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The Call For Papers for SysML'08, is now available. SysML'08 will be co-located with USENIX OSDI on December 11, 2008.
The Call For Papers for SysML'07, is now available. SysML'07 will be co-located with USENIX NSDI on April 10, 2007.
June 27, 2006
Saint-Malo, France
http://research.microsoft.com/workshops/sysml/
The full program, including papers and public reviews, is now available
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| Overview | ||||||||
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Recently, more and more computer systems researchers are borrowing machine learning techniques to attack problems in real-world computer systems, from reliability and performance issues in large-scale systems and networks to power efficiency in sensor networks and self-configuration in complicated systems. The motivation is simple: building empirical models based on statistical pattern recognition, data mining, probabilistic reasoning and other machine learning methods promises to help us cope with the challenges of scale and complexity of current and future systems. The goal of this workshop is to bring together researchers applying machine learning techniques to a wide-range of real-world computer systems and researchers making sure that measurements are robust and error free and that system performance models are sound. The objectives are cross-pollination, perspective on the hard problems and opportunities, as well as discussion of evaluation and validation methodologies. To this end, we would like to include the diverse spectrum of systems-related fields, including communication networks, computer architecture, databases, distributed systems, and operating systems. Regardless of the specific domain, applying machine learning techniques requires us to deal with many similar issues, from collecting training data and interpreting algorithm results to managing false positives and determining our confidence in inferences drawn from empirical models. We believe the lessons learned in the context of one system can give insights to applying machine learning to another.
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| Topics and submissions | ||||||||
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We invite authors to submit short position papers or reports of early work related to current and future applications of machine learning techniques to solving computer systems problems. Topics of interest include, but are not limited to:
We particularly encourage papers describing experience with real-world systems and lessons likely to be applicable across a variety of computer systems. Papers will be selected for presentation and/or publication in the workshop proceedings based on their originality, technical merit, topical relevance and their likelihood of generating discussion at the workshop. All accepted papers will be available online prior to the workshop and proceedings will be distributed at the workshop. The program committee will write short reviews (1-3 paragraphs) of accepted papers, giving the broader communities additional context and perspective.
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| Submission Instructions | ||||||||
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Submitted papers must be no longer than 5 two-column pages (10pt font, 1 inch margins), including all figures and references. The review process is not blind. Author names and affiliations should be included on the first page. The paper submission site is open for submissions. Papers should be submitted as PDF documents, viewable using standard tools (e.g., Adobe Acrobat). If you are submitting a file that is larger than 5mb or have questions about the submission process, please contact the co-chairs.
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| Important dates | ||||||||
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| Organizers | ||||||||
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Program Co-chairs
Program Committee
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