Lectures related to Optimality of Convergence Rates: Accelerated/Stochastic Gradient Descent

Covers modern neuroscience synthesis, biophysical modeling, and brain building blocks with practical applications.

Explores the LP-based Branch & Bound algorithm for finding optimal solutions.

Explores hardware and software optimization for system performance, emphasizing the importance of reducing delay per gate and improving architecture.

Covers classification using GMM and kNN, exploring boundaries, errors, and practical exercises.