Conditional independence testing under model misspecification. CoRR Felipe Maia Polo, Yuekai Sun, Moulinath Banerjee
2023	J	`jnl`	Estimating Fréchet bounds for validating programmatic weak supervision. CoRR Felipe Maia Polo, Mikhail Yurochkin, Moulinath Banerjee, Subha Maity, Yuekai Sun
2023	J	`jnl`	Fusing Models with Complementary Expertise. CoRR Hongyi Wang, Felipe Maia Polo, Yuekai Sun, Souvik Kundu, Eric P. Xing, Mikhail Yurochkin
2023	A*	`conf`	ISAAC Newton: Input-based Approximate Curvature for Newton's Method. ICLR Felix Petersen, Tobias Sutter, Christian Borgelt, Dongsung Huh, Hilde Kuehne, Yuekai Sun, Oliver Deussen
2023	J	`jnl`	ISAAC Newton: Input-based Approximate Curvature for Newton's Method. CoRR Felix Petersen, Tobias Sutter, Christian Borgelt, Dongsung Huh, Hilde Kuehne, Yuekai Sun, Oliver Deussen
2023	J	`jnl`	Large Language Model Routing with Benchmark Datasets. CoRR Tal Shnitzer, Anthony Ou, Mírian Silva, Kate Soule, Yuekai Sun, Justin Solomon, Neil Thompson, Mikhail Yurochkin
2023	A*	`conf`	Predictor-corrector algorithms for stochastic optimization under gradual distribution shift. ICLR Subha Maity, Debarghya Mukherjee, Moulinath Banerjee, Yuekai Sun
2023	A*	`conf`	Simple Disentanglement of Style and Content in Visual Representations. ICML Lilian Ngweta, Subha Maity, Alex Gittens, Yuekai Sun, Mikhail Yurochkin
2023	J	`jnl`	Simple Disentanglement of Style and Content in Visual Representations. CoRR Lilian Ngweta, Subha Maity, Alex Gittens, Yuekai Sun, Mikhail Yurochkin
2023	A*	`conf`	Understanding new tasks through the lens of training data via exponential tilting. ICLR Subha Maity, Mikhail Yurochkin, Moulinath Banerjee, Yuekai Sun
2022	J	`jnl`	Achieving Representative Data via Convex Hull Feasibility Sampling Algorithms. CoRR Laura Niss, Yuekai Sun, Ambuj Tewari
2022	A*	`conf`	Calibrated Data-Dependent Constraints with Exact Satisfaction Guarantees. NeurIPS Songkai Xue, Yuekai Sun, Mikhail Yurochkin
2022	—	`ch.`	Communication-Efficient Model Fusion. Federated Learning Mikhail Yurochkin, Yuekai Sun
2022	A*	`conf`	Domain Adaptation meets Individual Fairness. And they get along. NeurIPS Debarghya Mukherjee, Felix Petersen, Mikhail Yurochkin, Yuekai Sun
2022	J	`jnl`	Domain Adaptation meets Individual Fairness. And they get along. CoRR Debarghya Mukherjee, Felix Petersen, Mikhail Yurochkin, Yuekai Sun
2022	J	`jnl`	How does overparametrization affect performance on minority groups? CoRR Subha Maity, Saptarshi Roy, Songkai Xue, Mikhail Yurochkin, Yuekai Sun
2022	J	`jnl`	Meta-analysis of heterogeneous data: integrative sparse regression in high-dimensions. J. Mach. Learn. Res. Subha Maity, Yuekai Sun, Moulinath Banerjee
2022	J	`jnl`	Minimax optimal approaches to the label shift problem in non-parametric settings. J. Mach. Learn. Res. Subha Maity, Yuekai Sun, Moulinath Banerjee
2022	—	`ch.`	Personalization in Federated Learning. Federated Learning Mayank Agarwal, Mikhail Yurochkin, Yuekai Sun
