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1
Regularization in Reinforcement Learning: Equivalences and Novel Methods
Regularization in Reinforcement Learning: Equivalences and Novel Methods
Rathnam, Sarah V. | Harvard University | 2025
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2
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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3
Using Regularization to Evaluate Differential Item Functioning among Multiple Covariates: A Penalized Expectation-Maximization Algorithm via Coordinate Descent and Soft-Thresholding
Using Regularization to Evaluate Differential Item Functioning among Multiple Covariates: A Penalized Expectation-Maximization Algorithm via Coordinate Descent and Soft-Thresholding
Belzak, William C.M. | The University of North Carolina at Chapel Hill | 2021
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4
Regularized Regression When Boundary Values Are Possible
Regularized Regression When Boundary Values Are Possible
Li, Tianqi. | The University of North Carolina at Chapel Hill | 2025
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5
Statistical and Algorithmic Perspectives on Estimating Optimal Transport Maps
Statistical and Algorithmic Perspectives on Estimating Optimal Transport Maps
Pooladian, Aram-Alexandre. | New York University | 2025
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6
Neural Networks Models with Applications to Genetic Studies
Neural Networks Models with Applications to Genetic Studies
Zhang, Shan. | Michigan State University | 2021
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