Skip to main content
Graph
Search
fr
|
en
Login
Search
All
Categories
Concepts
Courses
Lectures
MOOCs
People
Practice
Publications
Startups
Units
Show all results for
Home
Lecture
Controlled Stochastic Processes
Graph Chatbot
Related lectures (30)
Previous
Page 1 of 3
Next
Dynamic Programming: Optimal Control
Explores Dynamic Programming for optimal control, focusing on stability, stationary policy, and recursive solutions.
Diffusion Models
Explores diffusion models, focusing on generating samples from a distribution and the importance of denoising in the process.
Introduction to Reinforcement Learning: Key Concepts and Applications
Introduces reinforcement learning, covering its definitions, applications, and theoretical foundations, while outlining the course structure and objectives.
Markov Decision Processes: Foundations of Reinforcement Learning
Covers Markov Decision Processes, their structure, and their role in reinforcement learning.
Optimal Transport: Kantorovich Duality
Covers optimal transport and Kantorovich duality in real-life distribution problems.
Approximation Algorithms
Covers approximation algorithms for optimization problems, LP relaxation, and randomized rounding techniques.
Controlled Stochastic Processes
Explores controlled stochastic processes, dynamic programming, and the Machine Replacement Problem.
Generalization Error
Explores generalization error in machine learning, focusing on data distribution and hypothesis impact.
Set Cover: Integrality Gap
Explores the integrality gap concept in set cover and multiplicative weights algorithms.
Optimization Methods: Theory Discussion
Explores optimization methods, including unconstrained problems, linear programming, and heuristic approaches.