{"schema_version":"1.0","canonical_url":"https://patentable.app/patents/US-9600777","patent":{"patent_number":"US-9600777","title":"Configuring and optimizing computational structure for a machine learning application using a tuple of vectors","assignee":null,"inventors":[],"filing_date":"2014-03-10T00:00:00.000Z","publication_date":"2017-03-21T00:00:00.000Z","cpc_codes":["G06N","G06F"],"num_claims":13,"abstract":"A method provides program structures for constructing a program that is learned over training data. In one example, two specific program structures are provided in which the first program structure transforms each vector in an input tuple of vectors to provide an output tuple of vectors, and the second program structure operates on an input tuple of vectors to provide an output tuple of vectors by applying one or more transformations that each involves two or more vectors in the input tuple. The transformations of the first and second program structures may be linear transformations. The program may alternatively execute the first program structure and the second program structure in any suitable order a number of times, beginning with operating one of the program structures on an initial tuple of vectors. The vectors may each consist of an ordered set of real numbers."},"analysis":{"summary":null,"layman_explanation":null,"technical_analysis":null,"business_analysis":null,"faqs":null,"topics":[],"tech_cluster":null},"seo":{"title":"Configuring and optimizing computational structure for a machine learning application using a tuple of vectors","description":"A method provides program structures for constructing a program that is learned over training data. In one example, two specific program structures are provided in which the first program structure tr","keywords":[]},"attribution":{"source":"Patentable","source_url":"https://patentable.app","canonical_url":"https://patentable.app/patents/US-9600777","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-9600777","citation_suggestion":"Patentable. \"Configuring and optimizing computational structure for a machine learning application using a tuple of vectors\" (US-9600777). https://patentable.app/patents/US-9600777","copyright_holder":"Nomic Interactive Technology LLC"},"links":{"html":"https://patentable.app/patents/US-9600777","json":"https://patentable.app/api/llm-context/US-9600777","site":"https://patentable.app","llms_txt":"https://patentable.app/llms.txt"},"generated_at":"2026-06-06T10:35:20.153Z"}