ML Anthology

Yurochkin, Mikhail

67 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
ICLRW 2025 CARROT: A Cost Aware Rate Optimal Router Seamus Somerstep, Felipe Maia Polo, Allysson Flavio Melo de Oliveira, Prattyush Mangal, Mírian Silva, Onkar Bhardwaj, Mikhail Yurochkin, Subha Maity
ICML 2025 Compress Then Serve: Serving Thousands of LoRA Adapters with Little Overhead Rickard Brüel Gabrielsson, Jiacheng Zhu, Onkar Bhardwaj, Leshem Choshen, Kristjan Greenewald, Mikhail Yurochkin, Justin Solomon
TMLR 2025 How Does Overparametrization Affect Performance on Minority Groups? Saptarshi Roy, Subha Maity, Songkai Xue, Mikhail Yurochkin, Yuekai Sun
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
ICLRW 2025 Out-of-Distribution Detection Using Synthetic Data Generation Momin Abbas, Muneeza Azmat, Raya Horesh, Mikhail Yurochkin
NeurIPS 2025 Revisiting Reinforcement Learning for LLM Reasoning from a Cross-Domain Perspective Zhoujun Cheng, Shibo Hao, Tianyang Liu, Fan Zhou, Yutao Xie, Feng Yao, Yuexin Bian, Nilabjo Dey, Yonghao Zhuang, Yuheng Zha, Yi Gu, Kun Zhou, Yuqi Wang, Yuan Li, Richard Fan, Jianshu She, Chengqian Gao, Abulhair Saparov, Taylor W. Killian, Haonan Li, Mikhail Yurochkin, Eric P. Xing, Zhengzhong Liu, Zhiting Hu
ICML 2025 SPRI: Aligning Large Language Models with Context-Situated Principles Hongli Zhan, Muneeza Azmat, Raya Horesh, Junyi Jessy Li, Mikhail Yurochkin
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
ICML 2025 Speculate, Then Collaborate: Fusing Knowledge of Language Models During Decoding Ziyao Wang, Muneeza Azmat, Ang Li, Raya Horesh, 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
ICML 2024 Asymmetry in Low-Rank Adapters of Foundation Models Jiacheng Zhu, Kristjan Greenewald, Kimia Nadjahi, Haitz Sáez De Ocáriz Borde, Rickard Brüel Gabrielsson, Leshem Choshen, Marzyeh Ghassemi, Mikhail Yurochkin, Justin Solomon
ICLRW 2024 Asymmetry in Low-Rank Adapters of Foundation Models Jiacheng Zhu, Kristjan Greenewald, Kimia Nadjahi, Haitz Sáez de Ocáriz Borde, Rickard Brüel Gabrielsson, Leshem Choshen, Marzyeh Ghassemi, Mikhail Yurochkin, Justin Solomon
ICMLW 2024 CharED: Character-Wise Ensemble Decoding for Large Language Models Kevin Gu, Eva Tuecke, Dmitriy A Katz, Raya Horesh, David Alvarez-Melis, Mikhail Yurochkin
ICMLW 2024 Compress Then Serve: Serving Thousands of LoRA Adapters with Little Overhead Rickard Brüel Gabrielsson, Jiacheng Zhu, Onkar Bhardwaj, Leshem Choshen, Kristjan Greenewald, Mikhail Yurochkin, Justin Solomon
NeurIPS 2024 Distributional Preference Alignment of LLMs via Optimal Transport Igor Melnyk, Youssef Mroueh, Brian Belgodere, Mattia Rigotti, Apoorva Nitsure, Mikhail Yurochkin, Kristjan Greenewald, Jiri Navratil, Jarret Ross
ICMLW 2024 Distributional Preference Alignment of LLMs via Optimal Transport Igor Melnyk, Youssef Mroueh, Brian Belgodere, Mattia Rigotti, Apoorva Nitsure, Mikhail Yurochkin, Kristjan Greenewald, Jiri Navratil, Jarret Ross
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
ICML 2024 Risk Aware Benchmarking of Large Language Models Apoorva Nitsure, Youssef Mroueh, Mattia Rigotti, Kristjan Greenewald, Brian Belgodere, Mikhail Yurochkin, Jiri Navratil, Igor Melnyk, Jarret Ross
ICLR 2024 Uncertainty Quantification via Stable Distribution Propagation Felix Petersen, Aashwin Ananda Mishra, Hilde Kuehne, Christian Borgelt, Oliver Deussen, Mikhail Yurochkin
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
TMLR 2023 $k$-Mixup Regularization for Deep Learning via Optimal Transport Kristjan Greenewald, Anming Gu, Mikhail Yurochkin, Justin Solomon, Edward Chien
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
