Date: Wednesday, 9 August 2006, 6:30 PM
Location: SAP LABS, Building D, 3410 Hillview Avenue,
Palo Alto, CA (Google
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Cost: Free and open to all who wish to attend, but membership is
only $10/year.
Topic
As systems and distributed applications grow in complexity and scale, management of such systems becomes more difficult and sometimes infeasible for human operators. Recent research activity has shown encouraging results for performance debugging and failure diagnosis and detection in systems by using machine learning approaches, leveraging the vast amount of data collected on distributed systems. In this talk I'll describe some of the recent work and experience at HP-Labs in which machine learning and probabilistic modeling are used to aid in the area of system and application performance diagnosis. I'll also discuss the challenges and opportunities that this domain poses for machine learning and data mining researchers.
About the Speaker
Ira Cohen is a senior researcher at Hewlett Packard research labs, where he works on applying machine learning and pattern recognition techniques to system diagnosis, management and control. Ira joined HP-Labs in 2003 after receiving his PhD in Electrical and Computer Engineering from the University of Illinois at Urbana-Champaign where he worked on semi-supervised learning and computer vision applications. Ira holds a BSc. From Ben Gurion University, Israel. His research interests are in machine learning, probabilistic models, systems management and control, computer vision and human computer interaction. For more information on his research see http://www.hpl.hp.com/personal/Ira_Cohen/index.html.
See also:
http://www.hpl.hp.com/research/slic/publications.html
PowerPoint Presentation: http://www.hpl.hp.com/research/slic/SLIC_ACMBAPresentation2006.ppt