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Naoki Abe has been a Research Staff Member in the Data Analytics Research group since May 2001, and is engaged in research in Machine Learning, Data Mining, and their applications to problems in business analytics. Naoki obtained his B.S. and M.S. in computer science from MIT in 1984, and a Ph.D. in Computer and Information Sciences from the University of Pennsylvania in 1989. From 1984 to 1985, he worked as a researcher at IBM T.J. Watson Research Center. From 1989 to 1990, he was a post-doctoral researcher at U.C. Santa Cruz, where he conducted research in computational learning theory. During the 1990s, he was with NEC research laboratories in Japan, where he was engaged in research in machine learning and its applications to various areas, including data mining, e-commerce, natural language processing, and bioinformatics. During this period he was also involved with the MITI-sponsored Real World Computing project, and the MEXT-sponsored Discovery Science project. From 1998 to 2000, he was adjunct Associate Professor at the Tokyo Institute of Technology. Since joining IBM Research, Naoki has been engaged in research in the development of novel machine learning methods and their applications to problems in business analytics and optimization. His research activities range from cost-sensitive learning, sampling schemes (boosting and active learning), reinforcement learning and their applications to business intelligence. Naoki has served as program committee members of ICML, ALT and COLT, and is currently on the editorial board of the Journal of Machine Learning Research.
Optimizing Debt Collections Using Constrained Reinforcement Learning
as author at Industry / Government Sessions ,