Shvartsman, Michael

8 publications

NeurIPS 2025 AI Research Agents for Machine Learning: Search, Exploration, and Generalization in MLE-Bench Edan Toledo, Karen Hambardzumyan, Martin Josifoski, Rishi Hazra, Nicolas Baldwin, Alexis Audran-Reiss, Michael Kuchnik, Despoina Magka, Minqi Jiang, Alisia Maria Lupidi, Andrei Lupu, Roberta Raileanu, Tatiana Shavrina, Kelvin Niu, Jean-Christophe Gagnon-Audet, Michael Shvartsman, Shagun Sodhani, Alexander H Miller, Abhishek Charnalia, Derek Dunfield, Carole-Jean Wu, Pontus Stenetorp, Nicola Cancedda, Jakob Nicolaus Foerster, Yoram Bachrach

TMLR 2025 Scaling and Distilling Transformer Models for sEMG Nick Mehlman, Jean-Christophe Gagnon-Audet, Michael Shvartsman, Kelvin Niu, Alexander H Miller, Shagun Sodhani

NeurIPS 2025 The Automated LLM Speedrunning Benchmark: Reproducing NanoGPT Improvements Bingchen Zhao, Despoina Magka, Minqi Jiang, Xian Li, Roberta Raileanu, Tatiana Shavrina, Jean-Christophe Gagnon-Audet, Kelvin Niu, Shagun Sodhani, Michael Shvartsman, Andrei Lupu, Alisia Maria Lupidi, Karen Hambardzumyan, Martin Josifoski, Edan Toledo, Thomas Foster, Lucia Cipolina-Kun, Derek Dunfield, Abhishek Charnalia, Alexander H Miller, Oisin Mac Aodha, Jakob Nicolaus Foerster, Yoram Bachrach

UAI 2024 Response Time Improves Gaussian Process Models for Perception and Preferences Michael Shvartsman, Benjamin Letham, Eytan Bakshy, Stephen Keeley

AAAI 2023 A Semi-Parametric Model for Decision Making in High-Dimensional Sensory Discrimination Tasks Stephen Keeley, Benjamin Letham, Craig Sanders, Chase Tymms, Michael Shvartsman

AISTATS 2022 Look-Ahead Acquisition Functions for Bernoulli Level Set Estimation Benjamin Letham, Phillip Guan, Chase Tymms, Eytan Bakshy, Michael Shvartsman

AISTATS 2018 Matrix-Normal Models for fMRI Analysis Michael Shvartsman, Narayanan Sundaram, Mikio Aoi, Adam Charles, Theodore L. Willke, Jonathan D. Cohen

NeurIPS 2015 A Theory of Decision Making Under Dynamic Context Michael Shvartsman, Vaibhav Srivastava, Jonathan D. Cohen