Student Work
Exploring the Forward-Forward Algorithm
Público DepositedContenido Descargable
open in viewerThis report explores using the Foward-Foward (FF) algorithm to train neural networks. Unlike traditional training methods that use a forward and backward pass, the FF algorithm uses two forward passes with opposite objectives. The findings of this report lay the groundwork for feature work on the FF algorithm and propose a new method to control the influence individual layers have on the network's performance.
- This report represents the work of one or more WPI undergraduate students submitted to the faculty as evidence of completion of a degree requirement. WPI routinely publishes these reports on its website without editorial or peer review.
- Creator
- Publisher
- Identifier
- E-project-121423-170542
- 115204
- Palabra Clave
- Advisor
- Year
- 2023
- Date created
- 2023-12-14
- Resource type
- Major
- Source
- E-project-121423-170542
- Rights statement
- Última modificación
- 2024-02-07
Las relaciones
- En Collection:
Elementos
Elementos
Miniatura | Título | Visibilidad | Embargo Release Date | Acciones |
---|---|---|---|---|
Jared_Leonard_MQP.pdf | Público | Descargar |
Permanent link to this page: https://digital.wpi.edu/show/f7623h82x