Mikhail Yurochkin

Orcid: 0000-0003-0153-6811

According to our database1, Mikhail Yurochkin authored at least 71 papers between 2016 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
LiveXiv - A Multi-Modal Live Benchmark Based on Arxiv Papers Content.
CoRR, 2024

The Future of Open Human Feedback.
CoRR, 2024

CharED: Character-wise Ensemble Decoding for Large Language Models.
CoRR, 2024

Compress then Serve: Serving Thousands of LoRA Adapters with Little Overhead.
CoRR, 2024

Distributional Preference Alignment of LLMs via Optimal Transport.
CoRR, 2024

Efficient multi-prompt evaluation of LLMs.
CoRR, 2024

A statistical framework for weak-to-strong generalization.
CoRR, 2024

Prompt Exploration with Prompt Regression.
CoRR, 2024

Asymmetry in Low-Rank Adapters of Foundation Models.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

tinyBenchmarks: evaluating LLMs with fewer examples.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Risk Aware Benchmarking of Large Language Models.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Uncertainty Quantification via Stable Distribution Propagation.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

An Investigation of Representation and Allocation Harms in Contrastive Learning.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Fusing Models with Complementary Expertise.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Aligners: Decoupling LLMs and Alignment.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

2023
k-Mixup Regularization for Deep Learning via Optimal Transport.
Trans. Mach. Learn. Res., 2023

Rewiring with Positional Encodings for Graph Neural Networks.
Trans. Mach. Learn. Res., 2023

Estimating Fréchet bounds for validating programmatic weak supervision.
CoRR, 2023

Risk Assessment and Statistical Significance in the Age of Foundation Models.
CoRR, 2023

GeRA: Label-Efficient Geometrically Regularized Alignment.
CoRR, 2023

Large Language Model Routing with Benchmark Datasets.
CoRR, 2023

Simple Disentanglement of Style and Content in Visual Representations.
Proceedings of the International Conference on Machine Learning, 2023

Understanding new tasks through the lens of training data via exponential tilting.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Sampling with Mollified Interaction Energy Descent.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Learning Proximal Operators to Discover Multiple Optima.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Fairness Evaluation in Text Classification: Machine Learning Practitioner Perspectives of Individual and Group Fairness.
Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, 2023

2022
Outlier-Robust Group Inference via Gradient Space Clustering.
CoRR, 2022

How does overparametrization affect performance on minority groups?
CoRR, 2022

RMExplorer: A Visual Analytics Approach to Explore the Performance and the Fairness of Disease Risk Models on Population Subgroups.
Proceedings of the 2022 IEEE Visualization and Visual Analytics (VIS), 2022

Calibrated Data-Dependent Constraints with Exact Satisfaction Guarantees.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Domain Adaptation meets Individual Fairness. And they get along.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Log-Euclidean Signatures for Intrinsic Distances Between Unaligned Datasets.
Proceedings of the International Conference on Machine Learning, 2022

Fairness of Machine Learning in Search Engines.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

Measuring the robustness of Gaussian processes to kernel choice.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Your fairness may vary: Pretrained language model fairness in toxic text classification.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2022, 2022

Communication-Efficient Model Fusion.
Proceedings of the Federated Learning, 2022

Personalization in Federated Learning.
Proceedings of the Federated Learning, 2022

2021
On efficient multilevel Clustering via Wasserstein distances.
J. Mach. Learn. Res., 2021

Your fairness may vary: Group fairness of pretrained language models in toxic text classification.
CoRR, 2021

Measuring the sensitivity of Gaussian processes to kernel choice.
CoRR, 2021

Individually Fair Ranking.
CoRR, 2021

Post-processing for Individual Fairness.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Does enforcing fairness mitigate biases caused by subpopulation shift?
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

On sensitivity of meta-learning to support data.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Outlier-Robust Optimal Transport.
Proceedings of the 38th International Conference on Machine Learning, 2021

SenSeI: Sensitive Set Invariance for Enforcing Individual Fairness.
Proceedings of the 9th International Conference on Learning Representations, 2021

Individually Fair Gradient Boosting.
Proceedings of the 9th International Conference on Learning Representations, 2021

Statistical inference for individual fairness.
Proceedings of the 9th International Conference on Learning Representations, 2021

Individually Fair Rankings.
Proceedings of the 9th International Conference on Learning Representations, 2021

2020
Black Loans Matter: Distributionally Robust Fairness for Fighting Subgroup Discrimination.
CoRR, 2020

There is no trade-off: enforcing fairness can improve accuracy.
CoRR, 2020

Online Semi-Supervised Learning with Bandit Feedback.
CoRR, 2020

IBM Federated Learning: an Enterprise Framework White Paper V0.1.
CoRR, 2020

Continuous Regularized Wasserstein Barycenters.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Two Simple Ways to Learn Individual Fairness Metrics from Data.
Proceedings of the 37th International Conference on Machine Learning, 2020

Model Fusion with Kullback-Leibler Divergence.
Proceedings of the 37th International Conference on Machine Learning, 2020

Training individually fair ML models with sensitive subspace robustness.
Proceedings of the 8th International Conference on Learning Representations, 2020

Federated Learning with Matched Averaging.
Proceedings of the 8th International Conference on Learning Representations, 2020

Auditing ML Models for Individual Bias and Unfairness.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
Learning fair predictors with Sensitive Subspace Robustness.
CoRR, 2019

Scalable inference of topic evolution via models for latent geometric structures.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Hierarchical Optimal Transport for Document Representation.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Statistical Model Aggregation via Parameter Matching.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Alleviating Label Switching with Optimal Transport.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Dirichlet Simplex Nest and Geometric Inference.
Proceedings of the 36th International Conference on Machine Learning, 2019

Bayesian Nonparametric Federated Learning of Neural Networks.
Proceedings of the 36th International Conference on Machine Learning, 2019

2018
Streaming dynamic and distributed inference of latent geometric structures.
CoRR, 2018

2017
Multi-way Interacting Regression via Factorization Machines.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Conic Scan-and-Cover algorithms for nonparametric topic modeling.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Multilevel Clustering via Wasserstein Means.
Proceedings of the 34th International Conference on Machine Learning, 2017

2016
Geometric Dirichlet Means Algorithm for topic inference.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016


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