Lecture: David Waltz

SCHOOL OF INFORMATICS DISTINGUISHED COLLOQUIUM

Friday, April 24, 2009
3:00 p.m.
Lindley Hall 102

David Waltz, Columbia University, will present, "Machine Learning and Pasteur’s Quadrant in CS: Research with Relevance as well as Rigor.”

Abstract:
CS research has traditionally been curiosity-driven, emphasizing rigor over relevance. Application-driven CS research, emphasizing engineering for specific tasks, carries far less academic prestige. In his 1997 book, Pasteur’s Quadrant: Basic Science and Technological Innovation, Donald Stokes argues that, contrary to usual assumptions, these two alternatives are not the ends of a spectrum -- characterized at one end by Edison (relevance without rigor) and Bohr (rigor without relevance) – but that relevance and rigor are in fact orthogonal dimensions. Using this insight he makes the case for research that is high in both these dimensions (Pasteur’s Quadrant). Much of the research in Machine Learning (ML) has in fact been from Pasteur’s Quadrant – e.g. algorithms for character recognition, recommender systems, web search, protein structure prediction, etc. This talk will present ML research from CCLS - Columbia's Center for Computational Learning Systems – that strives for both rigor and relevance in three main areas: 1) learning systems for predictive maintenance for the electric power grid, largely done in conjunction with Con Edison, 2) learning to translate natural language, with a concentration on translating to and from Arabic - standard as well as dialects, and 3) predicting epileptic seizures using implanted electrode arrays. This talk will use these examples -- along with others from CS -- to argue for exploring Pasteur’s Quadrant in CS. It will also discuss some of the special challenges such work entails. For example, challenging applications typically involve large amounts of data that require large - and less academically rewarding – efforts in data cleaning and systems engineering in addition to driving research on understanding, new algorithms and valuable applications.