Machine Learning Theory

Established: August 1, 2016

Theory plays an important role in improving existing algorithms and motivating new algorithms. In this project, we aim to give mathematical formulations, derive theoretical results, and design new algorithms to variants of machine learning problems. In the past several years, we have investigated or are investigating the following topics:

  1. Distributed machine learning algorithms
  2. Deep neural networks
  3. Game-theoretic machine learning
  4. Learning to rank