Mikhail Yurochkin




I am a Research Staff Member at IBM Research and MIT-IBM Watson AI Lab in Cambridge, Massachusetts. My research interests are

  • Algorithmic fairness
  • Model fusion and federated learning
  • Applications of optimal transport in machine learning
  • Bayesian (nonparametric) modeling and inference

Before joining IBM, I completed a PhD in Statistics at the University of Michigan, where I worked with Long Nguyen. I received my bachelor degree in applied mathematics and physics from Moscow Institute of Physics and Technology.

News

Publications


2021

On sensitivity of meta-learning to support data

Mayank Agarwal, Mikhail Yurochkin, Yuekai Sun
Neural Information Processing Systems (NeurIPS), 2021
arXiv

Post-processing for Individual Fairness

Felix Petersen, Debarghya Mukherjee, Yuekai Sun, Mikhail Yurochkin
Neural Information Processing Systems (NeurIPS), 2021
arXiv / Code / Video

Does enforcing fairness mitigate biases caused by subpopulation shift?

Subha Maity, Debarghya Mukherjee, Mikhail Yurochkin, Yuekai Sun
Neural Information Processing Systems (NeurIPS), 2021
arXiv

On Efficient Multilevel Clustering via Wasserstein Distances

Viet Huynh, Nhat Ho, Nhan Dam, XuanLong Nguyen, Mikhail Yurochkin, Hung Bui, Dinh Phung
Journal of Machine Learning Research (JMLR), 2021
PDF / Code

Outlier-Robust Optimal Transport

Debarghya Mukherjee, Aritra Guha, Justin Solomon, Yuekai Sun, Mikhail Yurochkin
International Conference on Machine Learning (ICML), 2021
arXiv / Code

SenSeI: Sensitive Set Invariance for Enforcing Individual Fairness

Mikhail Yurochkin and Yuekai Sun
International Conference on Learning Representations (ICLR), 2021 (Oral)
arXiv / Code (see supplementary material) / Video / Blog

Individually Fair Rankings

Amanda Bower, Hamid Eftekhari, Mikhail Yurochkin, Yuekai Sun
International Conference on Learning Representations (ICLR), 2021
arXiv / Code (see supplementary material) / Video

Statistical inference for individual fairness

Subha Maity, Songkai Xue, Mikhail Yurochkin, Yuekai Sun
International Conference on Learning Representations (ICLR), 2021
arXiv / Code (see supplementary material) / Video

Individually Fair Gradient Boosting

Alexander Vargo, Fan Zhang, Mikhail Yurochkin, Yuekai Sun
International Conference on Learning Representations (ICLR), 2021 (Spotlight)
arXiv / Code (see supplementary material) / Video


2020

Continuous Regularized Wasserstein Barycenters

Lingxiao Li, Aude Genevay, Mikhail Yurochkin, Justin Solomon
Neural Information Processing Systems (NeurIPS), 2020
arXiv / Code

Black Loans Matter: Distributionally Robust Fairness for Fighting Subgroup Discrimination

Mark Weber, Mikhail Yurochkin, Sherif Botros, Vanio Markov
NeurIPS Fair AI in Finance Workshop, 2020 (Spotlight Talk)
arXiv / Blog

Model Fusion with KullbackÔÇôLeibler Divergence

Sebastian Claici, Mikhail Yurochkin, Soumya Ghosh, Justin Solomon
International Conference on Machine Learning (ICML), 2020
arXiv / Code

Two Simple Ways to Learn Individual Fairness Metric from Data

Debarghya Mukherjee, Mikhail Yurochkin, Moulinath Banerjee, Yuekai Sun
International Conference on Machine Learning (ICML), 2020
arXiv / Code

Auditing ML models for individual bias and unfairness

Songkai Xue, Mikhail Yurochkin, Yuekai Sun
International Conference on Artificial Intelligence and Statistics (AISTATS), 2020
arXiv

Federated Learning with Matched Averaging

Hongyi Wang, Mikhail Yurochkin, Yuekai Sun, Dimitris Papailiopoulos, Yasaman Khazaeni
International Conference on Learning Representations (ICLR), 2020 (Oral)
arXiv / Code / Video / Blog

Training individually fair ML models with sensitive subspace robustness

Mikhail Yurochkin, Amanda Bower, Yuekai Sun
International Conference on Learning Representations (ICLR), 2020 (Spotlight)
arXiv / Code / Video / Blog


2019

Hierarchical Optimal Transport for Document Representation

Mikhail Yurochkin, Sebastian Claici, Edward Chien, Farzaneh Mirzazadeh, Justin Solomon
Neural Information Processing Systems (NeurIPS), 2019
arXiv / Code / Blog / MIT News

Alleviating Label Switching with Optimal Transport

Pierre Monteiller, Sebastian Claici, Edward Chien, Farzaneh Mirzazadeh, Justin Solomon, Mikhail Yurochkin
Neural Information Processing Systems (NeurIPS), 2019
arXiv / Code / Blog

Statistical Model Aggregation via Parameter Matching

Mikhail Yurochkin, Mayank Agarwal, Soumya Ghosh, Kristjan Greenewald, Trong Nghia Hoang
Neural Information Processing Systems (NeurIPS), 2019
arXiv / Code / Blog

Scalable inference of topic evolution via models for latent geometric structures

Mikhail Yurochkin, Zhiwei Fan, Aritra Guha, Paraschos Koutris, XuanLong Nguyen
Neural Information Processing Systems (NeurIPS), 2019
arXiv / Code / Blog

Dirichlet Simplex Nest and Geometric Inference

Mikhail Yurochkin, Aritra Guha, Yuekai Sun, XuanLong Nguyen
International Conference on Machine Learning (ICML), 2019 (Long Talk)
arXiv / Code / Video

Bayesian Nonparametric Federated Learning of Neural Networks

Mikhail Yurochkin, Mayank Agarwal, Soumya Ghosh, Kristjan Greenewald, Trong Nghia Hoang, Yasaman Khazaeni
International Conference on Machine Learning (ICML), 2019
arXiv / Code / Video

Online Semi-Supervised Learning with Bandit Feedback

Mikhail Yurochkin, Sohini Upadhyay, Djallel Bouneffouf, Mayank Agarwal, Yasaman Khazaeni
ICLR Limited Labeled Data (LLD) Workshop, 2019
PDF


2016-2018

Geometric Inference in Bayesian Hierarchical Models with Applications to Topic Modeling

Mikhail Yurochkin
PhD Thesis, University of Michigan, 2018
PDF / Slides

Conic Scan-and-Cover algorithms for nonparametric topic modeling

Mikhail Yurochkin, Aritra Guha, XuanLong Nguyen
Neural Information Processing Systems (NeurIPS), 2017
arXiv / Code

Multi-way Interacting Regression via Factorization Machines

Mikhail Yurochkin, XuanLong Nguyen, Nikolaos Vasiloglou
Neural Information Processing Systems (NeurIPS), 2017
arXiv / Code

Multilevel Clustering via Wasserstein Means

Nhat Ho, XuanLong Nguyen, Mikhail Yurochkin, Hung Hai Bui, Viet Huynh, Dinh Phung
International Conference on Machine Learning (ICML), 2017
arXiv / Code

Geometric Dirichlet Means algorithm for topic inference

Mikhail Yurochkin and XuanLong Nguyen
Neural Information Processing Systems (NeurIPS), 2016
arXiv / Code