Mikhail Yurochkin

125 papers A* 42A 3Journal 71Unranked 7

Year	Rank	Type	Title / Venue / Authors
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`	CARROT: A Cost Aware Rate Optimal Router. CoRR Seamus Somerstep, Felipe Maia Polo, Allysson Flavio Melo de Oliveira, Prattyush Mangal, Mírian Silva, Onkar Bhardwaj, Mikhail Yurochkin, Subha Maity
2025	A*	`conf`	Compress then Serve: Serving Thousands of LoRA Adapters with Little Overhead. ICML Rickard Brüel Gabrielsson, Jiacheng Zhu, Onkar Bhardwaj, Leshem Choshen, Kristjan H. Greenewald, Mikhail Yurochkin, Justin Solomon
2025	J	`jnl`	Granite Vision: a lightweight, open-source multimodal model for enterprise Intelligence. CoRR Leonid Karlinsky, Assaf Arbelle, Abraham Daniels, Ahmed Nassar, Amit Alfassi, Bo Wu, Eli Schwartz, Dhiraj Joshi, Jovana Kondic, Nimrod Shabtay, Pengyuan Li, Roei Herzig, Shafiq Abedin, Shaked Perek, Sivan Harary, Udi Barzelay, Adi Raz Goldfarb, Aude Oliva, Ben Wieles, Bishwaranjan Bhattacharjee, Brandon Huang, Christoph Auer, Dan Gutfreund, David Beymer, David Wood, Hilde Kuehne, Jacob A. Hansen, Joseph Shtok, Ken Wong, Luis Angel D. Bathen, Mayank Mishra, Maksym Lysak, Michele Dolfi, Mikhail Yurochkin, Nikolaos Livathinos, Nimrod Harel, Ophir Azulai, Oshri Naparstek, Rafael Teixeira de Lima, Rameswar Panda, Sivan Doveh, Shubham Gupta, Subhro Das, Syed Zawad, Yusik Kim, Zexue He, Alexander Brooks, Gabe Goodhart, Anita Govindjee, Derek Leist, Ibrahim Ibrahim, Aya Soffer, David D. Cox, Kate Soule, Luis A. Lastras, Nirmit Desai, Shila Ofek-Koifman, Sriram Raghavan, Tanveer F. Syeda-Mahmood, Peter W. J. Staar, Tal Drory, Rogério Feris
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`	K2-Think: A Parameter-Efficient Reasoning System. CoRR Zhoujun Cheng, Richard Fan, Shibo Hao, Taylor W. Killian, Haonan Li, Suqi Sun, Hector Ren, Alexander Moreno, Daqian Zhang, Tianjun Zhong, Yuxin Xiong, Yuanzhe Hu, Yutao Xie, Xudong Han, Yuqi Wang, Varad Pimpalkhute, Yonghao Zhuang, Aaryamonvikram Singh, Xuezhi Liang, Anze Xie, Jianshu She, Desai Fan, Chengqian Gao, Liqun Ma, Mikhail Yurochkin, John Maggs, Xuezhe Ma, Guowei He, Zhiting Hu, Zhengzhong Liu, Eric P. Xing
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	J	`jnl`	Out-of-Distribution Detection using Synthetic Data Generation. CoRR Momin Abbas, Muneeza Azmat, Raya Horesh, Mikhail Yurochkin
2025	J	`jnl`	Revisiting Reinforcement Learning for LLM Reasoning from A Cross-Domain Perspective. CoRR Zhoujun Cheng, Shibo Hao, Tianyang Liu, Fan Zhou, Yutao Xie, Feng Yao, Yuexin Bian, Yonghao Zhuang, Nilabjo Dey, Yuheng Zha, Yi Gu, Kun Zhou, Yuqi Wang, Yuan Li, Richard Fan, Jianshu She, Chengqian Gao, Abulhair Saparov, Haonan Li, Taylor W. Killian, Mikhail Yurochkin, Zhengzhong Liu, Eric P. Xing, Zhiting Hu
2025	A*	`conf`	SPRI: Aligning Large Language Models with Context-Situated Principles. ICML Hongli Zhan, Muneeza Azmat, Raya Horesh, Junyi Jessy Li, Mikhail Yurochkin
2025	J	`jnl`	SPRI: Aligning Large Language Models with Context-Situated Principles. CoRR Hongli Zhan, Muneeza Azmat, Raya Horesh, Junyi Jessy Li, Mikhail Yurochkin
