Section 6.4

Technical Session Outline

A. Technical Sessions


  • Invited Speakers
    1. Keynote
  • Paper Sessions
    1. Number of Tracks
    2. Number of Days
    3. Session Length
    4. Number of Papers
  • Tutorials
    1. Topics
    2. Mix
  • Panels
    1. Forum for Discussion
    2. Not as Rigorous
    3. Not as Goal Oriented
    4. Popular

B. Refereed Paper Selection

  1. Select Referees
    • At Least 3 Per Paper
    • Appropriate Technical Background
    • Survey to Collect Background Information
  2. Deadlines
    • 3 Weeks in Reviewers Hands
    • 2 Weeks to Follow Up
    • Acceptance/Rejection Letters
    • Allow Time for Camera Ready Artwork
  3. Papers
    • Create a Process to Track Papers
    • Create a Checklist Cover Page
    • Categorize Papers by Topic (Link to Referee Background)
    • Selection of Papers
      1. Committee Meeting
      2. Accept/Reject Letters to Authors

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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. 

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