理学 学习理论 释 PAC learning PAC学习 PAC (Probably Approximately Correct)学习，中文翻译为概率近似正确学习，是计算学习理论中最重要的研究内容之一，由图灵奖得主Valiant [1]于1984年首先提出的学习框架。PAC学习给出了一种数学形式化刻画机器学习的框架，基于此框架，很多学习问题得以从理论上进一步探讨，如什么样的学习任务是可以学习的。
人工智能 机器学习 释文 probably approximately correct learning 概率近似正确学习
- Regulations on Implementation of the Law of the People's Republic of China on Bid Invitation and Bidding
- Regulations on Implementation of the Law of the People's Republic of China on Entry and Exit Animal and Plant Quarantine
- Regulations on Implementation of the Law of the People's Republic of China on the Protection of Cultural Relics
- Regulations on Implementation of the Law of the People’s Republic of China on Water and Soil Conservation
- regulations on importing and broadcasting overseas TV programs
- Regulations on Internal Supervision of Public Security Organs
- Regulations on Labor Protection in Workplaces Using Toxic Substances
- Regulations on Land Requisition Compensation and Resettlement of Migrants for Large and Medium Water Conservation and Power Construction Projects
- Regulations on Land Survey
- Regulationson License for Water Drawing and Levy and Administration of Water Resource Fees
- Regulations on Management of Fisheries Resources of Yangtze River
- Regulations on Management of River Course of the People’s Republic of China
- Regulations on Management of Urban Underground Space for Tianjin
- regulations on maritime trade
- regulations on medical service for impoverished patients
- Regulations on Medical Waste Management
- Regulations on Movable Type Printing Adopted at the Hall of Martial Valor
- regulations on national economic census
- Regulations on National General Survey of Pollution Sources
- Regulations on Newspapers and Periodicals
- regulations on payment of wages
- Regulations on Personnel Management of China's Public Institutions
- Regulations on Practicing Economy and Opposing Waste in Party and Government Organs
- Regulations on Preventing Collisions at Operation of Fishing Vessels
- Regulations on Prevention and Control of Forest Diseases and Pests