Summer School on Algorithmic and Theoretical Aspects of Machine Learning hosted by IIIT Bangalore

Co-sponsored by Microsoft Research India

Dates: 10 to 28 June

Venue: IIIT-Bangalore, 26-C, Hosur Road, Electronics City, Bangalore 560100

Course coordinators: Meenakshi D'Souza, G. Srinivasa Raghavan, Pradeesha Ashok, Srinivas Vivek

Brief description of school and list of topics:

The school will focus on algorithmic and theoretical aspects of machine learning. The lectures will also include the background material needed to understand the machine learning topics to be covered in the school. The following is a list of topics:

Algorithms (sorting, searching and graph algorithms)
Topics from probability theory and linear algebra as needed for machine learning
Introduction to machine learning, supervised and unsupervised learning
Finite state automata, decision trees and learning using finite state automata and decision trees
Algorithms for large data, clustering theory, theory of high dimensional problems
Optimization in machine learning
Computational learning theory
Machine learning on encrypted data and secure multi-party computation

Speakers:

G. Srinivasa Raghavan, IIIT Bangalore
Pradeesha Ashok, IIIT Bangalore
V. N. Muralidhara, IIIT Bangalore
Meenakshi D'Souza, IIIT Bangalore
Srinivas Vivek, IIIT Bangalore
Ashish Choudhury, IIIT Bangalore
Ajit Rajwade, IIT Mumbai
Ganesh Ramakrishnan, IIT Mumbai

Background/prior courses recommended:

Basics of Discrete Mathematics, Linear Algebra and Probability