Optimization Algorithms Courses and Certifications

Foundations of Optimization Algorithms

Master optimization algorithms from Newton's Method to adaptive learning rates, covering gradient descent, momentum techniques, and Adagrad for effective machine learning model tuning.

• CodeSignal
• On-Demand
• Free Certificate

Artificial Intelligence: Optimization Algorithms in Python

256 ratings at Udemy

Learn how to build optimization algorithms from the ground up!

• Udemy
• 6 hours 46 minutes
• On-Demand
• Paid Course

The Grey Wolf Optimizer

253 ratings at Udemy

Learn Inspirations, Theories, Mathematical Models, and Practical Applications of the Grey Wolf Optimizer

• Udemy
• 3 hours 13 minutes
• On-Demand
• Paid Course

Yannic Kilcher

Descending Through a Crowded Valley - Benchmarking Deep Learning Optimizers

Comprehensive analysis of popular deep learning optimizers, comparing performance across tasks and providing evidence-based recommendations for algorithm selection and parameter tuning.

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

Yannic Kilcher

Training More Effective Learned Optimizers, and Using Them to Train Themselves - Paper Explained

Explores a novel approach to machine learning optimization using neural networks, discussing its architecture, training process, and potential to revolutionize model training through self-improvement and generalization.

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

Alfredo Canziani

Optimisation

Explore optimization techniques for neural networks, including gradient descent, SGD, momentum, adaptive methods, and normalization layers, with real-world applications in MRI technology.

• YouTube
• 1 hour 29 minutes
• On-Demand
• Free Video

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

Alan Turing Institute

Delayed Column Generation in Large Scale Integer Optimization Problems

Explore delayed column generation for solving large-scale mixed integer programming problems, focusing on applications in data science and decision mathematics.

• YouTube
• 2 hours 41 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