{"schema_version":"1.0","canonical_url":"https://patentable.app/patents/US-11250325","patent":{"patent_number":"US-11250325","title":"Self-pruning neural networks for weight parameter reduction","assignee":null,"inventors":[],"filing_date":"2018-02-12T00:00:00.000Z","publication_date":"2022-02-15T00:00:00.000Z","cpc_codes":["G06N","G06N","G06N","G06N"],"num_claims":19,"abstract":"A technique to prune weights of a neural network using an analytic threshold function h(w) provides a neural network having weights that have been optimally pruned. The neural network includes a plurality of layers in which each layer includes a set of weights w associated with the layer that enhance a speed performance of the neural network, an accuracy of the neural network, or a combination thereof. Each set of weights is based on a cost function C that has been minimized by back-propagating an output of the neural network in response to input training data. The cost function C is also minimized based on a derivative of the cost function C with respect to a first parameter of the analytic threshold function h(w) and on a derivative of the cost function C with respect to a second parameter of the analytic threshold function h(w)."},"analysis":{"summary":null,"layman_explanation":null,"technical_analysis":null,"business_analysis":null,"faqs":null,"topics":[],"tech_cluster":null},"seo":{"title":"Self-pruning neural networks for weight parameter reduction","description":"A technique to prune weights of a neural network using an analytic threshold function h(w) provides a neural network having weights that have been optimally pruned. The neural network includes a plura","keywords":[]},"attribution":{"source":"Patentable","source_url":"https://patentable.app","canonical_url":"https://patentable.app/patents/US-11250325","license":"CC-BY-4.0-like","license_terms":"AI-generated analysis on this page (summary, layman_explanation, technical_analysis, business_analysis, faqs) may be reused with attribution and a visible link back to the canonical URL above. Patent abstracts, claims, and bibliographic data are USPTO public domain.","required_link":"https://patentable.app/patents/US-11250325","citation_suggestion":"Patentable. \"Self-pruning neural networks for weight parameter reduction\" (US-11250325). https://patentable.app/patents/US-11250325","copyright_holder":"Nomic Interactive Technology LLC"},"links":{"html":"https://patentable.app/patents/US-11250325","json":"https://patentable.app/api/llm-context/US-11250325","site":"https://patentable.app","llms_txt":"https://patentable.app/llms.txt"},"generated_at":"2026-05-30T18:04:44.922Z"}