This award provides support to students and other young researchers for travel and accommodation to the Machine Learning Summer School 2011 to be held in Purdue University, June 13-24, 2011. World class speakers from academia and industry are delivering tutorial style lectures over a two week period, and these presentations are being recorded and made available over the Internet. The Summer School is suitable for participants with different backgrounds. Individuals without previous knowledge are able to learn more about the theory and practice of Machine Learning, while those wishing to broaden their expertise in this area find the advanced courses particularly useful. The participating students are able to network with international experts.
We conducted a very successful Machine Learning Summer School (MLSS) thanks to generous funding from NSF as well as our other sponsors including Yahoo!, Microsoft Research, PASCAL network of excellence, IBM, and the Computational Design and Innovation Lab at Purdue University.The school featured 9 long talks and 10 application talks spread over a two week period. The students were exposed to a variety of basic and advanced topics in machine learning, many of which are not covered in typical undergraduateand graduate level machine learning classes. In total 131 participants which included 2 faculty members, 1researcher, 3 postdoctoral fellows, 4 industrial participants, 12 undergraduate students, and 109 graduate students participated in the summer school. Out of the 131 participants 27 were international while104 were from the US. In terms of gender 32 out of the 131 participantswere female while the rest were male. There were 3 minority students and one student from a historically black college. The applicants submitted a short application form, a curriculum vitae, a one page research statement, and a letter of recommendation letter from their advisors. We received a total of 74 complete applications. A committee of organizers (PIs on this grant) scrutinized the applications and made funding decisions. The priority (given merit and need) was given to women (17), underrepresented minorities (3 plus 1 enrolled in a Historically Black College), and advanced undergraduate students with background in Machine Learning (7). 56 of the applicants were partially reimbursed participant costs thanks to generous support from NSF. A majority of the students, especially undergraduates, noted in an anonymous exit survey that they could not have attended the school without the generous travel funding that they received.