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Everything about Factorial code
Data representation for machine learning
Most real world data sets consist of data vectors whose individual components are not statistically independent. In other words, knowing the value of an element will provide information about the value of elements in the data vector. When this occurs, it can be desirable to create a factorial code of the data, i.e., a new vector-valued representation of each data vector such that it gets uniquely encoded by the resulting code vector, but the code components are statistically independent. Wikipedia →
🧭 Start here: a 6-step reading path
- Read the overview: Factorial codeA 5-minute orientation
- Skim a recent paper: Codependencia laboral: análisis factorial confirmatorioInfluential work since 2022
- Pick up a classic book: Electrical wiring, industrialThe most-reprinted book on the subject
- Read the landmark paper: Nonlinear neurons in the low-noise limit: a factorial code maximizes information transferCited 200 times
- Go sideways: Types of artificial neural networksA closely related topic
- Go sideways: Independent component analysisA closely related topic
📖 Definitions
No dictionary entry for this exact phrase.
🗂️ The subject at a glance
No outline available.
🏆 Landmark papers (most cited)
Nonlinear neurons in the low-noise limit: a factorial code maximizes information transfer
Code-switching in Tunisian Arabic: a multi-factorial random forest analysis
FACTORIAL CODE WITH A GIVEN NUMBER OF INVERSIONS
Sparse factorial code representation using independent component analysis for face recognition
Searching for a binary factorial code using the ICA framework
🆕 Influential since 2022
📚 Books worth reading
Electrical wiring, industrialSmith, Robert L., Robert L. Smith · 1977
Decknamenverzeichnis deutscher unterirdischer Bauten, Ubootbunker, Ölanlagen, chemischer Anlagen und WIFO-Anlagen des zweiten Weltkrieges · 1994
The chocolate cipherCaroline Juskus · 2009
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
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