Events
The Taub Faculty of Computer Science Events and Talks
Tuesday, 13.11.2018, 14:30
The emergence of very effective deep learning techniques in recent years has affected
almost all areas of research remotely related to AI, and computer vision in particular
has been changed irreversibly. In this talk I will focus on visual object recognitions.
The incredible recent progress in this area, and the availability of very effective
public domain tools for object recognition in images, allows us to reopen old questions
and approach them from new directions with new tools. I will talk about two such
questions.
Specifically, in the first part of the lecture I will talk about curriculum learning,
where a learner is exposed to examples whose difficulty level is gradually increased.
This heuristic has been empirically shown to improve the outcome of learning in various
models. Our main contribution is a theoretical result, showing that learning with a
curriculum speeds up the rate of learning in the context of the regression and the
hinge loss. Interestingly, we also show how curriculum learning and hard-sample mining,
although conflicting at first sight, can coexist harmoniously within the same
theoretical model. In the second part of the lecture I will talk about a new generative
deep learning model, which we call GM-GAN. I will show how this model can be used for
novelty detection, and also augment data in a semi-supervised setting when the labeled
sample is small. I will conclude by showing how GM-GAN can be used for unsupervised
clustering.
Short Bio:
Daphna Weinshall received the BSc degree in mathematics and computer science from
Tel-Aviv University, Tel-Aviv Israel, in 1982. She received the MSc and PhD degrees in
mathematics and statistics from Tel-Aviv University in 1985 and 1986, respectively,
working on models of evolution and population genetics. Between 1987 and 1992, she
visited the center for biological information processing at MIT and the IBM T.J. Watson
Research Center. In 1993, she joined the Institute of Computer Science at the Hebrew
University of Jerusalem, where she is now a full professor. Her research interests
include computer and biological vision, as well as machine and human learning. Her
recent interests include the learning of distance functions, object class recognition,
cognitive passwords, and Virtual Reality in schizophrenia research.