James B. Simon
Publications by Year
Research Areas
Stochastic Gradient Optimization Techniques, Neural Networks and Applications, Advanced Neural Network Applications, Sparse and Compressive Sensing Techniques, Machine Learning and Data Classification
Most-Cited Works
- → Interleaved electro-optic dual comb generation to expand bandwidth and scan rate for molecular spectroscopy and dynamics studies near 1.6 µm(2021)12 cited
- → Design of unimodular sequences with real periodic correlation and complementary correlation(2016)7 cited
- → Fast noise-resistant control of donor nuclear spin qubits in silicon(2020)6 cited
- → More is Better in Modern Machine Learning: when Infinite Overparameterization is Optimal and Overfitting is Obligatory(2023)5 cited
- → The Eigenlearning Framework: A Conservation Law Perspective on Kernel Regression and Wide Neural Networks(2021)4 cited
- → Tune As You Scale: Hyperparameter Optimization For Compute Efficient Training(2023)4 cited
- → Les Houches lectures on deep learning at large and infinite width*(2024)3 cited
- → Benign, Tempered, or Catastrophic: A Taxonomy of Overfitting(2022)3 cited
- Neural Tangent Kernel Eigenvalues Accurately Predict Generalization(2021)
- → Avalon: A Benchmark for RL Generalization Using Procedurally Generated Worlds(2022)2 cited