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1. (WO2018182981) SENSOR DATA PROCESSOR WITH UPDATE ABILITY
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Pub. No.: WO/2018/182981 International Application No.: PCT/US2018/022528
Publication Date: 04.10.2018 International Filing Date: 15.03.2018
IPC:
G06N 99/00 (2010.01) ,G06K 9/00 (2006.01)
G PHYSICS
06
COMPUTING; CALCULATING; COUNTING
N
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
99
Subject matter not provided for in other groups of this subclass
G PHYSICS
06
COMPUTING; CALCULATING; COUNTING
K
RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
9
Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
Applicants: MICROSOFT TECHNOLOGY LICENSING, LLC[US/US]; One Microsoft Way Redmond, Washington 98052-6399, US
Inventors: NORI, Aditya Vithal; US
CRIMINISI, Antonio; US
ANCHA, Siddharth; US
LE FOLGOC, Loïc; US
Agent: MINHAS, Sandip S.; US
CHEN, Wei-Chen Nicholas; US
DRAKOS, Katherine J.; US
HINOJOSA, Brianna L.; US
HOLMES, Danielle J.; US
SWAIN, Cassandra T.; US
WONG, Thomas S.; US
CHOI, Daniel; US
HWANG, William C.; US
WIGHT, Stephen A.; US
CHATTERJEE, Aaron C.; US
Priority Data:
15/628,56420.06.2017US
1705189.731.03.2017GB
Title (EN) SENSOR DATA PROCESSOR WITH UPDATE ABILITY
(FR) PROCESSEUR DE DONNÉES DE CAPTEUR AVEC CAPACITÉ DE MISE À JOUR
Abstract:
(EN) A sensor data processor is described comprising a memory storing a plurality of trained expert models. The machine learning system has a processor configured to receive an unseen sensor data example and, for each trained expert model, compute a prediction from the unseen sensor data example using the trained expert model. The processor is configured to aggregate the predictions to form an aggregated prediction, receive feedback about the aggregated prediction and update, for each trained expert, a weight associated with that trained expert, using the received feedback. The processor is configured to compute a second aggregated prediction by computing an aggregation of the predictions which takes into account the weights.
(FR) La présente invention concerne un processeur de données de capteur comprenant une mémoire stockant une pluralité de modèles experts entraînés. Le système d’apprentissage de machine comporte un processeur configuré pour recevoir un exemple de données de capteur non observées et, pour chaque modèle expert entraîné, calculer une prédiction à partir de l’exemple de données de capteur non observées au moyen du modèle expert d’apprentissage. Le processeur est configuré pour agréger les prédictions pour former une prédiction agrégée, recevoir un retour concernant la prédiction agrégée et mettre à jour, pour chaque expert entraîné, une pondération associée à cet expert entraîné, au moyen du retour reçu. Le processeur est configuré pour calculer une deuxième prédiction agrégée par calcul d’une agrégation des prédictions qui tient compte des pondérations.
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Designated States: AE, AG, AL, AM, AO, AT, AU, AZ, BA, BB, BG, BH, BN, BR, BW, BY, BZ, CA, CH, CL, CN, CO, CR, CU, CZ, DE, DJ, DK, DM, DO, DZ, EC, EE, EG, ES, FI, GB, GD, GE, GH, GM, GT, HN, HR, HU, ID, IL, IN, IR, IS, JO, JP, KE, KG, KH, KN, KP, KR, KW, KZ, LA, LC, LK, LR, LS, LU, LY, MA, MD, ME, MG, MK, MN, MW, MX, MY, MZ, NA, NG, NI, NO, NZ, OM, PA, PE, PG, PH, PL, PT, QA, RO, RS, RU, RW, SA, SC, SD, SE, SG, SK, SL, SM, ST, SV, SY, TH, TJ, TM, TN, TR, TT, TZ, UA, UG, US, UZ, VC, VN, ZA, ZM, ZW
African Regional Intellectual Property Organization (ARIPO) (BW, GH, GM, KE, LR, LS, MW, MZ, NA, RW, SD, SL, ST, SZ, TZ, UG, ZM, ZW)
Eurasian Patent Office (AM, AZ, BY, KG, KZ, RU, TJ, TM)
European Patent Office (EPO) (AL, AT, BE, BG, CH, CY, CZ, DE, DK, EE, ES, FI, FR, GB, GR, HR, HU, IE, IS, IT, LT, LU, LV, MC, MK, MT, NL, NO, PL, PT, RO, RS, SE, SI, SK, SM, TR)
African Intellectual Property Organization (BF, BJ, CF, CG, CI, CM, GA, GN, GQ, GW, KM, ML, MR, NE, SN, TD, TG)
Publication Language: English (EN)
Filing Language: English (EN)