Invention Grant
- Patent Title: Machine learning implementation in processing systems
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Application No.: US16144550Application Date: 2018-09-27
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Publication No.: US11461694B2Publication Date: 2022-10-04
- Inventor: Thomas Parnell , Celestine Duenner , Dimitrios Sarigiannis , Charalampos Pozidis
- 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: Scully, Scott, Murphy & Presser, P.C.
- Agent Daniel P. Morris
- Main IPC: G06N20/00
- IPC: G06N20/00 ; G06F17/16 ; G06F17/13

Abstract:
Methods are provided for implementing training of a machine learning model in a processing system, together with systems for performing such methods. A method includes providing a core module for effecting a generic optimization process in the processing system, and in response to a selective input, defining a set of derivative modules, for effecting computation of first and second derivatives of selected functions ƒ and g in the processing system, to be used with the core module in the training operation. The method further comprises performing, in the processing system, the generic optimization process effected by the core module using derivative computations effected by the derivative modules.
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