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 Learning Proximal Operators to Discover Multiple Optima Lingxiao Li, Noam Aigerman, Vladimir Kim, Jiajin Li, Kristjan Greenewald, Mikhail Yurochkin, Justin Solomon
NeurIPSW 2023 Outlier-Robust Group Inference via Gradient Space Clustering Yuchen Zeng, Kristjan Greenewald, Luann Jung, Kangwook Lee, Justin Solomon, Mikhail Yurochkin
TMLR 2023 Rewiring with Positional Encodings for Graph Neural Networks Rickard Brüel Gabrielsson, Mikhail Yurochkin, Justin Solomon
NeurIPSW 2023 Risk Assessment and Statistical Significance in the Age of Foundation Models Apoorva Nitsure, Youssef Mroueh, Mattia Rigotti, Kristjan Greenewald, Brian Belgodere, Mikhail Yurochkin, Jiri Navratil, Igor Melnyk, Jarret Ross
ICLR 2023 Sampling with Mollified Interaction Energy Descent Lingxiao Li, Qiang Liu, Anna Korba, Mikhail Yurochkin, Justin Solomon
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
AISTATS 2022 Measuring the Robustness of Gaussian Processes to Kernel Choice William T. Stephenson, Soumya Ghosh, Tin D. Nguyen, Mikhail Yurochkin, Sameer Deshpande, Tamara Broderick
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
ICML 2022 Log-Euclidean Signatures for Intrinsic Distances Between Unaligned Datasets Tal Shnitzer, Mikhail Yurochkin, Kristjan Greenewald, Justin M Solomon
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
JMLR 2021 On Efficient Multilevel Clustering via Wasserstein Distances Viet Huynh, Nhat Ho, Nhan Dam, XuanLong Nguyen, Mikhail Yurochkin, Hung Bui, Dinh Phung
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
NeurIPS 2020 Continuous Regularized Wasserstein Barycenters Lingxiao Li, Aude Genevay, Mikhail Yurochkin, Justin M Solomon
ICLR 2020 Federated Learning with Matched Averaging Hongyi Wang, Mikhail Yurochkin, Yuekai Sun, Dimitris Papailiopoulos, Yasaman Khazaeni
ICML 2020 Model Fusion with Kullback-Leibler Divergence Sebastian Claici, Mikhail Yurochkin, Soumya Ghosh, Justin Solomon
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
NeurIPS 2019 Alleviating Label Switching with Optimal Transport Pierre Monteiller, Sebastian Claici, Edward Chien, Farzaneh Mirzazadeh, Justin M Solomon, Mikhail Yurochkin
ICML 2019 Bayesian Nonparametric Federated Learning of Neural Networks Mikhail Yurochkin, Mayank Agarwal, Soumya Ghosh, Kristjan Greenewald, Nghia Hoang, Yasaman Khazaeni
ICML 2019 Dirichlet Simplex Nest and Geometric Inference Mikhail Yurochkin, Aritra Guha, Yuekai Sun, Xuanlong Nguyen
NeurIPS 2019 Hierarchical Optimal Transport for Document Representation Mikhail Yurochkin, Sebastian Claici, Edward Chien, Farzaneh Mirzazadeh, Justin M Solomon
ICLRW 2019 Online Semi-Supervised Learning with Bandit Feedback Mikhail Yurochkin, Sohini Upadhyay, Djallel Bouneffouf, Mayank Agarwal, Yasaman Khazaeni
NeurIPS 2019 Scalable Inference of Topic Evolution via Models for Latent Geometric Structures Mikhail Yurochkin, Zhiwei Fan, Aritra Guha, Paraschos Koutris, Xuanlong Nguyen
NeurIPS 2019 Statistical Model Aggregation via Parameter Matching Mikhail Yurochkin, Mayank Agarwal, Soumya Ghosh, Kristjan Greenewald, Nghia Hoang
NeurIPS 2017 Conic Scan-and-Cover Algorithms for Nonparametric Topic Modeling Mikhail Yurochkin, Aritra Guha, Xuanlong Nguyen
NeurIPS 2017 Multi-Way Interacting Regression via Factorization Machines Mikhail Yurochkin, Xuanlong Nguyen, Nikolaos Vasiloglou
ICML 2017 Multilevel Clustering via Wasserstein Means Nhat Ho, XuanLong Nguyen, Mikhail Yurochkin, Hung Hai Bui, Viet Huynh, Dinh Phung
NeurIPS 2016 Geometric Dirichlet Means Algorithm for Topic Inference Mikhail Yurochkin, Xuanlong Nguyen