Mikhail Yurochkin
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
35
Venues
7
Active years
2017–2025
Best venue rank
A*
Where they publish
Papers
35 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | ICLR | 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 |
| 2025 | ICLR | A transfer learning framework for weak to strong generalization. | Seamus Somerstep, Felipe Maia Polo, Moulinath Banerjee, Yaacov Ritov, Mikhail Yurochkin, Yuekai Sun |
| 2025 | ICML | Compress then Serve: Serving Thousands of LoRA Adapters with Little Overhead. | Rickard Brel Gabrielsson, Jiacheng Zhu, Onkar Bhardwaj, Leshem Choshen, Kristjan H. Greenewald, Mikhail Yurochkin, Justin Solomon |
| 2025 | ICML | Speculate, then Collaborate: Fusing Knowledge of Language Models during Decoding. | Ziyao Wang, Muneeza Azmat, Ang Li, Raya Horesh, Mikhail Yurochkin |
| 2025 | ICML | SPRI: Aligning Large Language Models with Context-Situated Principles. | Hongli Zhan, Muneeza Azmat, Raya Horesh, Junyi Jessy Li, Mikhail Yurochkin |
| 2024 | EMNLP | Aligners: Decoupling LLMs and Alignment. | Lilian Ngweta, Mayank Agarwal, Subha Maity, Alex Gittens, Yuekai Sun, Mikhail Yurochkin |
| 2024 | ICLR | Fusing Models with Complementary Expertise. | Hongyi Wang, Felipe Maia Polo, Yuekai Sun, Souvik Kundu, Eric P. Xing, Mikhail Yurochkin |
| 2024 | ICLR | An Investigation of Representation and Allocation Harms in Contrastive Learning. | Subha Maity, Mayank Agarwal, Mikhail Yurochkin, Yuekai Sun |
| 2024 | ICLR | Aligners: Decoupling LLMs and Alignment. | Lilian Ngweta, Mayank Agarwal, Subha Maity, Alex Gittens, Yuekai Sun, Mikhail Yurochkin |
| 2024 | ICLR | Uncertainty Quantification via Stable Distribution Propagation. | Felix Petersen, Aashwin Ananda Mishra, Hilde Kuehne, Christian Borgelt, Oliver Deussen, Mikhail Yurochkin |
| 2024 | ICML | Risk Aware Benchmarking of Large Language Models. | Apoorva Nitsure, Youssef Mroueh, Mattia Rigotti, Kristjan H. Greenewald, Brian Belgodere, Mikhail Yurochkin, Jir Navrtil, Igor Melnyk, Jarret Ross |
| 2024 | ICML | tinyBenchmarks: evaluating LLMs with fewer examples. | Felipe Maia Polo, Lucas Weber, Leshem Choshen, Yuekai Sun, Gongjun Xu, Mikhail Yurochkin |
| 2024 | ICML | Asymmetry in Low-Rank Adapters of Foundation Models. | Jiacheng Zhu, Kristjan H. Greenewald, Kimia Nadjahi, Haitz Sez de Ocriz Borde, Rickard Brel Gabrielsson, Leshem Choshen, Marzyeh Ghassemi, Mikhail Yurochkin, Justin Solomon |
| 2023 | CHI | Fairness Evaluation in Text Classification: Machine Learning Practitioner Perspectives of Individual and Group Fairness. | Zahra Ashktorab, Benjamin Hoover, Mayank Agarwal, Casey Dugan, Werner Geyer, Hao Bang Yang, Mikhail Yurochkin |
| 2023 | ICLR | Learning Proximal Operators to Discover Multiple Optima. | Lingxiao Li, Noam Aigerman, Vladimir G. Kim, Jiajin Li, Kristjan H. Greenewald, Mikhail Yurochkin, Justin Solomon |
| 2023 | ICLR | Sampling with Mollified Interaction Energy Descent. | Lingxiao Li, Qiang Liu, Anna Korba, Mikhail Yurochkin, Justin Solomon |
| 2023 | ICLR | Understanding new tasks through the lens of training data via exponential tilting. | Subha Maity, Mikhail Yurochkin, Moulinath Banerjee, Yuekai Sun |
| 2023 | ICML | Simple Disentanglement of Style and Content in Visual Representations. | Lilian Ngweta, Subha Maity, Alex Gittens, Yuekai Sun, Mikhail Yurochkin |
| 2022 | ACL | Your fairness may vary: Pretrained language model fairness in toxic text classification. | Ioana Baldini, Dennis Wei, Karthikeyan Natesan Ramamurthy, Moninder Singh, Mikhail Yurochkin |
| 2022 | AISTATS | Measuring the robustness of Gaussian processes to kernel choice. | William T. Stephenson, Soumya Ghosh, Tin D. Nguyen, Mikhail Yurochkin, Sameer K. Deshpande, Tamara Broderick |
| 2022 | CIKM | Fairness of Machine Learning in Search Engines. | Yi Fang, Hongfu Liu, Zhiqiang Tao, Mikhail Yurochkin |
| 2022 | ICML | Log-Euclidean Signatures for Intrinsic Distances Between Unaligned Datasets. | Tal Shnitzer, Mikhail Yurochkin, Kristjan H. Greenewald, Justin M. Solomon |
| 2021 | ICLR | Individually Fair Rankings. | Amanda Bower, Hamid Eftekhari, Mikhail Yurochkin, Yuekai Sun |
| 2021 | ICLR | Statistical inference for individual fairness. | Subha Maity, Songkai Xue, Mikhail Yurochkin, Yuekai Sun |
| 2021 | ICLR | Individually Fair Gradient Boosting. | Alexander Vargo, Fan Zhang, Mikhail Yurochkin, Yuekai Sun |
| 2021 | ICLR | SenSeI: Sensitive Set Invariance for Enforcing Individual Fairness. | Mikhail Yurochkin, Yuekai Sun |
| 2021 | ICML | Outlier-Robust Optimal Transport. | Debarghya Mukherjee, Aritra Guha, Justin M. Solomon, Yuekai Sun, Mikhail Yurochkin |
| 2020 | AISTATS | Auditing ML Models for Individual Bias and Unfairness. | Songkai Xue, Mikhail Yurochkin, Yuekai Sun |
| 2020 | ICLR | Federated Learning with Matched Averaging. | Hongyi Wang, Mikhail Yurochkin, Yuekai Sun, Dimitris S. Papailiopoulos, Yasaman Khazaeni |
| 2020 | ICLR | Training individually fair ML models with sensitive subspace robustness. | Mikhail Yurochkin, Amanda Bower, Yuekai Sun |
| 2020 | ICML | Model Fusion with Kullback-Leibler Divergence. | Sebastian Claici, Mikhail Yurochkin, Soumya Ghosh, Justin Solomon |
| 2020 | ICML | Two Simple Ways to Learn Individual Fairness Metrics from Data. | Debarghya Mukherjee, Mikhail Yurochkin, Moulinath Banerjee, Yuekai Sun |
| 2019 | ICML | Bayesian Nonparametric Federated Learning of Neural Networks. | Mikhail Yurochkin, Mayank Agarwal, Soumya Ghosh, Kristjan H. Greenewald, Trong Nghia Hoang, Yasaman Khazaeni |
| 2019 | ICML | Dirichlet Simplex Nest and Geometric Inference. | Mikhail Yurochkin, Aritra Guha, Yuekai Sun, XuanLong Nguyen |
| 2017 | ICML | Multilevel Clustering via Wasserstein Means. | Nhat Ho, XuanLong Nguyen, Mikhail Yurochkin, Hung Hai Bui, Viet Huynh, Dinh Q. Phung |