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Description
Representation is a central issue in machine learning. Indeed, with
good representations even simple algorithms can work, but even the
most sophisticated machine learning algorithms will find it difficult
to make up for a poor representation. Ideally, we would like the data
representation itself to be the subject of learning, to avoid these
difficulties. I will discuss some the challenges in learning useful
representations and will give an overview of some of my work in
discovering representations for image and text data, using methods
from connectioninst deep learning to Bayesian nonparametrics.