2025	A*	`conf`	Speculate, then Collaborate: Fusing Knowledge of Language Models during Decoding. ICML Ziyao Wang, Muneeza Azmat, Ang Li, Raya Horesh, Mikhail Yurochkin
2025	J	`jnl`	Speculate, then Collaborate: Fusing Knowledge of Language Models during Decoding. CoRR Ziyao Wang, Muneeza Azmat, Ang Li, Raya Horesh, Mikhail Yurochkin
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`	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`	Asymmetry in Low-Rank Adapters of Foundation Models. ICML Jiacheng Zhu, Kristjan H. Greenewald, Kimia Nadjahi, Haitz Sáez de Ocáriz Borde, Rickard Brüel Gabrielsson, Leshem Choshen, Marzyeh Ghassemi, Mikhail Yurochkin, Justin Solomon
2024	J	`jnl`	Asymmetry in Low-Rank Adapters of Foundation Models. CoRR Jiacheng Zhu, Kristjan H. Greenewald, Kimia Nadjahi, Haitz Sáez de Ocáriz Borde, Rickard Brüel Gabrielsson, Leshem Choshen, Marzyeh Ghassemi, Mikhail Yurochkin, Justin Solomon
2024	J	`jnl`	CharED: Character-wise Ensemble Decoding for Large Language Models. CoRR Kevin Gu, Eva Tuecke, Dmitriy Katz, Raya Horesh, David Alvarez-Melis, Mikhail Yurochkin
2024	J	`jnl`	Compress then Serve: Serving Thousands of LoRA Adapters with Little Overhead. CoRR Rickard Brüel Gabrielsson, Jiacheng Zhu, Onkar Bhardwaj, Leshem Choshen, Kristjan H. Greenewald, Mikhail Yurochkin, Justin Solomon
2024	A*	`conf`	Distributional Preference Alignment of LLMs via Optimal Transport. NeurIPS Igor Melnyk, Youssef Mroueh, Brian Belgodere, Mattia Rigotti, Apoorva Nitsure, Mikhail Yurochkin, Kristjan H. Greenewald, Jirí Navrátil, Jarret Ross
2024	J	`jnl`	Distributional Preference Alignment of LLMs via Optimal Transport. CoRR Igor Melnyk, Youssef Mroueh, Brian Belgodere, Mattia Rigotti, Apoorva Nitsure, Mikhail Yurochkin, Kristjan H. Greenewald, Jirí Navrátil, Jerret Ross
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`	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`	Prompt Exploration with Prompt Regression. CoRR Michael Feffer, Ronald Xu, Yuekai Sun, Mikhail Yurochkin
2024	A*	`conf`	Risk Aware Benchmarking of Large Language Models. ICML Apoorva Nitsure, Youssef Mroueh, Mattia Rigotti, Kristjan H. Greenewald, Brian Belgodere, Mikhail Yurochkin, Jirí Navrátil, Igor Melnyk, Jarret Ross
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	J	`jnl`	The Future of Open Human Feedback. CoRR Shachar Don-Yehiya, Ben Burtenshaw, Ramón Fernandez Astudillo, Cailean Osborne, Mimansa Jaiswal, Tzu-Sheng Kuo, Wenting Zhao, Idan Shenfeld, Andi Peng, Mikhail Yurochkin, Atoosa Kasirzadeh, Yangsibo Huang, Tatsunori Hashimoto, Yacine Jernite, Daniel Vila-Suero, Omri Abend, Jennifer Ding, Sara Hooker, Hannah Rose Kirk, Leshem Choshen
2024	A*	`conf`	Uncertainty Quantification via Stable Distribution Propagation. ICLR Felix Petersen, Aashwin Ananda Mishra, Hilde Kuehne, Christian Borgelt, Oliver Deussen, Mikhail Yurochkin
2024	J	`jnl`	Uncertainty Quantification via Stable Distribution Propagation. CoRR Felix Petersen, Aashwin Ananda Mishra, Hilde Kuehne, Christian Borgelt, Oliver Deussen, 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	J	`jnl`	Estimating Fréchet bounds for validating programmatic weak supervision. CoRR Felipe Maia Polo, Mikhail Yurochkin, Moulinath Banerjee, Subha Maity, Yuekai Sun
