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1. WO2020112228 - DYNAMIC RECONFIGURATION TRAINING COMPUTER ARCHITECTURE

Publication Number WO/2020/112228
Publication Date 04.06.2020
International Application No. PCT/US2019/053219
International Filing Date 26.09.2019
IPC
G06N 3/10 2006.01
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
3Computer systems based on biological models
02using neural network models
10Simulation on general purpose computers
G06N 3/04 2006.01
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
3Computer systems based on biological models
02using neural network models
04Architecture, e.g. interconnection topology
G06N 3/08 2006.01
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
3Computer systems based on biological models
02using neural network models
08Learning methods
G06N 5/00 2006.01
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
5Computer systems using knowledge-based models
G06N 7/00 2006.01
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
7Computer systems based on specific mathematical models
G06N 20/10 2019.01
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
20Machine learning
10using kernel methods, e.g. support vector machines
CPC
G06F 16/2246
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
FELECTRIC DIGITAL DATA PROCESSING
16Information retrieval; Database structures therefor; File system structures therefor
20of structured data, e.g. relational data
22Indexing; Data structures therefor; Storage structures
2228Indexing structures
2246Trees, e.g. B+trees
G06F 16/285
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
FELECTRIC DIGITAL DATA PROCESSING
16Information retrieval; Database structures therefor; File system structures therefor
20of structured data, e.g. relational data
28Databases characterised by their database models, e.g. relational or object models
284Relational databases
285Clustering or classification
G06F 9/44505
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
FELECTRIC DIGITAL DATA PROCESSING
9Arrangements for program control, e.g. control units
06using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
44Arrangements for executing specific programs
445Program loading or initiating
44505Configuring for program initiating, e.g. using registry, configuration files
G06K 9/623
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
9Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
62Methods or arrangements for recognition using electronic means
6217Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
6228Selecting the most significant subset of features
623by ranking or filtering the set of features, e.g. using a measure of variance or of feature cross-correlation
G06N 20/00
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
20Machine learning
G06N 20/10
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
20Machine learning
10using kernel methods, e.g. support vector machines [SVM]
Applicants
  • RAYTHEON COMPANY [US]/[US]
Inventors
  • KIM, Peter
  • FISHBONE, Justin A.
Agents
  • PERDOK, Monique M.
  • ARORA, Suneel, Reg. No. 42,267
  • BEEKMAN, Marvin L., Reg. No. 38,377
  • BIANCHI, Timothy E., Reg. No. 39,610
  • BLACK, David W., Reg. No. 42,331
  • LANG, Allen R., Reg. No. 58,829
  • MCCRACKIN, Ann M., Reg. No. 42,858
  • SCHEER, Bradley W., Reg. No. 47,059
Priority Data
62/771,79627.11.2018US
Publication Language English (EN)
Filing Language English (EN)
Designated States
Title
(EN) DYNAMIC RECONFIGURATION TRAINING COMPUTER ARCHITECTURE
(FR) ARCHITECTURE D'ORDINATEUR D'ENTRAÎNEMENT À RECONFIGURATION DYNAMIQUE
Abstract
(EN)
A dynamic reconfiguration training machine learning computer architecture is disclosed. According to some aspects, a computing machine accesses a configuration file. The configuration file specifies parameters for a machine learning session. The computing machine trains a machine learning module to solve a problem, where the machine learning module operates according to the parameters specified in the configuration file. The computing machine generates an output representing the trained machine learning module.
(FR)
L'invention concerne une architecture d'ordinateur d'apprentissage automatique d'entraînement à reconfiguration dynamique. Selon certains aspects, une machine informatique accède à un fichier de configuration. Le fichier de configuration spécifie des paramètres pour une session d'apprentissage automatique. La machine informatique entraîne un module d'apprentissage automatique pour résoudre un problème, le module d'apprentissage automatique fonctionnant conformément aux paramètres spécifiés dans le fichier de configuration. La machine informatique génère une sortie qui représente le module d'apprentissage automatique entraîné.
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