Restricted Research - Award List, Note/Discussion Page
Fiscal Year: 2023
1203 University of Houston (143091)
Principal Investigator: Yan,Feng
Total Amount of Contract, Award, or Gift (Annual before 2011): $ 505,950
Exceeds $250,000 (Is it flagged?): Yes
Start and End Dates: 10/1/22 - 6/30/26
Restricted Research: YES
Academic Discipline: Computer Science
Department, Center, School, or Institute: Computer Science
Title of Contract, Award, or Gift: CAREER: AUTOMATED AND EFFICIENT MACHINE LEARNING AS A SERVICE
Name of Granting or Contracting Agency/Entity:
National Science Foundation
CFDA Link: NSF
47.070
Program Title:
n/a
CFDA Linked: Computer and Information Science and Engineering
Note:
This project aims to utilize the unique features of MLaaS to design efficient, automated, and user-centric MLaaS systems. This approach will significantly reduce resource waste and shorten the model design cycles through a variety of novel optimization approaches and by eliminating candidate models that fail to meet model serving latency and target accuracy. To support complete MLaaS workflow, this project will also develop MLaaS model serving methodologies that can meet service level latency requirements with minimum resource consumption using intelligent autoscaling. SAMs 1.1.3
Discussion: No discussion notes