Applied Machine Learning

MIT Media Lab


Welcome to the Applied Machine Learning reading group at the MIT Media Lab! The machine learning research ecosystem has been dominated by theoritical and incremental work. Yet, practical, real-world problems yearn for real-time, large-scale machine learning, often involving messy data. An ability to a) understand the distributions of your data before modeling, b) choosing the right algorithmic approaches for the right kind of data, and c) work with many practical constraints are very important for applying machine learning to real-world problems. We as a group discuss techniques & approaches with real-world applications in mind. We meet Wednesdays in E14-393 from 3-4pm. To get added to the mailing list, please send an email to this email address.

Organizers: Karthik Dinakar, Nicholas De Palma, Catherine Havasi

Past readings & talks:

DateTitle Speaker Speaker Info Required Reading(s)
July 11th, 2011 First meeting -none- -none-Leslie Valiant, A Theory of the Learnable. Communications of the ACM, 1984. Vol 27, No 11. pp. 1134-1142
July 20th, 2011 Applied Machine Learning at the Media Lab multiple MIT Media Lab -none-
August 3rd, 2011What Sociolinguistics and Machine Learning
Have to Say to
One Another
about Interaction Analysis (slides)
Professor Carolyn Rose Carnegie Mellon University 1. An analysis of perspectives in interactive settings,
2. Language use as a reflection of socialization in online communities
3. Modeling of Stylistic Variation in Social Media with Stretchy Patterns
September 28th, 2011 Introduction to supervised learning Karthik Dinakar MIT Media Lab 1. Supervised Learning (Chapter 2) - Alpaydin
2. Credibility - Evalauting what's being learned - Witten & Frank
September 29th, 2011Machine listening
and reading at scale (slides)
Brian Whitman EchoNest 1. Music Retrieval from Everything
2. The Million Song Dataset
3. Echoprint - An Open Music Identification Service
October 5th, 2011 Bayesian Decision Theory & Classification Karthik Dinakar MIT Media Lab -none-
October 21st, 2011Learning About Speech Recognition, Automatic and Otherwise! Janet Baker Harvard University -none-
October 26th, 2011 Markov Decision Processes (MDP) Nick DePalma MIT Media Lab -none-
March 16th, 2012 Adaptively Learning the Crowd Kernel Adam Kalai Microsoft Research Slides