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From Simplicity to Complexity: The Double Descent Effect in Modern Machine Learning

Offered By: Banach Center via YouTube

Tags

Machine Learning Courses Neural Networks Courses Complexity Theory Courses Overfitting Courses Bias-Variance Tradeoff Courses High-dimensional Statistics Courses

Course Description

Overview

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Explore the intriguing phenomenon of the double descent effect in modern machine learning through this comprehensive lecture by Yizhe Zhu from the University of Southern California. Delve into the transition from simplicity to complexity in machine learning models, gaining insights into how this effect impacts model performance and generalization. Discover the implications of this phenomenon for designing and optimizing machine learning algorithms, and understand its relevance in various applications across the field.

Syllabus

From simplicity to complexity: the double descent effect in modern machine learning


Taught by

Banach Center

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