Workshop on Algorithmic Challenges in Machine Learning

January 7-9, 2015
University of California, San Diego

With the ubiquity of big data, there has been a rise in interest in machine learning and data-based applications. This workshop aims to bring together theoretical computer scientists interested in machine learning with theoretically-inclined machine learning researchers to discuss challenges and opportunities at the intersection of these two fields. The workshop will cover a variety of topics such as spectral learning, online learning, bandits, sparsity, and unsupervised methods. Talks will consist of both survey talks and more specialized technical talks. We will also have allocated time for collaboration and informal discussions.

Schedule         Talk abstracts

Venue: Atkinson hall, Calit2
Parking: Hopkins parking structure ($8/day)
See map for details

Confirmed speakers include:


We have discounted rates with the following hotels:


Registration is free. Please register in advance, so that we can arrange accordingly. Lunch will be provided for registered participants.

For further details, please contact Kamalika Chaudhuri or Shachar Lovett.