ACM SGB Meeting Materials Agenda, March 8, 2010

SIG Governing Board
Monday, September 20, 2010
8:30 am – 4:00 pm
Location: Financial Ballrooms I & II
 
8:30 am – 9:00 am Continental Breakfast
9:00 am – 9:15 am
1.0 Welcome, Introductions (Wolf, Hanson)
9:15 am – 10:00 am
2.0 Report from the ACM CEO (White)
10:00 am – 10:15 am
3.0 Report from SGB Membership Task Force (Hanson) Slides
10:15 am – 10:45 am
4.0 Program Reviews
4.1 SIGACCESS - Program ReviewSlidesDL Revenue
4.2 SIGACT - Program ReviewSlidesDL Revenue
10:45 am – 11:00 am
Break
11:00 am – 11:30 am
4.3 SIGAda - Program ReviewSlidesDL Revenue
4.4 SIGCAS - Program ReviewSlidesDL Revenue
11:30 am – 12:00 pm 5.0 Publications Update (Davidson)
12:00 pm – 12:20 pm
6.0 Tech Pack (Terry)
12:20 pm – 1:20 pm Lunch
1:20 pm –   1:35 pm
7.0 History Committee Report (Hailpern) 
1:35 pm – 2:05 pm
Program Reviews Continued
4.5 SIGCSE - Program ReviewSlidesDL Revenue
4.6 SIGDA - Program ReviewSlidesDL Revenue
2:05 pm – 2:20 pm
8.0 SGB Administrative Report (Wolf)
8.1 Update on ACM EC and Council Activities
8.2 Lifetime Membership
8.3 SGB Election Update (Konstan)
2:20 pm – 2:35 pm
Break
2:35 pm – 3:05 pm
Program Reviews Continued
4.7 SIGDOC - Program ReviewSlidesDL Revenue
4.8 SIGGRAPH - Program ReviewSlidesDL Revenue
3:05 pm – 4:00 pm
9.0 SIG Proposal Report (Fisher)
9.1 Social Computing - Review Completed
9.2 Health Informatics - Under Review
9.3 Game - Under Review
9.4 Bioinformatics - Under Review

Prediction-Serving Systems

ACM Queue’s “Research for Practice” is your number one resource for keeping up with emerging developments in the world of theory and applying them to the challenges you face on a daily basis. In this installment, Dan Crankshaw and Joey Gonzalez provide an overview of machine learning server systems. What happens when we wish to actually deploy a machine learning model to production, and how do we serve predictions with high accuracy and high computational efficiency? Dan and Joey’s curated research selection presents cutting-edge techniques spanning database-level integration, video processing, and prediction middleware. Given the explosion of interest in machine learning and its increasing impact on seemingly every application vertical, it's possible that systems such as these will become as commonplace as relational databases are today. 

ACM Case Studies

Written by leading domain experts for software engineers, ACM Case Studies provide an in-depth look at how software teams overcome specific challenges by implementing new technologies, adopting new practices, or a combination of both. Often through first-hand accounts, these pieces explore what the challenges were, the tools and techniques that were used to combat them, and the solution that was achieved.

Why I Belong to ACM

Hear from Bryan Cantrill, vice president of engineering at Joyent, Ben Fried chief information officer at Google, and Theo Schlossnagle, OmniTI founder on why they are members of ACM.