Tom Mitchell

Founders University Professor
Machine Learning Department
School of Computer Science
Carnegie Mellon University

Resume

 Tom.Mitchell@cmu.edu,  412 268 2611, GHC 8203
Assistant: Mary Stech, 412 268-6869

What is Machine Learning, and where is it headed?

Video interview (5 min)

• AI, automation, and the future of work
  • Implications of Machine Learning for the workforce, Science, December 2017.
  • Governments need better data to track AI impact on jobs, Nature, April 2017.
  • 2017 U.S. National Academy report on Information Technology and the Future of Work
  • What Can Machines Learn and What Does It Mean for Occupations and the Economy?, AEA Papers and Proceedings, 2018.
• Machine Learning from Verbal User Instruction, video lecture on enabling cell phone users to teach their phones what to do, Simons Institute, Berkeley, February 13, 2017.
• Never Ending Language Learning, video lecture on our computer that is learning to read the web, Brown Univ., Feb. 2014.
• Neural representations of language meaning, video lecture on how the human brain represents word meanings, Berkeley, March 2014.
• When Computers Read, reprise of presentation at the World Economic Forum, Davos, Switzerland, January 2012 (5 minutes).
• Mining Our Reality, the emerging trend toward mining personal data, in Science, December 2009.
• The Discipline of Machine Learning, my perspective on this research field, July 2006

Current Research

• Can we make everybody a programmer (by letting people teach computers instead of program)?
  • Watch a 2018 talk on Conversational Machine Learning
  • Instructable Intelligent Personal Agent In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2016
  
  
• Can computers learn to read the web?
  • See our never-ending language learning (NELL) research
  
  
• How does the human brain represent word meanings?
• machine learning to analyze human brain activity (fMRI)
  

Online courses:

• Machine Learning course (includes video lectures, online slides, 2011)
• Semisupervised learning (includes video lecture, online slides, 2006)

Textbook: Machine Learning

• Machine Learning, Tom Mitchell, McGraw Hill, 1997.
• New chapters (available for free download)

Publications

• Selected publications

Colleagues

• Current and former students and visiting researchers
  

Courses

• Machine Learning, 10-601, Fall 2012
• Machine Learning, 10-601, Fall 2011
• Machine Learning, 10-701, Spring 2011
• Advanced Statistical NLP: Read the Web , Fall 2009

Reference

• Journals providing free online access to high-quality publications:
  • Journal of Machine Learning Research
  • Journal of AI Research
  • Public Library of Science, PLoS One
• Website providing free online access to lectures on machine learning, computer science, and other fields