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Interested in big data, machine learning, or computer vision?


Then come hear Lorenzo Torresani, Associate Professor of Computer Science talk about his latest computer vision research this Friday!


February 12, 6-7 PM


Kemeny 108


PIZZA WILL BE SERVED.


Title:

Computer Vision with Big Weakly-Labeled Data


Abstract:
Most modern computer vision methods employ a strongly-supervised learning paradigm that requires training on massive collections of richly-labeled images. These rich labels are provided by either human annotators or auxiliary sensors. Unfortunately, the reliance on time-consuming human labeling or sensory data collection greatly limits the applicability of these methods to new settings or novel domains. I will discuss the idea of eliminating or reducing the need for rich labels by leveraging existing large repositories of weakly-labeled images, i.e., photos annotated only with class labels indicating which objects are present but not their location.

Lorenzo Torresani is an Associate Professor in the Computer Science Department at Dartmouth College. He received a Laurea Degree in Computer Science with summa cum laude honors from the University of Milan (Italy) in 1996, and an M.S. and a Ph.D. in Computer Science from Stanford University in 2001 and 2005, respectively. In the past, he has worked at several industrial research labs including Microsoft Research Cambridge, Like.com<http://like.com> and Digital Persona. His research interests are in computer vision and machine learning. He is the recipient of several awards, including a CVPR best paper prize, a National Science Foundation CAREER Award, and a Google Faculty Research Award.