Speaker: Dennis Shasha, Courant Institute of New York University
SafePredict is a meta-algorithm for machine learning applications that strategically refuses to accept the predictions of an underlying machine learning algorithm or algorithms. The goal is to achieve a user-specified correctness rate on the non-refused predictions without refusing too much. We show applications to an on-line learning setting in which the data-to-class mapping is not independent and identically distributed (not iid). In a related work, we look at classification problems where we are willing to guess, on average, k classes in the hope that one is correct. We compare such an approach in which we always choose the top k most likely classes.
Short Bio
Dennis Shasha is a Julius Silver Professor of computer science at the Courant Institute of New York University and an Associate Director of NYU Wireless. He has written technical books about database tuning, biological pattern recognition, time series, DNA computing, resampling statistics, causal inference in molecular networks, and automated verification of concurrent search structures. He has also written books of puzzles about a mathematical detective named Dr. Ecco, a biography about great computer scientists, and a book about the future of computing.