is a form of regularization useful in training neural networks. Dropout regularization works by removing a random selection of a fixed number of the units in a network layer for a single gradient step. The more units dropped out, the stronger the regularization429.
Dynamic epistemic logic (DEL) is a logical framework dealing with knowledge and information change. Typically, DEL focuses on situations involving multiple agents and studies how their knowledge changes when events occur430.
Dynamic model is a model that is trained online in a continuously updating fashion. That is, data is continuously entering the model431,432.
«E»
Eager execution is a TensorFlow programming environment in which operations run immediately. By contrast, operations called in graph execution don’t run until they are explicitly evaluated. Eager execution is an imperative interface, much like the code in most programming languages. Eager execution programs are generally far easier to debug than graph execution programs433.
Eager learning is a learning method in which the system tries to construct a general, input-independent target function during training of the system, as opposed to lazy learning, where generalization beyond the training data is delayed until a query is made to the system434.
Early stopping is a method for regularization that involves ending model training before training loss finishes decreasing. In early stopping, you end model training when the loss on a validation dataset starts to increase, that is, when generalization performance worsens435.
Earth mover’s distance (EMD) is a measure of the relative similarity between two documents. The lower the value, the more similar the documents436.
Ebert test is a test which gauges whether a computer-based synthesized voice can tell a joke with sufficient skill to cause people to laugh. It was proposed by film critic Roger Ebert at the 2011 TED conference as a challenge to software developers to have a computerized voice master the inflections, delivery, timing, and intonations of a speaking human. The test is similar to the Turing test proposed by Alan Turing in 1950 as a way to gauge a computer’s ability to exhibit intelligent behavior by generating performance indistinguishable from a human being437.
Echo state network (ESN) is a recurrent neural network with a sparsely connected hidden layer (with typically 1% connectivity). The connectivity and weights of hidden neurons are fixed and randomly assigned. The weights of output neurons can be learned so that the network can (re) produce specific temporal patterns. The main interest of this network is that although its behaviour is non-linear, the only weights that are modified during training are for the synapses that connect the hidden neurons to output neurons. Thus, the error function is quadratic with respect to the parameter vector and can be differentiated easily to a linear system438.
Ecosystem of the digital economy is a partnership of organizations that ensures the constant interaction of their technological platforms, applied Internet services, analytical systems, information systems of state authorities of the Russian Federation, organizations and citizens439.
Edge computing is a subspecies of distributed computing in which information processing takes place in close proximity to the place where the data was received and will be consumed (for example, using phones and other consumer devices)440.
Electronic circuit is a product, a combination of individual electronic components, such as resistors, capacitors, diodes, transistors and integrated circuits, interconnected to perform any task or a circuit with conventional signs441,442.
Electronic Data Interchange (EDI) is a series of standards and conventions for the transfer of structured digital information between organizations, based on certain regulations and formats of transmitted messages443.
Electronic government (e-Government) is a package of technologies and a set of related organizational measures, regulatory and legal support for organizing digital interaction between public authorities of various branches of government, citizens, organizations and other economic entities444.
Electronic industry is a set of organizations that perform scientific, technological and other work in the field of development, production, maintenance of operation, as well as providing services related to electronic and microelectronic products, respectively445.
Electronic Medical Record (EMR) is electronic health record, is the systematized collection of patient and population electronically stored health information in a digital format. These records can be shared across different healthcare settings446.
Electronic state is a way of implementing the information aspects of state activity based on the use of IT systems, as well as a new type of state based on the use of this technology. In the Russian Federation, activities to create an «electronic state» are carried out within the framework of the federal target program «Electronic Russia»447,448.
Eli5 environment is a Python environment that is used to debug and visualize machine learning models. By default, it supports several machine learning frameworks – Scikit-learn, XGBoost, LightGBM, CatBoost, lightning, Keras and so on. Eli5 also provides LIME and Permutation Importance models to test machine learning pipelines as black boxes449.
ELIZA effect is a term used to discuss progressive artificial intelligence. It is the idea that people may falsely attach meanings of symbols or words that they ascribe to artificial intelligence in technologies450.
Embedding (Word Embedding) is one instance of some mathematical structure contained within another instance, such as a group that is a subgroup451.
Embedding space – the d-dimensional vector space that features from a higher-dimensional vector space are mapped to. Ideally, the embedding space contains a structure that yields meaningful mathematical results; for example, in an ideal embedding space, addition and subtraction of embeddings can solve word analogy tasks. The dot product of two embeddings is a measure
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Dynamic epistemic logic [Электронный ресурс] https://en.wikipedia.org URL: https://en.wikipedia.org/wiki/Dynamic_epistemic_logic (дата обращения: 09.04.2023)
Dynamic model [Электронный ресурс] https://www.primeclasses.in URL: https://www.primeclasses.in/glossary/data-science-course/machine-learning/dynamic-model (дата обращения: 09.04.2023)
Динамическая модель [Электронный ресурс] https://kartaslov.ru URL: https://kartaslov.ru/карта-знаний/Динамическая+модель (дата обращения: 09.04.2023)
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Eager learning [Электронный ресурс] https://en.wikipedia.org URL: https://en.wikipedia.org/wiki/Eager_learning (дата обращения 06.07.2023)
Early stopping [Электронный ресурс] https://developers.google.com URL: https://developers.google.com/machine-learning/glossary#early-stopping (дата обращения: 29.06.2023)
Earth mover’s distance (EMD) [Электронный ресурс] https://developers.google.com URL: https://developers.google.com/machine-learning/glossary#earth-movers-distance-emd (дата обращения: 29.06.2023)
Ebert test [Электронный ресурс] https://detailedpedia.com URL: https://detailedpedia.com/wiki-Ebert_test (дата обращения 08.08.2021)
Echo state network (ESN) [Электронный ресурс] https://en.wikipedia.org URL: https://en.wikipedia.org/wiki/Echo_state_network (дата обращения: 30.06.2023)
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Электронная схема [Электронный ресурс] https://ru.wikipedia.org URL: https://ru.wikipedia.org/wiki/Электронная_схема (дата обращения: 11.07.2023)
EDI Electronic Data Interchange [Электронный ресурс] www.igi-global.com URL: https://www.igi-global.com/dictionary/edi-electronic-data-interchange/9084 (дата обращения: 07.07.2022)
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Eli5 environment [Электронный ресурс] https://github.com URL: https://github.com/TeamHG-Memex/eli5 (дата обращения: 02.07.2023)
ELIZA effect [Электронный ресурс] https://www.techopedia.com URL: https://www.techopedia.com/definition/19121/eliza-effect (дата обращения: 11.07.2023)
Embedding [Электронный ресурс] https://appen.com URL: https://appen.com/ai-glossary/ (дата обращения 28.02.2022)
