Simon, James B.

1. A Spectral Condition for Feature Learning
   2023/10/26 by Greg Yang, James B. Simon, Yang, Greg +3 · 1 voice · 18 citations
   Computer Science · Engineering · #FOS: Computer and information sciences #Face and Expression Recognition #Machine Learning (cs.LG) #Neural Networks and Applications #Sparse and Compressive Sensing Techniques #cs.LG
2. Reverse Engineering the Neural Tangent Kernel
   2021/06/06 by Simon, James B., Anand, Sajant, DeWeese, Michael R. · 2 citations
   #FOS: Computer and information sciences #Machine Learning (cs.LG)
3. More is Better in Modern Machine Learning: when Infinite Overparameterization is Optimal and Overfitting is Obligatory
   2023/11/24 by James B. Simon, Simon, James B., Dhruva Karkada +5 · 3 citations
   Computer Science · #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Machine Learning and Data Classification
4. On the Stepwise Nature of Self-Supervised Learning
   2023/03/27 by James B. Simon, Maksis Knutins, Simon, James B. +9 · 2 citations
   Computer Science · Physics and Astronomy · #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Model Reduction and Neural Networks #Neural Networks and Applications
5. The Eigenlearning Framework: A Conservation Law Perspective on Kernel Regression and Wide Neural Networks
   2021/10/08 by Simon, James B., Dickens, Madeline, Karkada, Dhruva +1 · 1 citation
   #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
6. An Agnostic View on the Cost of Overfitting in (Kernel) Ridge Regression
   2023/06/22 by Zhou, Lijia, Simon, James B., Vardi, Gal +1 · 1 citation
   #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
7. Tune As You Scale: Hyperparameter Optimization For Compute Efficient Training
   2023/06/13 by Abraham J. Fetterman, Ellie Kitanidis, Fetterman, Abraham J. +15 · 1 citation
   Computer Science · Materials Science · #Machine Learning and Data Classification #Advanced Neural Network Applications #Machine Learning in Materials Science
8. Les Houches Lectures on Deep Learning at Large & Infinite Width
   2023/09/04 by Bahri, Yasaman, Hanin, Boris, Brossollet, Antonin +4 · 1 citation
   #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #FOS: Mathematics #FOS: Physical sciences #High Energy Physics - Theory (hep-th) #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Probability (math.PR)
9. Alternating Gradient Flows: A Theory of Feature Learning in Two-layer Neural Networks
   2025/06/06 by Kunin, Daniel, Marchetti, Giovanni Luca, Chen, Feng +5 · 2 citations
   #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
10. The Optimization Landscape of SGD Across the Feature Learning Strength
    2024/10/06 by Alexander Atanasov, Alexandru Meterez, Atanasov, Alexander +5 · 1 citation
    Computer Science · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification
11. Predicting kernel regression learning curves from only raw data statistics
    2025/10/16 by Karkada, Dhruva, Turnbull, Joseph, Liu, Yuxi +1 · 1 citation
    #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG)