Live briefing
Everything about Relevance vector machine
Machine learning technique
In mathematics, a Relevance Vector Machine (RVM) is a machine learning technique that uses Bayesian inference to obtain parsimonious solutions for regression and probabilistic classification. A greedy optimisation procedure and thus fast version were subsequently developed. The RVM has an identical functional form to the support vector machine, but provides probabilistic classification. Wikipedia →
🧭 Start here: a 6-step reading path
- Read the overview: Relevance vector machineA 5-minute orientation
- Skim a recent paper: Multi-Kernel Relevance Vector Machine With Parameter Optimization for Cycling Aging Prediction of Lithium-Ion BatteriesInfluential work since 2022
- Pick up a classic book: Artificial intelligenceThe most-reprinted book on the subject
- Read the landmark paper: Fault diagnosis of low speed bearing based on relevance vector machine and support vector machineCited 291 times
- Go sideways: Support vector machineA closely related topic
- Go sideways: Least-squares support vector machineA closely related topic
📖 Definitions
No dictionary entry for this exact phrase.
🗂️ The subject at a glance
No outline available.
🏆 Landmark papers (most cited)
Fault diagnosis of low speed bearing based on relevance vector machine and support vector machine
Application of relevance vector machine and logistic regression for machine degradation assessment
Relevance vector machine for tool wear prediction
Relevance vector machine for automatic detection of clustered microcalcifications
Robust Hyperspectral Classification Using Relevance Vector Machine
Application of relevance vector machine and survival probability to machine degradation assessment
Facies Identification Based on Multikernel Relevance Vector Machine
Classification of silent speech using support vector machine and relevance vector machine
🆕 Influential since 2022
Multi-Kernel Relevance Vector Machine With Parameter Optimization for Cycling Aging Prediction of Lithium-Ion Batteries
Online state-of-health estimation of lithium-ion battery based on relevance vector machine with dynamic integration
Adaptive relevance vector machine combined with Markov-chain-based importance sampling for reliability analysis
Extended Relevance Vector Machine-Based Remaining Useful Life Prediction for DC-Link Capacitor in High-Speed Train
Predicting ground vibration during rock blasting using relevance vector machine improved with dual kernels and metaheuristic algorithms
📚 Books worth reading
Artificial intelligenceStuart J. Russell, Peter Norvig · 1994
Gaussian processes for machine learningCarl Edward Rasmussen · 2005
Introduction to information retrievalChristopher D. Manning, Prabhakar Raghavan · 2008
Intelligent Information and Database SystemsAli Selamat · 2013- 📕Applied data miningGuandong Xu · 2013
Economic Modeling Using Artificial Intelligence MethodsTshilidzi Marwala · 2013- 📕Data management for multimedia retrievalK. Selçuk Candan · 2010
Parallel Processes and Related Automata =: Parallele Prozesse Und Damit Zusammenhangende Automaten (Journal of Neural Transmission: Supplementum)Walter Knodel · 1981
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
🔗 Related topics
- Support vector machine In machine learning, a support vector machine (SVM) or support vector network is a supervised max-margin model with associated learning algorithms that…
- Least-squares support vector machine Least-squares support-vector machines (LS-SVM) for statistics and in statistical modeling, are least-squares versions of support-vector machines (SVM)…
- Kernel method In machine learning, kernel machines are a class of algorithms for pattern analysis, whose best known member is the support-vector machine (SVM). These…
- Multiple kernel learning Multiple kernel learning refers to a set of machine learning methods that use a predefined set of kernels and learn an optimal linear or non-linear combination…
- Kernel perceptron In machine learning, the kernel perceptron is a variant of the popular perceptron learning algorithm that can learn kernel machines, i.e. non-linear classifiers…
- Outline of machine learning The following outline is provided as an overview of, and topical guide to, machine learning: Machine learning (ML) is a subfield of artificial intelligence…
- Radial basis function kernel In machine learning, the radial basis function kernel, or RBF kernel, is a popular kernel function used in various kernelized learning algorithms. In particular…
- Kernel methods for vector output Kernel methods are a well-established tool to analyze the relationship between input data and the corresponding output of a function. Kernels encapsulate…