Score-Based Hypothesis Testing for Unnormalized Models

Score-Based Hypothesis Testing for Unnormalized Models

Unnormalized statistical models play an important role in machine learning, statistics, and signal processing. In this paper, we derive a new hypothesis testing procedure for unnormalized models. Our approach is motivated by the success of score matching techniques that avoid the intensive computati...

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Bibliographic Details
Main Authors: Suya Wu, Enmao Diao, Khalil Elkhalil, Jie Ding, Vahid Tarokh
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Hypothesis testing
goodness-of-fit
score matching
unnormalized statistical models
Online Access:https://ieeexplore.ieee.org/document/9813688/

Internet

https://ieeexplore.ieee.org/document/9813688/

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