2023	A*	`conf`	Fairness Evaluation in Text Classification: Machine Learning Practitioner Perspectives of Individual and Group Fairness. CHI Zahra Ashktorab, Benjamin Hoover, Mayank Agarwal, Casey Dugan, Werner Geyer, Hao Bang Yang, Mikhail Yurochkin
2023	J	`jnl`	Fairness Evaluation in Text Classification: Machine Learning Practitioner Perspectives of Individual and Group Fairness. CoRR Zahra Ashktorab, Benjamin Hoover, Mayank Agarwal, Casey Dugan, Werner Geyer, Hao Bang Yang, Mikhail Yurochkin
2023	J	`jnl`	Fusing Models with Complementary Expertise. CoRR Hongyi Wang, Felipe Maia Polo, Yuekai Sun, Souvik Kundu, Eric P. Xing, Mikhail Yurochkin
2023	J	`jnl`	GeRA: Label-Efficient Geometrically Regularized Alignment. CoRR Dustin Klebe, Tal Shnitzer, Mikhail Yurochkin, Leonid Karlinsky, Justin Solomon
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`	Learning Proximal Operators to Discover Multiple Optima. ICLR Lingxiao Li, Noam Aigerman, Vladimir G. Kim, Jiajin Li, Kristjan H. Greenewald, Mikhail Yurochkin, Justin Solomon
2023	J	`jnl`	Rewiring with Positional Encodings for Graph Neural Networks. Trans. Mach. Learn. Res. Rickard Brüel Gabrielsson, Mikhail Yurochkin, Justin Solomon
2023	J	`jnl`	Risk Assessment and Statistical Significance in the Age of Foundation Models. CoRR Apoorva Nitsure, Youssef Mroueh, Mattia Rigotti, Kristjan H. Greenewald, Brian Belgodere, Mikhail Yurochkin, Jirí Navrátil, Igor Melnyk, Jerret Ross
2023	A*	`conf`	Sampling with Mollified Interaction Energy Descent. ICLR Lingxiao Li, Qiang Liu, Anna Korba, Mikhail Yurochkin, Justin Solomon
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
2023	J	`jnl`	k-Mixup Regularization for Deep Learning via Optimal Transport. Trans. Mach. Learn. Res. Kristjan H. Greenewald, Anming Gu, Mikhail Yurochkin, Justin Solomon, Edward Chien
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	A	`conf`	Fairness of Machine Learning in Search Engines. CIKM Yi Fang, Hongfu Liu, Zhiqiang Tao, Mikhail Yurochkin
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`	Learning Proximal Operators to Discover Multiple Optima. CoRR Lingxiao Li, Noam Aigerman, Vladimir G. Kim, Jiajin Li, Kristjan H. Greenewald, Mikhail Yurochkin, Justin Solomon
2022	A*	`conf`	Log-Euclidean Signatures for Intrinsic Distances Between Unaligned Datasets. ICML Tal Shnitzer, Mikhail Yurochkin, Kristjan H. Greenewald, Justin M. Solomon
2022	J	`jnl`	Log-Euclidean Signatures for Intrinsic Distances Between Unaligned Datasets. CoRR Tal Shnitzer, Mikhail Yurochkin, Kristjan H. Greenewald, Justin Solomon
2022	A	`conf`	Measuring the robustness of Gaussian processes to kernel choice. AISTATS William T. Stephenson, Soumya Ghosh, Tin D. Nguyen, Mikhail Yurochkin, Sameer K. Deshpande, Tamara Broderick
2022	J	`jnl`	Outlier-Robust Group Inference via Gradient Space Clustering. CoRR Yuchen Zeng, Kristjan H. Greenewald, Kangwook Lee, Justin Solomon, Mikhail Yurochkin
2022	—	`ch.`	Personalization in Federated Learning. Federated Learning Mayank Agarwal, Mikhail Yurochkin, Yuekai Sun
