Lectures related to Optimizing Loss Functions: Gradient Descent Variants

Faster and Projected Gradient Descent: Optimization Techniques

Discusses advanced optimization techniques, focusing on faster and projected gradient descent methods in machine learning.

Stochastic Gradient Descent

Explores stochastic gradient descent optimization and the Mean-Field Method in neural networks.

Optimality of Convergence Rate: Acceleration in Gradient Descent

Explores the optimality of convergence rate in gradient descent and acceleration techniques for convex and non-convex problems.

Gradient Descent Methods: Theory and Computation

Explores gradient descent methods for smooth convex and non-convex problems, covering iterative strategies, convergence rates, and challenges in optimization.