Speaker: Pierre Baldi (UC Irvine)

Title: Deep Learning: Theory, Algorithms, and Applications

Abstract:

Learning is essential for building intelligent systems, whether carbon-based or silicon-based ones.
Morever these systems do not solve complex task in a single step but rather go through multiple processing stages.
Hence the question of deep learning, how efficient learning can be implemented in deep architectures.
This fundamental question not only impinges on problems of memory and intelligence in the brain but it is also
at the forefront of current machine learning research. In the last year alone, new performance breakthroughs
were achieved by deep learning methods in applications areas ranging from computer vision, to speech recognition,
to natural language understanding, to bioinformatics. This talk will provide a brief overview of deep learning,
from its biological origins to some of the latest theoretical, algorithmic, and application results.