2022	—	`conf`	RMExplorer: A Visual Analytics Approach to Explore the Performance and the Fairness of Disease Risk Models on Population Subgroups. IEEE VIS (Short Papers) Bum Chul Kwon, Uri Kartoun, Shaan Khurshid, Mikhail Yurochkin, Subha Maity, Deanna G. Brockman, Amit V. Khera, Patrick T. Ellinor, Steven A. Lubitz, Kenney Ng
2022	J	`jnl`	RMExplorer: A Visual Analytics Approach to Explore the Performance and the Fairness of Disease Risk Models on Population Subgroups. CoRR Bum Chul Kwon, Uri Kartoun, Shaan Khurshid, Mikhail Yurochkin, Subha Maity, Deanna G. Brockman, Amit V. Khera, Patrick T. Ellinor, Steven A. Lubitz, Kenney Ng
2022	J	`jnl`	Rewiring with Positional Encodings for Graph Neural Networks. CoRR Rickard Brüel Gabrielsson, Mikhail Yurochkin, Justin Solomon
2022	J	`jnl`	Sampling with Mollified Interaction Energy Descent. CoRR Lingxiao Li, Qiang Liu, Anna Korba, Mikhail Yurochkin, Justin Solomon
2022	J	`jnl`	Understanding new tasks through the lens of training data via exponential tilting. CoRR Subha Maity, Mikhail Yurochkin, Moulinath Banerjee, Yuekai Sun
2022	—	`conf`	Your fairness may vary: Pretrained language model fairness in toxic text classification. ACL (Findings) Ioana Baldini, Dennis Wei, Karthikeyan Natesan Ramamurthy, Moninder Singh, Mikhail Yurochkin
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	J	`jnl`	Measuring the sensitivity of Gaussian processes to kernel choice. CoRR William T. Stephenson, Soumya Ghosh, Tin D. Nguyen, Mikhail Yurochkin, Sameer K. Deshpande, Tamara Broderick
2021	J	`jnl`	On efficient multilevel Clustering via Wasserstein distances. J. Mach. Learn. Res. Viet Huynh, Nhat Ho, Nhan Dam, XuanLong Nguyen, Mikhail Yurochkin, Hung Bui, Dinh Q. Phung
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
2021	J	`jnl`	Your fairness may vary: Group fairness of pretrained language models in toxic text classification. CoRR Ioana Baldini, Dennis Wei, Karthikeyan Natesan Ramamurthy, Mikhail Yurochkin, Moninder Singh
2021	J	`jnl`	k-Mixup Regularization for Deep Learning via Optimal Transport. CoRR Kristjan H. Greenewald, Anming Gu, Mikhail Yurochkin, Justin Solomon, Edward Chien
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	J	`jnl`	Black Loans Matter: Distributionally Robust Fairness for Fighting Subgroup Discrimination. CoRR Mark Weber, Mikhail Yurochkin, Sherif Botros, Vanio Markov
2020	A*	`conf`	Continuous Regularized Wasserstein Barycenters. NeurIPS Lingxiao Li, Aude Genevay, Mikhail Yurochkin, Justin M. Solomon
2020	J	`jnl`	Continuous Regularized Wasserstein Barycenters. CoRR Lingxiao Li, Aude Genevay, Mikhail Yurochkin, Justin Solomon
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`	IBM Federated Learning: an Enterprise Framework White Paper V0.1. CoRR Heiko Ludwig, Nathalie Baracaldo, Gegi Thomas, Yi Zhou, Ali Anwar, Shashank Rajamoni, Yuya Jeremy Ong, Jayaram Radhakrishnan, Ashish Verma, Mathieu Sinn, Mark Purcell, Ambrish Rawat, Tran Ngoc Minh, Naoise Holohan, Supriyo Chakraborty, Shalisha Witherspoon, Dean Steuer, Laura Wynter, Hifaz Hassan, Sean Laguna, Mikhail Yurochkin, Mayank Agarwal, Ebube Chuba, Annie Abay
