Boolean autoencoders and hypercube clustering complexity

DOI10.1007/s10623-012-9719-xzbMath1252.68223OpenAlexW2013380636MaRDI QIDQ690669

Pierre Baldi

Publication date: 28 November 2012

Published in: Designs, Codes and Cryptography (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10623-012-9719-x

zbMATH Keywords

computational complexityclusteringlearningBoolean circuitsautoencoders

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Analytic circuit theory (94C05) Coding and information theory (compaction, compression, models of communication, encoding schemes, etc.) (aspects in computer science) (68P30) Computational difficulty of problems (lower bounds, completeness, difficulty of approximation, etc.) (68Q17)

Related Items (1)

The capacity of feedforward neural networks

Uses Software

• apcluster
• APCluster
• darch

Cites Work

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• Clustering by Passing Messages Between Data Points
• Proof of the squashed cube conjecture
• Cubical graphs and cubical dimensions
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• Complex-valued autoencoders
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• On the Complexity of Some Common Geometric Location Problems
• Deep, Narrow Sigmoid Belief Networks Are Universal Approximators
• The Planar k-Means Problem is NP-Hard
• The complexity of cubical graphs
• On the complexity of some coding problems (Corresp.)
• A Clustering and Data-Reorganizing Algorithm
• On the inherent intractability of certain coding problems (Corresp.)
• The intractability of computing the minimum distance of a code
• Learning representations by back-propagating errors
• A Fast Learning Algorithm for Deep Belief Nets
• $B$-valuations of graphs

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