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1
An Investigation of Stochastic Gradient Descent Dynamics of Neural Networks
An Investigation of Stochastic Gradient Descent Dynamics of Neural Networks
Luo, Victor. | The University of Wisconsin - Madison | 2021
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2
Learned Surrogates and Stochastic Gradients for Accelerating Numerical Modeling, Simulation, and Design
Learned Surrogates and Stochastic Gradients for Accelerating Numerical Modeling, Simulation, and Design
Beatson, Alex. | Princeton University | 2021
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3
Odors as ''Natural Language'': Sparse Neural Networks in Mammalian Olfactory Systems and Large Language Models
Odors as ''Natural Language'': Sparse Neural Networks in Mammalian Olfactory Systems and Large Language Models
Liu, Bo. | Harvard University | 2025
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4
Efficient Algorithms for Modern Machine Learning Optimization
Efficient Algorithms for Modern Machine Learning Optimization
Ding, Lisang. | University of California, Los Angeles | 2025
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5
Distributed Multi-Agent Learning Under Federated and Competitive Settings
Distributed Multi-Agent Learning Under Federated and Competitive Settings
Qin, Tiancheng. | University of Illinois at Urbana-Champaign | 2024
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6
Long-Time Dynamics of Differential Equations in Physics and AI
Long-Time Dynamics of Differential Equations in Physics and AI
Jin, Kexin. | Princeton University | 2025
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7
Learning From Optimal Actions: Theory and Empirical Analysis in Digital Platforms
Learning From Optimal Actions: Theory and Empirical Analysis in Digital Platforms
Resende Fonseca, Yuri. | Columbia University | 2024
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8
Algorithm Dynamics in Modern Statistical Learning: Asymptotics, Universality, and Implicit Regularization
Algorithm Dynamics in Modern Statistical Learning: Asymptotics, Universality, and Implicit Regularization
Wang, Tianhao. | Yale University | 2024
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9
Stochastic Optimization Methods for Modern Machine Learning Problems
Stochastic Optimization Methods for Modern Machine Learning Problems
Sun, Yuejiao. | University of California, Los Angeles | 2021
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