Extreme learning machines are feedforward neural networks for classification, regression, clustering, sparse approximation, compression and feature learning...

In machine learning, a neural network (also artificial neural network or neural net, abbreviated ANN or NN) is a computational model inspired by the structure...

outline is provided as an overview of, and topical guide to, machine learning: Machine learning (ML) is a subfield of artificial intelligence within computer...

In machine learning and statistical classification, multiclass classification or multinomial classification is the problem of classifying instances into...

Adversarial machine learning is the study of the attacks on machine learning algorithms, and of the defenses against such attacks. A survey from May 2020...

"Real-time fault diagnosis for gas turbine generator systems using extreme learning machine". Neurocomputing. 128: 249–257. doi:10.1016/j.neucom.2013.03.059...

Extreme Machines was a documentary series created by Pioneer Productions for The Learning Channel and Discovery Channel. The series focused mainly on...

machine learning (ML) research and have been cited in peer-reviewed academic journals. Datasets are an integral part of the field of machine learning...

given by the Extreme Theory of Functional Connections (X-TFC) framework, where a single-layer Neural Network and the extreme learning machine training algorithm...

Elm (programming language) European Logarithmic Microprocessor Extreme learning machine Christina Elm (born 1995), Danish handball player David Elm (footballer)...

of a random kitchen sink algorithm (also going by the name of extreme learning machines in some communities). In 2019, another possible implementation...

Spectroscopy Combined with Characteristic Variables Selection and Extreme Learning Machine". Food and Bioprocess Technology. 6 (9): 2486–2493. doi:10.1007/s11947-012-0936-0...

Darsana (December 2018). "Fine-Tuning of Pre-Trained Deep Learning Models with Extreme Learning Machine". 2018 International Conference on Computational Science...

Reinforcement learning is one of the three basic machine learning paradigms, alongside supervised learning and unsupervised learning. Reinforcement learning differs...

Extremal Ensemble Learning (EEL) is a machine learning algorithmic paradigm for graph partitioning. EEL creates an ensemble of partitions and then uses...

(CNN), Long Short-term Memory (LSTM), and Extreme Learning Machine (ELM). The popularity of deep learning approaches in the domain of emotion recognition...

now be processed using the Support vector machine, extreme learning machines, or some other machine learning algorithm to classify images. Such classifiers...

Machine learning in bioinformatics is the application of machine learning algorithms to bioinformatics, including genomics, proteomics, microarrays, systems...

Meta-learning is a subfield of machine learning where automatic learning algorithms are applied to metadata about machine learning experiments. As of...

develops and studies methods and software that enable machines to perceive their environment and use learning and intelligence to take actions that maximize...

computer vision, natural language processing, and machine perception. The first paper on zero-shot learning in natural language processing appeared in a 2008...

become an important optimization method in machine learning. Both statistical estimation and machine learning consider the problem of minimizing an objective...

of machine learning (ML) in earth sciences include geological mapping, gas leakage detection and geological feature identification. Machine learning is...

begins to "memorize" training data rather than "learning" to generalize from a trend. As an extreme example, if the number of parameters is the same...

show how to imprint vector fields into neurals networks such as Extreme Learning Machines (ELMs) in a guaranteed stable manner. Furthermore, the paper won...

PMID 19403281. Yuan, Qi (2011). "Epileptic EEG classification based on extreme learning machine and nonlinear features". Epilepsy Research. 96 (1–2): 29–38. doi:10...

external data as in RAG), model uncertainty estimation techniques from machine learning may be applied to detect hallucinations. According to Luo et al., the...

August 26, 2019. C. Merkel and D. Kudithipudi, "Neuromemristive extreme learning machines for pattern classification," ISVLSI, 2014. Maan, A.K.; James,...

Kelmė, also spelt Kelm, a Lithuanian town Kelm, a surname kernel extreme learning machine, a method in statistics Search for "kelm" on Wikipedia. All pages...

disease. Algorithms, such as Nearest-Neighbour classifiers, RF, extreme learning machines, SVMs, and deep neural networks (DNNs), are used for VS based...