Abstract
A mathematical model is presented for the description of parallel Boltzmann machines. The framework is based on the theory of Markov chains and combines a number of previously known results into one generic model. It is argued that parallel Boltzmann machines maximize a function consisting of a weighted sum of the well-known consensus function and a pseudoconsensus function. The weighting is determined by the amount of parallelism used in the Boltzmann machine and turns out to be problem dependent.
| Original language | English |
|---|---|
| Pages (from-to) | 65-75 |
| Number of pages | 11 |
| Journal | Journal of Parallel and Distributed Computing |
| Volume | 13 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 1991 |
| Externally published | Yes |
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