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De-anonymization
| AI Glossary |
Matching anonymous data (also known as de-identified data) with publicly available information, or auxiliary data, in order to discover the individual to whom the data belong.23 (see anonymization.)
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Identified, английский
Information, английский
- Knowledge of a particular event or situation, or knowledge communicated or received concerning a particular fact.
- Информация
- Facts about something have you any information about the treatment of sunburn? the police won’t give us any information about how the accident happened. you haven’t given me enough information about when your symptoms started. that’s a very useful piece or bit of information. (note: no plural: some information; a piece of information.)
- N информация | attr. информационный flow, structure source of ~ источник информации 1 ранее использовался в более широком значении как ‘умозаключе- ние’. 2 получение выводных данных в процессе обработки информации и/или языка и само выводное знание, умозаключение; мыслительная операция, в ходе которой человек выходит за пределы данных в тек- сте сведений и получает новую информацию. 3 аффикс, вставляемый внутрь корня слова при словообразовании или словоизменении.
- In admiralty courts, implies a clause introduced into a citation, intimating that in the event of a party cited not appearing, the court will proceed in his absence.
- Информация; данные; сведения
- Координационный комитет ин4юрмации о проектируемых и возводимых объектах строительства
- Literally that which forms within, but more adequately
- Data that has been recorded, classified, organized, related or interpreted so that meaning is apparent.
- Contextualised data providing answer to a certain question decreasing uncertainty.
- Информация, сведения
Individual, английский
Физическое лицо
Anonymization, английский
Also referred to as data de-identification, this is the process of removing or replacing with synthetic values any identifiable information in data. this is intended to make it impossible to derive insights on any specific individual in the data while remaining useful for the intended use of the data.6 (see de-anonymization.) application programming interfaces (apis): programming tools for describing how one program can access the functionality of another7 while hiding the implementation details inside each program. application-specific integrated circuit (asic): a chipset custom designed to perform a particular task. asics could provide significant performance gains over generic chips but are inflexible in their functions compared to central processing units.
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Deep learning, английский
- A machine learning implementation technique that exploits large quantities of data, or feedback from interactions with a simulation or the environment, as training sets for a network with multiple hidden layers, called a deep neural network, often employing 605 p an iterative optimization technique called gradient descent, to tune large numbers of parameters that describe weights given to connections among units.25 deep neural networks (dnn): a deep learning architecture that is trained on data or feedback, generating outputs, calculating errors, and adjusting its internal parameters. the process is repeated possibly hundreds of thousands of times until the network achieves an acceptable level of performance. it has proved to be an effective technique for image classification, object detection, speech recognition, some kinds of game-playing, and natural language processing––problems that challenged researchers for decades. by learning from data, dnns can solve some problems much more effectively and also solve problems that were never solvable before.26
- Подход к созданию богатых иерархических представлений посредством эффективного обучения архитектур с неограниченным количеством слоев.
- An artificial intelligence function that imitates the workings of the human brain in processing data and creating patterns for use in decision making. essentially, teaching computers to process information more like humans do.
Data architecture, английский
The structure of an organization’s logical and physical data assets and data management resources.20
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