UTCS Colloquia/AI - Alexander Smola, Google/CMU, "Learning at Scale," ACE 2.302

Contact Name: 
Inderjit Dhillon
ACES 2.302
Oct 18, 2012 11:00am - 12:00pm

Signup Schedule: http://apps.cs.utexas.edu/talkschedules/cgi/list_events.cgi

Type of Talk: Colloquium/AI

Speaker/Affiliation: Alexander Smola, Google/CMU

Talk Audience: UTCS Faculty and Grads

Date/Time: October 18, 2012, 11:00 AM - 12:00 PM

Location: ACE 2.302

Host:  Inderjit Dhillon

Talk Title: Learning at Scale

Video Recording: http://mediasite.aces.utexas.edu/UTMediasite/Catalog/Full/8253d475397742258c1a81a0af2a72c021#8253d475397742258c1a81a0af2a72c021/?state=kKAKHhqq9v8JFTGB6IH2&_suid=768

Talk Abstract: In this talk Alexander Smola will give an overview of a number of problems arising when learning at scale. After an overview of problems and systems used in large scale inference, he will discuss strategies for parameter distribution and how they can be used to perform inference in massive graphical models. Subsequently he will discuss methods for accelerating function evaluation. This addresses the issues of scalability both in terms of efficiency and problem size.

Speaker Bio: Alexander Smola studied physics in Munich at the University of Technology, Munich, at the Universita degli Studi di Pavia and at AT&T Research in Holmdel. During this time he was at the Maximilianeum München and the Collegio Ghislieri in Pavia. In 1996 he received the Master degree at the University of Technology, Munich and in 1998 the Doctoral Degree in computer science at the University of Technology Berlin. Until 1999 he was a researcher at the IDA Group of the GMD Institute for Software Engineering and Computer Architecture in Berlin (now part of the Fraunhofer Geselschaft). After that, he worked as a Researcher and Group Leader at the Research School for Information Sciences and Engineering of the Australian National University. From 2004 onwards he worked as a Senior Principal Researcher and Program Leader at the Statistical Machine Learning Program at NICTA.