YoVDO

Learning-Augmented Online Optimization

Offered By: Institute for Pure & Applied Mathematics (IPAM) via YouTube

Tags

Machine Learning Courses Artificial Intelligence Courses Data Science Courses Algorithm Design Courses Computational Learning Theory Courses

Course Description

Overview

Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only!
Explore a 49-minute conference talk on learning-augmented online optimization presented by Ravi Kumar from Google Inc. at IPAM's EnCORE Workshop on Computational vs Statistical Gaps in Learning and Optimization. Recorded on February 26, 2024, at the Institute for Pure & Applied Mathematics (IPAM) at UCLA, this presentation delves into the intersection of machine learning and online optimization techniques. Gain insights into how learning algorithms can enhance traditional online optimization methods, potentially leading to more efficient and adaptive problem-solving approaches in various computational domains. Discover the latest research and developments in this field as Kumar shares his expertise on bridging the gap between computational and statistical aspects of learning and optimization.

Syllabus

Ravi Kumar - Learning-Augmented Online Optimization - IPAM at UCLA


Taught by

Institute for Pure & Applied Mathematics (IPAM)

Related Courses

Data Analysis
Johns Hopkins University via Coursera
Computing for Data Analysis
Johns Hopkins University via Coursera
Scientific Computing
University of Washington via Coursera
Introduction to Data Science
University of Washington via Coursera
Web Intelligence and Big Data
Indian Institute of Technology Delhi via Coursera