Sampling-based Algorithms for Fast and Deployable AI

We present sampling-based algorithms with provable guarantees to alleviate the increasingly prohibitive costs of training and deploying modern AI systems. At the core of this thesis lies importance sampling, which we use to construct representative subsets of inputs and compress machine learning mod...

Full description

Bibliographic Details
Main Author: Baykal, Cenk
Other Authors: Rus, Daniela
Format: Thesis
Published: Massachusetts Institute of Technology 2022
Online Access:https://hdl.handle.net/1721.1/139924
https://orcid.org/0000-0002-6776-9493