← Authors

Mikhail Yurochkin

49 papers · 2016–2025 · 7 conferences · across top CS/AI conferences

Achievements

🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🌍 Conference Polyglot (7) πŸƒ Academic Marathon (9) 🌈 Renaissance Researcher (5) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (15) 🐝 Cross-Pollinator (5) 🀝 Dynamic Duo (25) πŸ‘‘ Triple Crown πŸ† Keyword Champion (2) πŸ’Ž Century Club (49) ⚑ Prolific Year (5) πŸ”₯ Unstoppable (7) ❓ The Questioner πŸ“ˆ Trend Setter πŸ—ƒοΈ Keyword Collector (155)

Conferences

NIPS (16) ICLR (14) ICML (14) AISTATS (2) ACL (1) EMNLP (1) JMLR (1)

Top co-authors

Yuekai Sun (25) Kristjan Greenewald (8) Xuanlong Nguyen (7) Subha Maity (7) Felipe Maia Polo (6) Justin Solomon (5) Justin M Solomon (5) Mayank Agarwal (5) Debarghya Mukherjee (5) Leshem Choshen (5)

Keywords

optimal transport (7) algorithmic fairness (4) individual fairness (4) topic modeling (4) bayesian inference (3) wasserstein distance (3) wasserstein barycenter (3) large language model (3) probabilistic model (2) federated learning (2) posterior inference (2) hierarchical clustering (2) probability measure (2) domain generalization (2) bayesian nonparametrics (2) gaussian process (2) domain adaptation (2) variational inference (2) convex optimization (2) model evaluation (2)

Papers

LiveXiv - A Multi-Modal live benchmark based on Arxiv papers content ICLR 2025
A transfer learning framework for weak to strong generalization ICLR 2025
Compress then Serve: Serving Thousands of LoRA Adapters with Little Overhead ICML 2025
SPRI: Aligning Large Language Models with Context-Situated Principles ICML 2025
Speculate, then Collaborate: Fusing Knowledge of Language Models during Decoding ICML 2025
tinyBenchmarks: evaluating LLMs with fewer examples ICML 2024
Uncertainty Quantification via Stable Distribution Propagation ICLR 2024
Fusing Models with Complementary Expertise ICLR 2024
An Investigation of Representation and Allocation Harms in Contrastive Learning ICLR 2024
Efficient multi-prompt evaluation of LLMs NIPS 2024
Distributional Preference Alignment of LLMs via Optimal Transport NIPS 2024
Weak Supervision Performance Evaluation via Partial Identification NIPS 2024
Aligners: Decoupling LLMs and Alignment EMNLP 2024
Asymmetry in Low-Rank Adapters of Foundation Models ICML 2024
Risk Aware Benchmarking of Large Language Models ICML 2024
Simple Disentanglement of Style and Content in Visual Representations ICML 2023
Learning Proximal Operators to Discover Multiple Optima ICLR 2023
Understanding new tasks through the lens of training data via exponential tilting ICLR 2023
Sampling with Mollified Interaction Energy Descent ICLR 2023
Measuring the robustness of Gaussian processes to kernel choice AISTATS 2022
Calibrated Data-Dependent Constraints with Exact Satisfaction Guarantees NIPS 2022
Your fairness may vary: Pretrained language model fairness in toxic text classification ACL 2022
Log-Euclidean Signatures for Intrinsic Distances Between Unaligned Datasets ICML 2022
Domain Adaptation meets Individual Fairness. And they get along. NIPS 2022
On efficient multilevel Clustering via Wasserstein distances JMLR 2021
On sensitivity of meta-learning to support data NIPS 2021
Does enforcing fairness mitigate biases caused by subpopulation shift? NIPS 2021
Post-processing for Individual Fairness NIPS 2021
Individually Fair Rankings ICLR 2021
Statistical inference for individual fairness ICLR 2021
SenSeI: Sensitive Set Invariance for Enforcing Individual Fairness ICLR 2021
Individually Fair Gradient Boosting ICLR 2021
Outlier-Robust Optimal Transport ICML 2021
Training individually fair ML models with sensitive subspace robustness ICLR 2020
Model Fusion with Kullback-Leibler Divergence ICML 2020
Two Simple Ways to Learn Individual Fairness Metrics from Data ICML 2020
Auditing ML Models for Individual Bias and Unfairness AISTATS 2020
Continuous Regularized Wasserstein Barycenters NIPS 2020
Federated Learning with Matched Averaging ICLR 2020
Bayesian Nonparametric Federated Learning of Neural Networks ICML 2019
Dirichlet Simplex Nest and Geometric Inference ICML 2019
Hierarchical Optimal Transport for Document Representation NIPS 2019
Statistical Model Aggregation via Parameter Matching NIPS 2019
Alleviating Label Switching with Optimal Transport NIPS 2019
Scalable inference of topic evolution via models for latent geometric structures NIPS 2019
Multilevel Clustering via Wasserstein Means ICML 2017
Multi-way Interacting Regression via Factorization Machines NIPS 2017
Conic Scan-and-Cover algorithms for nonparametric topic modeling NIPS 2017
Geometric Dirichlet Means Algorithm for topic inference NIPS 2016