Helmholtz Information & Data Science Academy Lectures
The HIDA Lectures is an event series organized by HIDA together with the six Helmholtz Information & Data Science Schools. Throughout the year, the Data Science Schools invite outstanding international Data Scientists to speak about their ongoing research.
As the Schools represent all Helmholtz research areas - Energy; Earth and Environment; Health; Information; Matter; and Aeronautics, Space and Transport - the series will reflect a wide range of topics and offers a great opportunity to dive into the diversity of current approaches in Data Science.
We cordially invite the interested public and especially PhD students in the Helmholtz Association, who can gain insight into the diverse activities of the Schools and HIDA but most importantly discuss with international researchers about different application fields of Data Science.
All lectures of the series are public.
The host of this HIDA Lecture is the Helmholtz Einstein International Berlin Research School in Data Science HEIBRiDS.
HIDA Lectures @ HEIBRiDS
SafePredict and Friends
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.
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.
