SGB Meeting Agenda, March 21, 2004

March 21, 2004
8:30 am - 5:00 pm

8:30am- 9am
Contintental Breakfast
9:00 am-9:15 am
9:15am- 9:45am
2.0 ACM Update (White)
9:45 am- 10:15 am
10:15 am- 10:30 am
Break
10:30 am- 10:45 am
4.0 International Activities (Berenbaum)
10:45 am- 11:00 am
5.0 History Committee Report (Johnson)
11:00 am- 11:40 am
6.0 Conference Multimedia Activities
6.1 DVD production (Chesnais, R. Walker  20 min)
6.2 End System Multicast (Rexford, Zhang  20 min)
11:40 am- 12:00 noon
12:00 Noon- 1:00pm
Lunch
1:00 pm- 3:00 pm
8.0 SGB EC Recommendations
8.1 SIGs in Transition (R. Walker  25 min)
8.1.2 SIGGROUP
8.2 Chartering of New SIG (R. Walker  20 min)
8.4 Grant Task Force (R. Walker  25 min)
3:00pm- 3:15pm
Break
3: 15 pm- 3:40 pm
9.0 Election Models (Johnson)
3:40 pm- 4:40 pm
10.0 Best and Worst Practices Session (All)
10.1 Increased Conference Submissions (Gabow)
4:40 pm- 5:00 pm
11.0 Other Business
 

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. 

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