James B. Simon

According to our database, James B. Simon authored at least 13 papers between 2021 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

More is Better in Modern Machine Learning: when Infinite Overparameterization is Optimal and Overfitting is Obligatory.

James B. Simon, Dhruva Karkada, Nikhil Ghosh, Mikhail Belkin

CoRR, 2023

A Spectral Condition for Feature Learning.

Greg Yang, James B. Simon, Jeremy Bernstein

CoRR, 2023

Les Houches Lectures on Deep Learning at Large & Infinite Width.

Yasaman Bahri, Boris Hanin, Antonin Brossollet, Vittorio Erba, Christian Keup, Rosalba Pacelli, James B. Simon

CoRR, 2023

An Agnostic View on the Cost of Overfitting in (Kernel) Ridge Regression.

Lijia Zhou, James B. Simon, Gal Vardi, Nathan Srebro

CoRR, 2023

Tune As You Scale: Hyperparameter Optimization For Compute Efficient Training.

Abraham J. Fetterman, Ellie Kitanidis, Joshua Albrecht, Zachary Polizzi, Bryden Fogelman, Maksis Knutins, Bartosz Wróblewski, James B. Simon, Kanjun Qiu

CoRR, 2023

On the Stepwise Nature of Self-Supervised Learning.

James B. Simon, Maksis Knutins, Ziyin Liu, Daniel Geisz, Abraham J. Fetterman, Joshua Albrecht

Proceedings of the International Conference on Machine Learning, 2023

2022

Avalon: A Benchmark for RL Generalization Using Procedurally Generated Worlds.

Joshua Albrecht, Abraham J. Fetterman, Bryden Fogelman, Ellie Kitanidis, Bartosz Wróblewski, Nicole Seo, Michael Rosenthal, Maksis Knutins, Zachary Polizzi, James B. Simon, Kanjun Qiu

CoRR, 2022

On Kernel Regression with Data-Dependent Kernels.

James B. Simon

CoRR, 2022

Benign, Tempered, or Catastrophic: A Taxonomy of Overfitting.

Neil Mallinar, James B. Simon, Amirhesam Abedsoltan, Parthe Pandit, Mikhail Belkin, Preetum Nakkiran

CoRR, 2022

Benign, Tempered, or Catastrophic: Toward a Refined Taxonomy of Overfitting.

Neil Mallinar, James B. Simon, Amirhesam Abedsoltan, Parthe Pandit, Misha Belkin, Preetum Nakkiran

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Reverse Engineering the Neural Tangent Kernel.

James Benjamin Simon, Sajant Anand, Michael Robert DeWeese

Proceedings of the International Conference on Machine Learning, 2022

SGD Can Converge to Local Maxima.

Ziyin Liu, Botao Li, James B. Simon, Masahito Ueda

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Neural Tangent Kernel Eigenvalues Accurately Predict Generalization.

James B. Simon, Madeline Dickens, Michael Robert DeWeese

CoRR, 2021