2020	A*	`conf`	Model Fusion with Kullback-Leibler Divergence. ICML Sebastian Claici, Mikhail Yurochkin, Soumya Ghosh, Justin Solomon
2020	J	`jnl`	Model Fusion with Kullback-Leibler Divergence. CoRR Sebastian Claici, Mikhail Yurochkin, Soumya Ghosh, Justin Solomon
2020	J	`jnl`	Online Semi-Supervised Learning with Bandit Feedback. CoRR Sohini Upadhyay, Mikhail Yurochkin, Mayank Agarwal, Yasaman Khazaeni, Djallel Bouneffouf
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
2019	A*	`conf`	Alleviating Label Switching with Optimal Transport. NeurIPS Pierre Monteiller, Sebastian Claici, Edward Chien, Farzaneh Mirzazadeh, Justin M. Solomon, Mikhail Yurochkin
2019	J	`jnl`	Alleviating Label Switching with Optimal Transport. CoRR Pierre Monteiller, Sebastian Claici, Edward Chien, Farzaneh Mirzazadeh, Justin Solomon, Mikhail Yurochkin
2019	A*	`conf`	Bayesian Nonparametric Federated Learning of Neural Networks. ICML Mikhail Yurochkin, Mayank Agarwal, Soumya Ghosh, Kristjan H. Greenewald, Trong Nghia Hoang, Yasaman Khazaeni
2019	J	`jnl`	Bayesian Nonparametric Federated Learning of Neural Networks. CoRR Mikhail Yurochkin, Mayank Agarwal, Soumya Ghosh, Kristjan H. Greenewald, Trong Nghia Hoang, Yasaman Khazaeni
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	A*	`conf`	Hierarchical Optimal Transport for Document Representation. NeurIPS Mikhail Yurochkin, Sebastian Claici, Edward Chien, Farzaneh Mirzazadeh, Justin M. Solomon
2019	J	`jnl`	Hierarchical Optimal Transport for Document Representation. CoRR Mikhail Yurochkin, Sebastian Claici, Edward Chien, Farzaneh Mirzazadeh, Justin Solomon
2019	J	`jnl`	Learning fair predictors with Sensitive Subspace Robustness. CoRR Mikhail Yurochkin, Amanda Bower, Yuekai Sun
2019	J	`jnl`	On Efficient Multilevel Clustering via Wasserstein Distances. CoRR Viet Huynh, Nhat Ho, Nhan Dam, XuanLong Nguyen, Mikhail Yurochkin, Hung Bui, Dinh Q. Phung
2019	A*	`conf`	Scalable inference of topic evolution via models for latent geometric structures. NeurIPS Mikhail Yurochkin, Zhiwei Fan, Aritra Guha, Paraschos Koutris, XuanLong Nguyen
2019	A*	`conf`	Statistical Model Aggregation via Parameter Matching. NeurIPS Mikhail Yurochkin, Mayank Agarwal, Soumya Ghosh, Kristjan H. Greenewald, Trong Nghia Hoang
2019	J	`jnl`	Statistical Model Aggregation via Parameter Matching. CoRR Mikhail Yurochkin, Mayank Agarwal, Soumya Ghosh, Kristjan H. Greenewald, Trong Nghia Hoang
2018	J	`jnl`	Streaming dynamic and distributed inference of latent geometric structures. CoRR Mikhail Yurochkin, Zhiwei Fan, Aritra Guha, Paraschos Koutris, XuanLong Nguyen
2017	—	`conf`	Conic Scan-and-Cover algorithms for nonparametric topic modeling. NIPS Mikhail Yurochkin, Aritra Guha, XuanLong Nguyen
2017	—	`conf`	Multi-way Interacting Regression via Factorization Machines. NIPS Mikhail Yurochkin, XuanLong Nguyen, Nikolaos Vasiloglou
2017	A*	`conf`	Multilevel Clustering via Wasserstein Means. ICML Nhat Ho, XuanLong Nguyen, Mikhail Yurochkin, Hung Hai Bui, Viet Huynh, Dinh Q. Phung
2016	—	`conf`	Geometric Dirichlet Means Algorithm for topic inference. NIPS Mikhail Yurochkin, XuanLong Nguyen