Michael R. Metel — accepted AI-conference papers

2025

Modified K-means Algorithm with Local Optimality Guarantees

Mingyi Li, Michael R. Metel, Akiko Takeda

ICML 2025poster

The K-means algorithm is one of the most widely studied clustering algorithms in machine learning. While extensive research has focused on its ability to achieve a globally optimal solution, there still lacks a rigorous analysis of its local optimality guarantees. In this paper, we first present con…

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2024

Draft on the Fly: Adaptive Self-Speculative Decoding using Cosine Similarity

Michael R. Metel, Peng Lu, Boxing Chen, Mehdi Rezagholizadeh, Ivan Kobyzev

EMNLP 2024finding

We present a simple on the fly method for faster inference of large language models. Unlike other (self-)speculative decoding techniques, our method does not require fine-tuning or black-box optimization to generate a fixed draft model, relying instead on simple rules to generate varying draft model…

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