- 专利标题: AUTOMATED TUNING OF HYPERPARAMETERS BASED ON RANKINGS IN A FEDERATED LEARNING ENVIRONMENT
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申请号: US18115596申请日: 2023-02-28
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公开(公告)号: US20240144026A1公开(公告)日: 2024-05-02
- 发明人: Yi Zhou , Parikshit Ram , Theodoros Salonidis , Nathalie Baracaldo Angel , Horst Cornelius Samulowitz , Heiko H. Ludwig
- 申请人: International Business Machines Corporation
- 申请人地址: US NY Armonk
- 专利权人: International Business Machines Corporation
- 当前专利权人: International Business Machines Corporation
- 当前专利权人地址: US NY Armonk
- 优先权: GR 220100875 2022.10.26
- 主分类号: G06N3/098
- IPC分类号: G06N3/098
摘要:
A computer-implemented method, according to one approach, includes issuing a hyperparameter optimization (HPO) query to a plurality of computing devices. HPO results are received from the plurality of computing devices, and the HPO results include a set of hyperparameter (HP)/rank value pairs. The method further includes computing, based on the set of HP/rank value pairs, a global set of HPs from the HPO results for federated learning (FL) training. An indication of the global set of HPs is output to the plurality of computing devices. A computer program product, according to another approach, includes a computer readable storage medium having program instructions embodied therewith. The program instructions are readable and/or executable by a computer to cause the computer to perform the foregoing method.
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