In mathematics, a Relevance Vector Machine (RVM) is a machine learning technique that uses Bayesian inference to obtain parsimonious solutions for regression...

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

A vector database, vector store or vector search engine is a database that can store vectors (fixed-length lists of numbers) along with other data items...

decision trees, k-nearest neighbors, naive Bayes, support vector machines and extreme learning machines to address multi-class classification problems. These...

recognition and machine learning, a feature vector is an n-dimensional vector of numerical features that represent some object. Many algorithms in machine learning...

gating mechanism to input or forget certain features, but lacks a context vector or output gate, resulting in fewer parameters than LSTM. GRU's performance...

encoding-decoding. In machine translation, the seq2seq model, as it was proposed in 2014, would encode an input text into a fixed-length vector, which would then...

numerical representations called tokens, and each token is converted into a vector via looking up from a word embedding table. At each layer, each token is...

representation is a real-valued vector that encodes the meaning of the word in such a way that the words that are closer in the vector space are expected to be...

Supervised learning (SL) is a paradigm in machine learning where input objects (for example, a vector of predictor variables) and a desired output value...