Systems and methods for quantum processing of data
US9727824B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jun 26, 2014 |
| Grant date | Aug 8, 2017 |
| Priority date | — |
| Expiry date | Dec 5, 2035 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F18/28
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Systems, methods and aspects, and embodiments thereof relate to unsupervised or semi-supervised features learning using a quantum processor. To achieve unsupervised or semi-supervised features learning, the quantum processor is programmed to achieve Hierarchal Deep Learning (referred to as HDL) over one or more data sets. Systems and methods search for, parse, and detect maximally repeating patterns in one or more data sets or across data or data sets. Embodiments and aspects regard using sparse coding to detect maximally repeating patterns in or across data. Examples of sparse coding include L0 and L1 sparse coding. Some implementations may involve appending, incorporating or attaching labels to dictionary elements, or constituent elements of one or more dictionaries. There may be a logical association between label and the element labeled such that the process of unsupervised or semi-supervised feature learning spans both the elements and the incorporated, attached or appended label.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.