ACM SGB Meeting Agenda, March 21, 2014

SIG Governing Board

Friday, March 21, 2014

8:30 am - 4:00 pm

Chicago, Hilton O'Hare

Room: International West & Center

WIRELESS ACCESS (case sensitive):

Network Name: Hilton Meeting Rms

Access Code: AFCOHARE

8:30 am - 9:00 am
Continental Breakfast
9:00 am - 9:05 am
1.0 Welcome, Introductions (Cerf, Altman, Madden)
9:05 am - 9:50 am
2.0 Report from the ACM CEO (White) Report
9:50 am - 10:10 am 3.0 ACM Europe (Gagliardi)
10:10 am - 10:25 am
10:25 am - 11:00 am 4.0 Report on ACM Books Program (Ozsu)
11:00 am - 11:25 am 5.0 Research Highlights CACM (Morrisett) Report
11:25 am - 11:45 am 6.0 ICPS Program (Perrott)
11:45 am - 12:00 pm 7.0 Publications Activities (Konstan)
12:00 pm - 12:45 pm  8.0 Viability Reviews Recommendations
8.1SIGACCESS SlidesViabilityReach
8.2 SIGACT SlidesViabilityReach
8.3 SIGAda SlidesViabilityReach 
1:15 pm - 2:00 pm Viability Reviews Continued
8.4 SIGCAS SlidesViabilityReach
8.5 SIGCSE SlidesViabilityReach
8.6 SIGDA SlidesViabilityReach
2:00 pm - 2:15 pm 9.0 SIGLOG Proposal to Charter (Shankar) ProposalBudgetSlides
2:15 pm - 2:45 pm 10.0 DL App Demo (Graves)
10.0.1 Android App                                      10.0.2 iPhone App
2:45 pm - 2:55 pm Break
2:55 pm - 3:10 pm 11.0 Webinar Programs (Tracz) Report
3:10 pm - 3:30 pm 12.0 SGB EC Administrative Reports                          
12.1 SGB EC Update (Altman) Report
12.1.1 Survey Results from the last SGB MeetingM
12.1.2 Retreat
12.1.3 CCS/NSA Issue
12.1.4 History Committee Report
12.2 SGB Elections (Hanson) Report
12.3 Full Inclusion Task Force Report (Harper) Slides
3:30 pm - 4:00 pm 13.0 Best Practices Relationship with Steering Committees (Van der Veer) Report

ACM Case Studies

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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.