{"schema_version":"1.0","canonical_url":"https://patentable.app/patents/US-11978272","patent":{"patent_number":"US-11978272","title":"Domain adaptation for machine learning models","assignee":null,"inventors":[],"filing_date":"2022-08-09T00:00:00.000Z","publication_date":"2024-05-07T00:00:00.000Z","cpc_codes":["G06V","G06F","G06F","G06N","G06N","G06N","G06N","G06N","G06V","G06V","G06V","G06V","G06V","G06N"],"num_claims":20,"abstract":"Adapting a machine learning model to process data that differs from training data used to configure the model for a specified objective is described. A domain adaptation system trains the model to process new domain data that differs from a training data domain by using the model to generate a feature representation for the new domain data, which describes different content types included in the new domain data. The domain adaptation system then generates a probability distribution for each discrete region of the new domain data, which describes a likelihood of the region including different content described by the feature representation. The probability distribution is compared to ground truth information for the new domain data to determine a loss function, which is used to refine model parameters. After determining that model outputs achieve a threshold similarity to the ground truth information, the model is output as a domain-agnostic model."},"analysis":{"summary":null,"layman_explanation":null,"technical_analysis":null,"business_analysis":null,"faqs":null,"topics":[],"tech_cluster":null},"seo":{"title":"Domain adaptation for machine learning models","description":"Adapting a machine learning model to process data that differs from training data used to configure the model for a specified objective is described. A domain adaptation system trains the model to pro","keywords":[]},"attribution":{"source":"Patentable","source_url":"https://patentable.app","canonical_url":"https://patentable.app/patents/US-11978272","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-11978272","citation_suggestion":"Patentable. \"Domain adaptation for machine learning models\" (US-11978272). https://patentable.app/patents/US-11978272","copyright_holder":"Nomic Interactive Technology LLC"},"links":{"html":"https://patentable.app/patents/US-11978272","json":"https://patentable.app/api/llm-context/US-11978272","site":"https://patentable.app","llms_txt":"https://patentable.app/llms.txt"},"generated_at":"2026-05-31T16:15:18.724Z"}