YoVDO

Differentially Quantized Gradient Methods

Offered By: Simons Institute via YouTube

Tags

Machine Learning Courses Information Theory Courses Trustworthy Machine Learning Courses

Course Description

Overview

Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only!
Explore a 34-minute lecture by Victoria Kostina from the California Institute of Technology, presented at the Simons Institute, focusing on Differentially Quantized Gradient Methods. Delve into information-theoretic approaches for developing trustworthy machine learning systems, gaining insights into advanced techniques for optimizing gradient-based algorithms through quantization methods.

Syllabus

Differentially Quantized Gradient Methods


Taught by

Simons Institute

Related Courses

Introduction to Artificial Intelligence
Stanford University via Udacity
Natural Language Processing
Columbia University via Coursera
Probabilistic Graphical Models 1: Representation
Stanford University via Coursera
Computer Vision: The Fundamentals
University of California, Berkeley via Coursera
Learning from Data (Introductory Machine Learning course)
California Institute of Technology via Independent