Over the past years, there has been a growing interest in Unsupervised Learning methods, mainly due to the massive increase in the volume and types of data stored, as well as, in their use for Big Data Analytics. Since tagging such quantities of data infeasible, various methodologies have been developed to allow systems to exploit these large amounts of data and the information they provide in a non-supervised manner.
The second annual Unsupervised Machine Learning Seminar will be the satellite event for the 2016 Speech Processing Conference. The focus of the seminar will be theory and application of unsupervised learning mechanisms such as clustering and deep learning in various domains. The keynote lecture will be given by Dr. Christian Hennig who will speak about cluster validation - a major challenge in the field. The event will include several short lectures.
The seminar will be held immediately following and is included in the registration fee for the conference. Registration for the satellite event is also available as a separate fee.
See Registration fees & Guidelines >>
Program: Satellite Event - Unsupervised Machine Learning Seminar
| 16:30 - 16:45
- Dr. Itshak Lapidot, Satellite Event Chairman, Afeka
Dr. Christian Hennig
Department of Statistical Science,
University College London
“Cluster Validation: How to Think and What to Do?”
- "Sparse Signal Processing of Intracardiac Electrocardiograms"
Dr. Tom Trigano, Sami Shamoon College of Engineering
- "A perception – action cycle approach to understanding eye gazing distributions"
Ron M. Hecht, General Motors & The Hebrew University
- "Recursive inference of important sub-scenes in a user generated video"
Raanan Y. Yehezkel Rohekar, Intel
Interested in sponsoring this event?