The International Conference on Machine Learning (ICML) is considered to be the premier conference in Machine Learning, both from an educational and scientific standpoint. ICML encompasses topics on all facets of Machine Learning, and solicits papers on problem areas, research topics, learning paradigms, and approaches to evaluation. It is a key forum for exchange of ideas in the Machine Learning community, and features scientific poster sessions, educational tutorials, forward-looking workshops, and invited talks. This project offers awards to students to help defray their travel costs, promoting a broader societal reach for the conference. Promoting education and participation in cutting edge data science is central to the mission of the NSF, and this project and its awards speak directly to that mission.

ICML 2016 will be held in New York City. We have estimated itemized costs based on previous ICML conferences. Students funded via this project will be selected by a peer review process based on their financial needs, alignment of research areas, and participation in the conference. These awards will offer the opportunity to network with experts in the area and gain valuable insights into the cutting edge of Machine Learning research. This will positively impact the depth and breadth of their research as well as quality of their dissertations. Long-term career benefits should also result, as ICML has a number of industrial sponsors who set up booths and discuss Machine Learning-oriented job opportunities within their own companies. The ICML 2016 scholarship program follows the successful scholarship programs from the last several years. The requested funds will be used exclusively to help defray the travel and registration costs of students attending the conference. These student scholarships are very important for encouraging student participation in this premier conference and for shaping the future of the field as a whole.

Agency
National Science Foundation (NSF)
Institute
Division of Information and Intelligent Systems (IIS)
Type
Standard Grant (Standard)
Application #
1630365
Program Officer
Weng-keen Wong
Project Start
Project End
Budget Start
2016-06-01
Budget End
2017-05-31
Support Year
Fiscal Year
2016
Total Cost
$30,000
Indirect Cost
Name
Columbia University
Department
Type
DUNS #
City
New York
State
NY
Country
United States
Zip Code
10027