Invention Grant
- Patent Title: Interactive learning
-
Application No.: US14748375Application Date: 2015-06-24
-
Publication No.: US10169716B2Publication Date: 2019-01-01
- Inventor: Brian P. Gaucher , Jonathan Lenchner , David O. Melville , Valentina Salapura
- Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
- Applicant Address: US NY Armonk
- Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
- Current Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
- Current Assignee Address: US NY Armonk
- Agency: Tutunjian & Bitetto, P.C.
- Agent Rahan Uddin
- Main IPC: G06N99/00
- IPC: G06N99/00

Abstract:
A system and method are provided for shared machine learning. The method includes providing a model to a plurality of agents included in a machine learning system. The model specifies attributes and attribute value data types for an event in which the agents act. The method further includes receiving agent-provided inputs during an instance of the event. The agent-provided inputs include estimated attribute values that are consistent with the attribute value data types. The method also includes determining expertise weights for at least some agents in response to at least one ground-truth which is learned from the estimated attribute values. The method additionally includes determining an estimate value for one or more of the attributes using respective adaptive mixtures of the estimated attribute values.
Public/Granted literature
- US20160117603A1 INTERACTIVE LEARNING Public/Granted day:2016-04-28
Information query