자료유형  

 학위논문

Control Number  

0016932331

International Standard Book Number  

9798380380904

Dewey Decimal Classification Number  

004

Main Entry-Personal Name  

Sun, Yu.

Publication, Distribution, etc. (Imprint  

[S.l.] : University of California, Berkeley., 2023

Publication, Distribution, etc. (Imprint  

Ann Arbor : ProQuest Dissertations & Theses, 2023

Physical Description  

1 online resource(78 p.)

General Note  

Source: Dissertations Abstracts International, Volume: 85-03, Section: B.

General Note  

Advisor: Efros, Alexei A.;Hardt, Moritz.

Dissertation Note  

Thesis (Ph.D.)--University of California, Berkeley, 2023.

Restrictions on Access Note  

This item must not be sold to any third party vendors.

Summary, Etc.  

요약Most models in machine learning today are fixed during deployment. As a consequence, a trained model must prepare to be robust to all possible futures, even though only one of them is actually going to happen. The basic idea of test-time training is to train on this future once it arrives in the form of a test instance. Since each test instance arrives without a ground truth label, training is performed with self-supervision. This thesis explores the first steps in realizing this idea, for images, videos and robotics.

Subject Added Entry-Topical Term  

Computer science.

Subject Added Entry-Topical Term  

Electrical engineering.

Subject Added Entry-Topical Term  

Robotics.

Index Term-Uncontrolled  

Machine learning

Index Term-Uncontrolled  

Test-time training

Index Term-Uncontrolled  

Test instance

Added Entry-Corporate Name  

University of California, Berkeley Electrical Engineering & Computer Sciences

Host Item Entry  

Dissertations Abstracts International. 85-03B.

Host Item Entry  

Dissertation Abstract International

Electronic Location and Access  

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Control Number  

joongbu:642047