Artificial intelligence and data

Edmond de Belamy

Edmond de Belamy is a 2018 portrait generated by a GAN and printed on canvas by the Paris collective Obvious, sold at Christie's New York for $432,500.

Edmonds–Karp algorithm

The Edmonds–Karp algorithm is a polynomial-time method for computing maximum flow, published by Jack Edmonds and Richard M. Karp in 1972, with O(m²n) running time independent of capacities.

EfficientDet is a family of scalable object detection models from Google Research, introduced at CVPR 2020, using EfficientNet backbones with a bi-directional feature pyramid network and compound scaling.

EfficientNet

EfficientNet is a family of convolutional neural networks for image classification that scales depth, width, and resolution together, reported by Mingxing Tan and Quoc V. Le in 2019.

Egeria

Egeria (ODPi Egeria) is an LF AI & Data open source project, contributed by IBM and ING in 2018, providing an Apache-2.0 open metadata type system, OMAG server platform, cohorts, and integration connectors for cross-tool metadata exchange and governance.

Ego-motion estimation

Ego-motion estimation is the computer vision task of computing a sensor platform's own translation and orientation over time from sequential camera images or lidar scans.

Eigenface

An eigenface is an eigenvector reshaped into a face-like image, produced by principal component analysis of face photographs; the method was introduced for face recognition by Turk and Pentland at MIT in 1991.

Eigenvector centrality

Eigenvector centrality is a network measure in which each node's score depends on the scores of the nodes pointing to it, first applied by Edmund Landau in 1895.

Elastic net regularization

Elastic net regularization, also known as the elastic net, is a regression method combining the lasso and ridge penalties, proposed by Hui Zou and Trevor Hastie at Stanford in 2005.

Elastic weight consolidation

Elastic weight consolidation (EWC) is a continual learning algorithm introduced by James Kirkpatrick and colleagues at Google DeepMind in 2017 to overcome catastrophic forgetting in neural networks.

Elasticsearch

Elasticsearch is a distributed search and analytics engine built on Apache Lucene that stores JSON documents searchable in near real time, created by Shay Banon and released in 2010.

Electoral roll

An electoral roll, also called an electoral register or voter roll, is the official list of persons entitled to vote, which election authorities use to assign ballots.

Electronic System for Travel Authorization

The Electronic System for Travel Authorization, or ESTA, is an automated U.S. system that screens Visa Waiver Program travelers before they board a carrier to the United States.

Elementary Data

Elementary Data (elementary-data.com) is a Tel Aviv-based data observability company founded in 2021 by Or Avidov and Maayan Salom, YC W22, offering an open-source dbt-native observability package and Elementary Cloud; acquired by Boomi in October 2026.

Elements of AI

Elements of AI is a series of free online courses on artificial intelligence created by MinnaLearn, formerly Reaktor, and the University of Helsinki, with over 1.4 million students.

Elephant herding optimization

Elephant herding optimization (EHO) is a swarm-based metaheuristic algorithm for continuous global optimization, introduced in 2015, that mimics elephant herds led by a matriarch, with males separating from the group.

ELIZA

ELIZA, also known as Eliza AI, is a natural language conversation program written by Joseph Weizenbaum at MIT and published in 1966, usually considered the first chatbot.

ELIZA effect

The ELIZA effect is the tendency to attribute human-like understanding, intention, or feeling to computer programs even when users know they follow simple rules, named for the 1966 MIT chatbot ELIZA by Joseph Weizenbaum.

Ellipsoid method

The ellipsoid method is an iterative algorithm for convex optimization that shrinks enclosing ellipsoids, used by Khachiyan in 1979 to prove linear programming solvable in polynomial time.

Elman neural network

The Elman neural network, also called a simple recurrent network, is a recurrent network that copies its hidden layer's previous activations into a context layer, enabling sequence prediction.

Embarrassingly parallel

An embarrassingly parallel problem, also called pleasingly parallel, splits into independent tasks needing little or no communication between processors, scaling from PC networks to supercomputers.

Embase

Embase, the Excerpta Medica database, is an Elsevier biomedical bibliographic database indexing journals, conferences, trials, and preprints, and is a key source for systematic reviews alongside MEDLINE.

Embedding (machine learning)

An embedding in machine learning is a learned vector of floating-point numbers representing items such as words or images, arranged so that similar items land near each other.

Embulk

Embulk is an open-source, plugin-based parallel bulk data loader for databases, storages, file formats, and cloud services, released in 2015 by Sadayuki Furuhashi (Sada) of Treasure Data; latest release v0.11.5 (2024), Apache-2.0 licensed, now in maintenance mode (2025).

Empirical Methods in Natural Language Processing

Empirical Methods in Natural Language Processing, or EMNLP, is an annual academic conference on natural language processing, first held in 1996 and one of the main NLP publication venues alongside ACL.

Empirical risk minimization

Empirical risk minimization (ERM) is a statistical learning principle that picks the model minimizing average loss on training data; Vapnik developed its theory in the 1960s and 1970s.

Empirical wavelet transform

The empirical wavelet transform (EWT) is a signal processing method, introduced by Jérôme Gilles in 2013, that builds a wavelet filter bank adapted to the analyzed signal's frequency content.

Encarta

Microsoft Encarta, also known as Encarta Encyclopedia or MSN Encarta, was a digital multimedia encyclopedia published by Microsoft from 1993 to 2009, first on CD-ROM and later online, before free competitors like Wikipedia displaced it.

Encoder–decoder neural network

An encoder–decoder neural network, often called seq2seq, is a machine-learning architecture in which an encoder compresses the input and a decoder generates the output, the standard approach for machine translation.