CPC Subgroup
G06N 3/08 Learning methods
Full Title
Computing arrangements based on biological models > Neural networks > Learning methods
12 direct subcodes
Child Classifications
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- G06N 3/082 modifying the architecture, e.g. adding, deleting or silencing nodes or connections
- G06N 3/084 Backpropagation, e.g. using gradient descent
- G06N 3/086 using evolutionary algorithms, e.g. genetic algorithms or genetic programming
- G06N 3/088 Non-supervised learning, e.g. competitive learning
- G06N 3/0895 Weakly supervised learning, e.g. semi-supervised or self-supervised learning
- G06N 3/09 Supervised learning
- G06N 3/091 Active learning
- G06N 3/092 Reinforcement learning
- G06N 3/094 Adversarial learning
- G06N 3/096 Transfer learning
- G06N 3/098 Distributed learning, e.g. federated learning
- G06N 3/0985 Hyperparameter optimisation; Meta-learning; Learning-to-learn
Top Applicants
Top 10 applicants by patent filingsfor class G06, 2013–2023, worldwide · Source: EPO PATSTAT
- SAMSUNG ELECTRONICS COMPANY KR 76,952
- IBM (INTERNATIONAL BUSINESS MACHINES CORPORATION) US 62,841
- MICROSOFT TECHNOLOGY LICENSING US 44,778
- GOOGLE US 35,735
- INTEL CORPORATION US 32,087
- HUAWEI TECHNOLOGIES COMPANY CN 30,572
- TENCENT TECHNOLOGY (SHENZHEN) COMPANY 25,023
- APPLE US 23,482
- SGCC(STATE GRID CORPORATION OF CHINA) 22,548
- HUAWEI TECHNOLOGIES COMPANY 20,917