2022	J	`jnl`	Predictor-corrector algorithms for stochastic optimization under gradual distribution shift. CoRR Subha Maity, Debarghya Mukherjee, Moulinath Banerjee, Yuekai Sun
2022	J	`jnl`	Understanding new tasks through the lens of training data via exponential tilting. CoRR Subha Maity, Mikhail Yurochkin, Moulinath Banerjee, Yuekai Sun
2021	A*	`conf`	Does enforcing fairness mitigate biases caused by subpopulation shift? NeurIPS Subha Maity, Debarghya Mukherjee, Mikhail Yurochkin, Yuekai Sun
2021	A*	`conf`	Individually Fair Gradient Boosting. ICLR Alexander Vargo, Fan Zhang, Mikhail Yurochkin, Yuekai Sun
2021	J	`jnl`	Individually Fair Gradient Boosting. CoRR Alexander Vargo, Fan Zhang, Mikhail Yurochkin, Yuekai Sun
2021	J	`jnl`	Individually Fair Ranking. CoRR Amanda Bower, Hamid Eftekhari, Mikhail Yurochkin, Yuekai Sun
2021	A*	`conf`	Individually Fair Rankings. ICLR Amanda Bower, Hamid Eftekhari, Mikhail Yurochkin, Yuekai Sun
2021	A*	`conf`	On sensitivity of meta-learning to support data. NeurIPS Mayank Agarwal, Mikhail Yurochkin, Yuekai Sun
2021	J	`jnl`	On sensitivity of meta-learning to support data. CoRR Mayank Agarwal, Mikhail Yurochkin, Yuekai Sun
2021	A*	`conf`	Outlier-Robust Optimal Transport. ICML Debarghya Mukherjee, Aritra Guha, Justin M. Solomon, Yuekai Sun, Mikhail Yurochkin
2021	A*	`conf`	Post-processing for Individual Fairness. NeurIPS Felix Petersen, Debarghya Mukherjee, Yuekai Sun, Mikhail Yurochkin
2021	J	`jnl`	Post-processing for Individual Fairness. CoRR Felix Petersen, Debarghya Mukherjee, Yuekai Sun, Mikhail Yurochkin
2021	A*	`conf`	SenSeI: Sensitive Set Invariance for Enforcing Individual Fairness. ICLR Mikhail Yurochkin, Yuekai Sun
2021	A*	`conf`	Statistical inference for individual fairness. ICLR Subha Maity, Songkai Xue, Mikhail Yurochkin, Yuekai Sun
2021	J	`jnl`	Statistical inference for individual fairness. CoRR Subha Maity, Songkai Xue, Mikhail Yurochkin, Yuekai Sun
2020	A	`conf`	Auditing ML Models for Individual Bias and Unfairness. AISTATS Songkai Xue, Mikhail Yurochkin, Yuekai Sun
2020	J	`jnl`	Auditing ML Models for Individual Bias and Unfairness. CoRR Songkai Xue, Mikhail Yurochkin, Yuekai Sun
2020	A*	`conf`	Federated Learning with Matched Averaging. ICLR Hongyi Wang, Mikhail Yurochkin, Yuekai Sun, Dimitris S. Papailiopoulos, Yasaman Khazaeni
2020	J	`jnl`	Federated Learning with Matched Averaging. CoRR Hongyi Wang, Mikhail Yurochkin, Yuekai Sun, Dimitris S. Papailiopoulos, Yasaman Khazaeni
2020	J	`jnl`	SenSeI: Sensitive Set Invariance for Enforcing Individual Fairness. CoRR Mikhail Yurochkin, Yuekai Sun
2020	J	`jnl`	There is no trade-off: enforcing fairness can improve accuracy. CoRR Subha Maity, Debarghya Mukherjee, Mikhail Yurochkin, Yuekai Sun
2020	A*	`conf`	Training individually fair ML models with sensitive subspace robustness. ICLR Mikhail Yurochkin, Amanda Bower, Yuekai Sun
2020	A*	`conf`	Two Simple Ways to Learn Individual Fairness Metrics from Data. ICML Debarghya Mukherjee, Mikhail Yurochkin, Moulinath Banerjee, Yuekai Sun
