What perceptron neural networks are (not) good for?-Reference-Cited by-同舟云学术

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What perceptron neural networks are (not) good for?

Published:2023-04 Issue: Volume:621 Page:844-857
ISSN:0020-0255
Container-title:Information Sciences
language:en
Short-container-title:Information Sciences

Author:

Calude Cristian S.,Heidari Shahrokh,Sifakis Joseph

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Computer Science Applications,Theoretical Computer Science,Control and Systems Engineering,Software

Reference30 articles.

1. Discrete Mathematics of Neural Networks: Selected Topics;Anthony,2001

2. M. Anthony. Boolean functions and artificial neural networks. CDAM research report series (LSE-CDAM-2003-01), URL:http://www.cdam.lse.ac.uk/Reports/Files/cdam-2003-01.pdf, 2003.

3. Learnability can be undecidable;Ben-David;Nature Mach. Intell.,2019

4. Theories of Computational Complexity;Calude,1988

5. Adiabatic quantum computing challenges;Calude;ACM SIGACT News,2015

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1. Topological equivalence classification and enumeration of n-input linearly separable Boolean functions;Information Sciences;2024-02

2. Impossibility Results in AI: A Survey;ACM Computing Surveys;2023-08-25

3. An Order Reduction Design Framework for Higher-Order Binary Markov Random Fields;Entropy;2023-03-20

4. Classification using Perceptron in Low Feature Space;2023 6th International Conference on Information Systems and Computer Networks (ISCON);2023-03-03

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