Reduced complexity constructive learning algorithm

Valeriu Beiu

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)


State-of-the-art learning techniques are presented with an emphasis on constructive algorithms. The focus is on several complexity aspects pertaining to neural networks: size complexity and depth-size tradeoffs; complexity of learning; and precision of weights and thresholds as well as limited interconnectivity. Three steps are given for a detailed tight upper and lower bounds for the number-of-bits required for solving a classification problem. A solution which can lower the size of the resulting neural network by impressive constants is detailed. Results showed that small fan-ins lead to optimal hardware solutions.

Original languageEnglish
Pages (from-to)1-38
Number of pages38
JournalNeural Network World
Issue number1
Publication statusPublished - 1998
Externally publishedYes

ASJC Scopus subject areas

  • Software
  • General Neuroscience
  • Hardware and Architecture
  • Artificial Intelligence


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