2020	J	`jnl`	Two Simple Ways to Learn Individual Fairness Metrics from Data. CoRR Debarghya Mukherjee, Mikhail Yurochkin, Moulinath Banerjee, Yuekai Sun
2020	J	`jnl`	Uniform Bounds for Invariant Subspace Perturbations. SIAM J. Matrix Anal. Appl. Anil Damle, Yuekai Sun
2019	A*	`conf`	Dirichlet Simplex Nest and Geometric Inference. ICML Mikhail Yurochkin, Aritra Guha, Yuekai Sun, XuanLong Nguyen
2019	J	`jnl`	Dirichlet Simplex Nest and Geometric Inference. CoRR Mikhail Yurochkin, Aritra Guha, Yuekai Sun, XuanLong Nguyen
2019	J	`jnl`	Learning fair predictors with Sensitive Subspace Robustness. CoRR Mikhail Yurochkin, Amanda Bower, Yuekai Sun
2019	A	`conf`	Precision Matrix Estimation with Noisy and Missing Data. AISTATS Roger Fan, Byoungwook Jang, Yuekai Sun, Shuheng Zhou
2019	J	`jnl`	Precision Matrix Estimation with Noisy and Missing Data. CoRR Roger Fan, Byoungwook Jang, Yuekai Sun, Shuheng Zhou
2018	J	`jnl`	Debiasing representations by removing unwanted variation due to protected attributes. CoRR Amanda Bower, Laura Niss, Yuekai Sun, Alexander Vargo
2017	J	`jnl`	A Geometric Approach to Archetypal Analysis and Nonnegative Matrix Factorization. Technometrics Anil Damle, Yuekai Sun
2017	J	`jnl`	An inexact subsampled proximal Newton-type method for large-scale machine learning. CoRR Xuanqing Liu, Cho-Jui Hsieh, Jason D. Lee, Yuekai Sun
2017	J	`jnl`	Communication-efficient Sparse Regression. J. Mach. Learn. Res. Jason D. Lee, Qiang Liu, Yuekai Sun, Jonathan E. Taylor
2017	J	`jnl`	On conditional parity as a notion of non-discrimination in machine learning. CoRR Yaacov Ritov, Yuekai Sun, Ruofei Zhao
2016	—	`conf`	Feature-distributed sparse regression: a screen-and-clean approach. NIPS Jiyan Yang, Michael W. Mahoney, Michael A. Saunders, Yuekai Sun
2015	J	`jnl`	Communication-efficient sparse regression: a one-shot approach. CoRR Jason D. Lee, Yuekai Sun, Qiang Liu, Jonathan E. Taylor
2015	—	`conf`	Evaluating the statistical significance of biclusters. NIPS Jason D. Lee, Yuekai Sun, Jonathan E. Taylor
2014	A*	`conf`	Learning Mixtures of Linear Classifiers. ICML Yuekai Sun, Stratis Ioannidis, Andrea Montanari
2014	J	`jnl`	Proximal Newton-Type Methods for Minimizing Composite Functions. SIAM J. Optim. Jason D. Lee, Yuekai Sun, Michael A. Saunders
2013	J	`jnl`	Learning Mixtures of Linear Classifiers. CoRR Yuekai Sun, Stratis Ioannidis, Andrea Montanari
2013	—	`conf`	On model selection consistency of penalized M-estimators: a geometric theory. NIPS Jason D. Lee, Yuekai Sun, Jonathan E. Taylor
2013	J	`jnl`	On model selection consistency of regularized M-estimators. CoRR Jason D. Lee, Yuekai Sun, Jonathan E. Taylor
2013	J	`jnl`	Robust flux balance analysis of multiscale biochemical reaction networks. BMC Bioinform. Yuekai Sun, Ronan M. T. Fleming, Ines Thiele, Michael A. Saunders
2012	J	`jnl`	Proximal Newton-type Methods for Minimizing Convex Objective Functions in Composite Form CoRR Jason D. Lee, Yuekai Sun, Michael A. Saunders
2012	—	`conf`	Proximal Newton-type methods for convex optimization. NIPS Jason D. Lee, Yuekai Sun, Michael A. Saunders