Optimization Algorithms Courses and Certifications

Hausdorff Center for Mathematics

Mixed Integer Optimization in High Dimensions

Explore advanced techniques for solving high-dimensional mixed integer optimization problems, focusing on cutting-edge algorithms and theoretical foundations.

• YouTube
• 1 hour 4 minutes
• On-Demand
• Free Video

Hausdorff Center for Mathematics

LP-Norm Multiway Cut

Explores graph partitioning with lp-norm multiway cut, unifying min-sum and min-max variants. Discusses hardness, integrality gap, and approximation algorithm for this generalized problem.

• YouTube
• 31 minutes
• On-Demand
• Free Video

Society for Industrial and Applied Mathematics

Inexact Accelerated High-order Proximal-point Methods in Convex Programming

New framework for accelerated methods in convex programming using approximations of high-order proximal points. Presents second-order method with O(k^(-4)) convergence rate, surpassing traditional complexity limits.

• YouTube
• 55 minutes
• On-Demand
• Free Video

IEEE

Towards a Theory of Non-Commutative Optimization - Geodesic First and Second Order Methods for Moment Maps

Explore geodesic methods for non-commutative optimization, focusing on moment maps and their applications in mathematical theory and algorithms.

• YouTube
• 23 minutes
• On-Demand
• Free Video

GERAD Research Center

Global Convergence and Asymptotic Optimality of the Heavy Ball Method

Explore global convergence and asymptotic optimality of the heavy ball method, challenging complexity lower bounds for strongly convex functions with Lipschitz gradients.

• YouTube
• 48 minutes
• On-Demand
• Free Video

GERAD Research Center

Multi-Precision Optimization Algorithm: Decreasing Computational Cost and Controlling Computational Error

Explore multi-precision optimization algorithms to reduce computational costs and control errors in smooth, non-convex function minimization, with applications in deep neural network training.

• YouTube
• 56 minutes
• On-Demand
• Free Video

Institute for Mathematical Sciences

Swarm-Based Gradient Descent Method for Non-Convex Optimization

Explore innovative swarm-based gradient descent techniques for solving non-convex optimization problems, presented by Prof. Eitan Tadmor from the University of Maryland.

• YouTube
• 47 minutes
• On-Demand
• Free Video

Erwin Schrödinger International Institute for Mathematics and Physics (ESI)

Strong Convergence of Inertial Algorithms via Tikhonov Regularization

Explore inertial algorithms with Tikhonov regularization for optimization problems, examining strong convergence to minimum norm solutions and fast convergence rates for objective function values.

• YouTube
• 24 minutes
• On-Demand
• Free Video

Erwin Schrödinger International Institute for Mathematics and Physics (ESI)

A New Derivative-Free Method Using an Improved Under-Determined Quadratic Interpolation Model

Explore a novel derivative-free optimization method using improved under-determined quadratic interpolation, considering trust-region iteration properties and model optimality.

• YouTube
• 23 minutes
• On-Demand
• Free Video

Erwin Schrödinger International Institute for Mathematics and Physics (ESI)

Computer-Aided Lyapunov Analyses and Counter-Examples to the Convergence of First-Order Optimization Methods

Explore computer-aided Lyapunov analyses and counter-examples for first-order optimization methods, focusing on constructive approaches and structural properties.

• YouTube
• 33 minutes
• On-Demand
• Free Video

GERAD Research Center

Learn to Compare Nodes in Branch and Bound

Explore node selection strategies in Branch and Bound, focusing on data-based methods and graph neural networks for efficient problem-solving in NP-hard optimization.

• YouTube
• 24 minutes
• On-Demand
• Free Video

Yacine Mahdid

AdamW Optimizer from Scratch in Python

Discover how to implement the state-of-the-art AdamW optimizer from scratch, understanding its unique weight decay regularization that outperforms traditional Adam + L2.

• YouTube
• 20 minutes
• On-Demand
• Free Video

NPTEL-NOC IITM

Convergence Analysis of a Descent Algorithm - Part 2

Explore convergence analysis of descent algorithms, including condition number concepts and MATLAB implementation for optimization problems.

• YouTube
• 20 minutes
• On-Demand
• Free Video

NPTEL-NOC IITM

Unconstrained Optimization - Identifying a Local Minima - 1st and 2nd Order Conditions - Part 2

Explore the necessary and sufficient conditions for identifying local minima in unconstrained optimization, including Taylor's theorem, first-order conditions, and descent direction algorithms.

• YouTube
• 16 minutes
• On-Demand
• Free Video

NPTEL-NOC IITM

BFGS Method

Explore the BFGS method, a powerful optimization algorithm used in numerical analysis and machine learning applications.

• YouTube
• 16 minutes
• On-Demand
• Free Video