Hacking Classifiers – talk by Ran Gilad-Bachrach (TAU)

Ran Gilad-Bachrach from Tel-Aviv University.

Location: Gonda building (901), room 101.

Time: Sunday 10/11 12:00.

Hacking Classifiers

Abstract:

In this talk will explore ways to stretch classifiers and use them in ways they were not intended to be used. In the first part of the talk we will break the training process of classifiers into its components: (i) selecting a prior (ii) creating a posterior (iii) selecting a candidate classifier. We will focus on the third step and make a case for the use of deep classifiers*. We will show generalization bounds and other properties of such classifiers as well as algorithms to find them. In the second part of the talk we will use classifiers to solve unsupervised learning problems. The problem we are interested at is finding sub-types of diseases from unlabeled data. We will see how this problem can be solved by training a tree model where each node in the tree is a classifier and each leaf is a sub-type of the disease (also known as a cluster).

About the speaker:

Ran Gilad-Bachrach’s research focuses on machine learning and its applications to health and well-being. Prof. Gilad-Bachrach recently joined the faculty of the Bio-Medical Engineering department in Tel-Aviv University. Prior to that he was a principal researcher in Microsoft Research and led a machine learning research team in Intel Research. He did his Ph.D. studies at the Hebrew University of Jerusalem under the supervision of Prof. Naftali Tishby.