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math.ST2025
Basic Inequalities for First-Order Optimization with Applications to Statistical Risk Analysis
Seunghoon Paik, Kangjie Zhou, Matus Telgarsky +1
In this work, we introduce for first-order iterative optimization algorithms, forming a simple yet versatile framework which connects implicit and exp…
cs.LG2025
Benefits of Early Stopping in Gradient Descent for Overparameterized Logistic Regression
Jingfeng Wu, Peter Bartlett, Matus Telgarsky +1
In overparameterized logistic regression, gradient descent (GD) iterates diverge in norm while converging in direction to the maximum -margin solution -- a phenomenon known…