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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


  • 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

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