goldszmidt moises nbhdzziyhtvlegmlhpcom first workshop tackling computer systems problems machine learning techniques sysml june 27 2006 saintmalo france colocated sigmetrics 2006 httpresearchmicrosoftomworkshopssysml overview recently computer systems researchers borrowing machine learning techniques attack problems realworld computer systems reliability performance issues largescale systems networks power efficiency sensor networks selfconfiguration complicated systems motivation simple building empirical models based statistical pattern recognition data mining probabilistic reasoning machine learning methods promises help us cope challenges scale complexity current future systems goal workshop bring together researchers applying machine learning techniques widerange realworld computer systems researchers making sure measurements robust error free system performance models sound objectives crosspollination perspective hard problems opportunities well discussion evaluation validation methodologies end would like include diverse spectrum systemsrelated fields including communication networks computer architecture databases distributed systems operating systems regardless specific domain applying machine learning techniques requires us deal many similar issues collecting training data interpreting algorithm results managing false positives determining confidence inferences drawn empirical models believe lessons learned context one system give insights applying machine learning another topics submissions invite authors submit short position papers reports early work related current future applications machine learning techniques solving computer systems problems topics interest include limited use machine learning techniques address reliability performance security manageability issues computer systems new applications machine learning techniques computer systems problems challenges scale applying machine learning large systems experience online data collection machine learning analysis integration machine learning techniques realworld systems processes particularly encourage papers describing experience realworld systems lessons likely applicable across variety computer systems papers selected presentation andor publication workshop proceedings based originality technical merit topical relevance likelihood generating discussion workshop accepted papers available online prior workshop proceedings distributed workshop program committee write short reviews 13 paragraphs accepted papers giving broader communities additional context perspective submission instructions submitted papers must longer 5 twocolumn pages 10pt font 1 inch margins including figures references review process blind author names affiliations included first page details submission process made available january important dates submissions due march 3 2006 notification acceptance april 14 2006 cameraready copy due may 1 2006 workshop june 27 2006 organizers program cochairs moises goldszmidt hp labs emre kiciman microsoft research program committee paul barford u wisconsin albert greenberg att labsresearch carlos guestrin cmu armando fox stanford michael jordan uc berkeley randy katz uc berkeley sam madden mit dina papagiannaki intel research cambridge john platt microsoft research emmett witchel ut austin wed 06 aug 2008 131316 0800 uai call papers workshop tackling systems problems machine learning techniques sysml