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GRASP Seminar: Guy Hacohen, Hebrew University, “Learning how neural networks learn: Which examples are important to neural networks, and when?”
July 28, 2022 @ 3:00 pm - 4:00 pm
*This was a HYBRID Event with in-person attendance in Levine 512 and virtual attendance…
ABSTRACT
In this talk, I’ll present my Ph.D. research at Daphna Weinshall’s lab. Our research focus is on the learning dynamics of neural networks. In this talk, we’ll draw inspiration from human learning, discussing how to divide the learning process of neural networks into several qualitatively different stages. We’ll show that different types of examples are important in different learning stages, allowing the use of curriculum learning approaches. We’ll continue by discussing the resulting qualitative differences in active learning strategies for the high and low-budget regimes. We’ll conclude by analyzing the order in which neural networks learn new data points, finding vast similarities across different architectures and in several data domains.
Presenter
Guy Hacohen
My name is Guy Hacohen, and I’m a Ph.D. student at the Hebrew University in Prof. Daphna Weinshall’s lab. I did my BSc in computer and cognitive sciences at the Hebrew University. I continued to do my MSc and Ph.D. at the Edmond and Lily Safra Center for Brain Sciences (ELSC) international graduate program, studying computation neuroscience and machine learning. My Ph.D. research is focused on the learning dynamics of deep neural networks and deals with the intersection of general deep learning, computer vision, and learning using only a few examples. Publication list: https://www.cs.huji.ac.il/w~