Similarity learning is an area of supervised machine learning in artificial intelligence. It is closely related to regression and classification, but...

the similarity of documents in the vector space model. In machine learning, common kernel functions such as the RBF kernel can be viewed as similarity functions...

analysis, cosine similarity is a measure of similarity between two non-zero vectors defined in an inner product space. Cosine similarity is the cosine of...

future temperatures based on historical data. Similarity learning is an area of supervised machine learning closely related to regression and classification...

genome databases. Similarity learning Latent semantic analysis Pei Lee, Laks V. S. Lakshmanan, Jeffrey Xu Yu: On Top-k Structural Similarity Search. ICDE 2012:774-785...

not just by arbitrary descriptors. Deep learning methods have become an accurate way to gauge semantic similarity between two text passages, in which each...

neighbors algorithm Neural networks (e.g., Multilayer perceptron) Similarity learning Given a set of N {\displaystyle N} training examples of the form...

Deep learning is a subset of machine learning that focuses on utilizing multilayered neural networks to perform tasks such as classification, regression...

Systems. 6: 737–744. Chopra, S.; Hadsell, R.; LeCun, Y. (June 2005). "Learning a Similarity Metric Discriminatively, with Application to Face Verification"...

categorization models in psychology are based on geometric similarity, assuming that learning involves the storage of specific instances (i.e. of general...

linguistics, lexical similarity is a measure of the degree to which the word sets of two given languages are similar. A lexical similarity of 1 (or 100%) would...

for vector output Kernel density estimation Representer theorem Similarity learning Cover's theorem "Kernel method". Engati. Retrieved 2023-04-04. Theodoridis...

gradient methods for learning Semantic analysis Similarity learning Sparse dictionary learning Stability (learning theory) Statistical learning theory Statistical...

Zero-shot learning (ZSL) is a problem setup in deep learning where, at test time, a learner observes samples from classes which were not observed during...

Learning disability, learning disorder, or learning difficulty (British English) is a condition in the brain that causes difficulties comprehending or...

semantic analysis Information extraction Semantic similarity Stochastic semantic analysis Ontology learning Nitin Indurkhya; Fred J. Damerau (22 February...

learning. Factors that can affect transfer include: Context and degree of original learning: how well the learner acquired the knowledge. Similarity:...

Siamese neural network t-distributed stochastic neighbor embedding Similarity learning Schroff, Florian; Kalenichenko, Dmitry; Philbin, James (2015). "FaceNet:...

Bozinovski and Ante Fulgosi (1976). "The influence of pattern similarity and transfer learning on the base perceptron training." (original in Croatian) Proceedings...

Hellinger distance, also a measure of distance between data sets Similarity learning, for other approaches to learn a distance metric from examples. "Reprint...

few principles that explain the ways humans perceive objects based on similarity, proximity, and continuity. The law of proximity states that when an individual...

Bozinovski S. and Fulgosi A. (1976). "The influence of pattern similarity and transfer learning on the base perceptron training" (original in Croatian) Proceedings...

Unsupervised learning is a framework in machine learning where, in contrast to supervised learning, algorithms learn patterns exclusively from unlabeled...

research that explores methodological and structural similarities between certain physical systems and learning systems, in particular neural networks. For example...

Self-supervised learning (SSL) is a paradigm in machine learning where a model is trained on a task using the data itself to generate supervisory signals...

Active learning is a special case of machine learning in which a learning algorithm can interactively query a human user (or some other information source)...

In machine learning, support vector machines (SVMs, also support vector networks) are supervised max-margin models with associated learning algorithms...

interpolation Neighbor joining Principal component analysis Range search Similarity learning Singular value decomposition Sparse distributed memory Statistical...

(also known as a string similarity metric or string distance function) is a metric that measures distance ("inverse similarity") between two text strings...

Observational learning is learning that occurs through observing the behavior of others. It is a form of social learning which takes various forms, based...