Online learning for dynamic Boltzmann machines with hidden units
US11995540B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 11, 2018 |
| Grant date | May 28, 2024 |
| Priority date | — |
| Expiry date | Jun 25, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/09
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A computer-implemented method, a computer program product, and a computer processing system are provided for online learning for a Dynamic Boltzmann Machine (DyBM) with hidden units. The method includes imposing, by a processor device, limited connections in the DyBM where (i) a current observation x[t] depends only on latest hidden units h[t-1/2] and all previous observations x[<t] and (ii) the latest hidden units h[t-1/2] depend on all the previous observations x[<t] while being independent of older hidden units h[t-1/2]. The method further includes computing, by the processor device, gradients of an objective function. The method also includes optimizing, by the processor device, the objective function in polynomial time using a stochastic Gradient Descent algorithm applied to the gradients.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.