Stochastic Optimization Courses and Certifications

Simons Institute

The Importance of Better Models in Stochastic Optimization

Explore stochastic optimization models, focusing on robustness, stability, and asymptotic minimax theory. Learn about weak convexity, sharp growth problems, and practical experiments.

• YouTube
• 47 minutes
• On-Demand
• Free Online Course

Simons Institute

First-Order Stochastic Optimization

Explore first-order stochastic optimization techniques for machine learning, covering gradient descent, adaptive learning, and convergence rates in data science applications.

• YouTube
• 58 minutes
• On-Demand
• Free Online Course

Alan Turing Institute

Masterclass for Optimisation - Professor Coralia Cartis, University of Oxford

Explore advanced optimization techniques for large-scale problems with Professor Coralia Cartis. Learn about algorithm development, analysis, and implementation for various problem classes in numerical optimization.

• YouTube
• 1 hour 53 minutes
• On-Demand
• Free Online Course

Society for Industrial and Applied Mathematics

Stochastic Primal Dual Splitting Algorithms for Convex and Nonconvex Composite Optimization in Imaging

Explore stochastic primal dual splitting algorithms for convex and nonconvex composite optimization in imaging, focusing on SPDFP and SVRG-PDFP methods and their applications.

• YouTube
• 49 minutes
• On-Demand
• Free Online Course

IEEE Signal Processing Society

Distributed Stochastic Non-Convex Optimization - Optimal Regimes and Tradeoffs

Explore optimal regimes and tradeoffs in distributed stochastic non-convex optimization with Usman A. Khan. Gain insights into advanced data science concepts and their applications in signal processing.

• YouTube
• 1 hour 5 minutes
• On-Demand
• Free Online Course

Simons Institute

Hitting the High-Dimensional Notes - An ODE for SGD Learning Dynamics in High-Dimensions

Explore stochastic optimization algorithms in high dimensions, analyzing dynamics and performance of SGD and momentum methods using a framework inspired by random matrix theory.

• YouTube
• 56 minutes
• On-Demand
• Free Online Course

Mathematical understanding of uncertainty

Explore probability theory, universal principles, and Markov chains to understand and harness uncertainty in real-world applications, from statistics to deep learning algorithms.

• edX
• 12 weeks, 1-2 hours a week
• On-Demand
• Free Online Course (Audit)

IIT Guwahati;  NPTEL

Chemical Process Intensification

Explore advanced chemical process intensification techniques, focusing on sustainable development, optimization, and innovative reactor designs for enhanced efficiency in industrial applications.

• Swayam
• 12 weeks
• On-Demand
• Free Online Course

Simons Institute

Implicit Regularization I

Explore implicit regularization in deep learning, covering boosting, complexity control, optimization landscapes, and stochastic gradient descent for effective model training.

• YouTube
• 1 hour 17 minutes
• On-Demand
• Free Online Course

Paul Hand

Variational Autoencoders

Explore generative models, autoencoders, and variational techniques in deep learning. Learn about architecture, optimization, and practical applications of variational autoencoders.

• YouTube
• 43 minutes
• On-Demand
• Free Online Course

Alan Turing Institute

Optimisation - An Introduction: Professor Coralia Cartis, University of Oxford

Explore optimization techniques, from basic concepts to advanced methods, covering minimizers, derivatives, quadratic functions, and gradient methods for solving complex mathematical problems.

• YouTube
• 2 hours 31 minutes
• On-Demand
• Free Online Course

USENIX

DOTE - Rethinking Predictive WAN Traffic Engineering

Innovative approach to WAN traffic engineering using historical data and deep learning, outperforming existing methods in quality and runtime while nearly matching an omniscient oracle.

• YouTube
• 17 minutes
• On-Demand
• Conference Talk

IEEE

Approximation Algorithms for Stochastic Minimum Norm Combinatorial Optimization

Explore advanced techniques for solving stochastic minimum norm combinatorial optimization problems, focusing on approximation algorithms and their applications in complex decision-making scenarios.

• YouTube
• 22 minutes
• On-Demand
• Free Online Course

EuroPython Conference

Decision Science with Probabilistic Programming

Explore generative models and probabilistic programming for decision-making under uncertainty, integrating with robust optimization techniques to enhance business strategies.

• YouTube
• 54 minutes
• On-Demand
• Conference Talk

Alan Turing Institute

Variational Bayesian Approximation of Inverse Problems Using Sparse Precision Matrices

Explore Variational Bayes as an efficient alternative to MCMC for solving inverse problems in PDEs, using sparse precision matrices and stochastic optimization for improved computational tractability.

• YouTube
• 1 hour 4 minutes
• On-Demand
• Free Online Course