Sparse Bayesian learning and the relevance vector machine
about
CAMUR: Knowledge extraction from RNA-seq cancer data through equivalent classification rules.Fusing heterogeneous data for the calibration of molecular dynamics force fields using hierarchical Bayesian models.More Is Better: Recent Progress in Multi-Omics Data Integration MethodsKnowledge-based identification of sleep stages based on two forehead electroencephalogram channelsBayesian symmetrical EEG/fMRI fusion with spatially adaptive priors.EEGLAB, SIFT, NFT, BCILAB, and ERICA: new tools for advanced EEG processingRevisiting Warfarin Dosing Using Machine Learning Techniques.Prognostics of Lithium-Ion Batteries Based on Wavelet Denoising and DE-RVMEstimation of Response Functions Based on Variational Bayes Algorithm in Dynamic Images Sequences.Detecting differential growth of microbial populations with Gaussian process regression.Augmenting multi-instance multilabel learning with sparse bayesian models for skin biopsy image analysis.Premature Brain Aging in Baboons Resulting from Moderate Fetal Undernutrition.Scanpath modeling and classification with hidden Markov models.Indefinite Proximity Learning: A Review.Using neuroimaging to help predict the onset of psychosis.Distinct Frontoparietal Networks Underlying Attentional Effort and Cognitive Control.Bayesian semiparametric predictive modeling with applications in dose-response prediction.Integrated Analysis of EEG and fMRI Using Sparsity of Spatial Maps.Imaging the distribution of transient viscosity after the 2016 Mw 7.1 Kumamoto earthquake.Pattern Analysis in Neuroimaging: Beyond Two-Class Categorization.Using the Relevance Vector Machine Model Combined with Local Phase Quantization to Predict Protein-Protein Interactions from Protein Sequences.Diverse coordinate frames on sensorimotor areas in visuomotor transformation.Arbitrary norm support vector machines.Prototype classification: insights from machine learning.Classification of faces in man and machine.Sparse coding via thresholding and local competition in neural circuits.Maximum likelihood estimation of a stochastic integrate-and-fire neural encoding model.Modular encoding and decoding models derived from bayesian canonical correlation analysis.Efficient learning and feature selection in high-dimensional regression.Feature scaling for kernel fisher discriminant analysis using leave-one-out cross validation.Regularized variational Bayesian learning of echo state networks with delay&sum readout.Validation-based sparse Gaussian process classifier design.Fast generalized cross-validation algorithm for sparse model learning.Optimal reduced-set vectors for support vector machines with a quadratic kernel.Relevance Vector Machines for Enhanced BER Probability in DMT-Based SystemsInterpolation in Time Series: An Introductive Overview of Existing Methods, Their Performance Criteria and Uncertainty AssessmentMid-Infrared Spectroscopy for Coffee Variety Identification: Comparison of Pattern Recognition MethodsPredictive downscaling based on non-homogeneous hidden Markov modelsTradares: A Tool for the Automatic Evaluation of Human Translation Quality within An MOOC EnvironmentA Review of Human Activity Recognition Methods
P2860
Q31014129-19B77C2A-1F22-4993-BF76-EDA7688AF813Q31152505-D3BC03C7-8E4C-4D89-9D5D-509F667B1B17Q33804425-831FC165-D3C9-4FA9-9C01-31E704EC97DBQ34133110-F2FC5674-497B-48BB-9CFB-2AD1FDF28CB7Q34567559-2a71363a-40f5-424d-6f89-062b241467e0Q35043505-F9774555-65D9-4585-9228-599670BDB3B9Q35753465-10269DF4-5D5F-424F-8244-D6FEEA1012A7Q36054789-2CBAC375-7B4B-4795-A3AB-3653155EBA4FQ37224761-838E9E7E-37F9-4401-9E14-2111678C69C4Q37619116-B58E327F-5BC7-4055-88D0-3EEBC56AD6C6Q37720296-E5976892-0D35-44E4-BC3B-CC2356C0856CQ37746821-A74B7BD2-EB58-4BE2-B773-D78A64D8A168Q38378077-49ec3802-48e5-a4f5-14ce-76bbeeb840d3Q38575045-9A3A53A5-D59E-4249-8B2B-C6D966DAA537Q38796768-4c27a5ff-4aa3-ce56-e505-1a0985b9aa19Q38933355-11DD01DC-FFC4-414B-82A0-600ADA46EC34Q39236432-8AAD5B84-3A65-4BD2-88BB-6116F25BAA70Q39557771-9D98A293-DC86-4A1D-B56D-66DB974DEABAQ41931939-5B154BBD-E7F7-4CD7-B35D-1834931E2DE0Q42232619-DE4B437E-B735-45FD-B541-6559B1AC78ECQ42741127-1525456E-840D-46F4-A908-4A975FCDAC5FQ44225841-03660F8F-763F-4708-AF2F-FC190E3301A2Q44346351-16D36671-EFD2-418C-B7B4-EDC6084D9244Q44715373-A1B699DB-1BAB-4ADB-ADAC-F4B1C5E03EA2Q45966177-75AC4BD7-5177-4C56-9E96-7F5968AE2D06Q47748197-67F2E864-7CA0-4A6D-9B51-A82B5E57F27EQ47866601-B62EA16F-E73C-46AF-AD03-4A8B2EAF6674Q48199659-1C35F77E-6213-47A7-8BB1-33DA3B1DB81DQ48371649-943A87E3-8811-4390-AD6F-FDE913AC5910Q48456413-3C58B3A1-525A-471B-A6FB-D698CA2E1E23Q50978335-F71E4C5A-4598-4A02-A7E3-F06E162FE333Q51848269-B89D40A2-CDE3-4F79-87C2-E9B48CF6373CQ51927891-7AF9A5AF-C698-44EB-BAA6-16F6EEB2A98BQ51992633-4AA2A4F2-014D-4927-9A4C-CE26A09EE3AAQ57088621-68F12390-80EB-4558-A680-D388C2DC5675Q57521391-6F6B277B-EAB8-4678-B4E0-197DEC00DC14Q57554384-1E572E07-F29C-4DE4-9204-9092374CCAA4Q58091763-B8D90532-1CE4-431C-A485-C16431017EF8Q58292618-7EDABDBD-4E2E-4756-B48D-DA8B91BA3432Q58643632-B41F91A1-725D-41E2-BBAD-118DD9768541
P2860
Sparse Bayesian learning and the relevance vector machine
description
im Januar 2000 veröffentlichter wissenschaftlicher Artikel
@de
wetenschappelijk artikel
@nl
наукова стаття, опублікована у 2000
@uk
name
10.1162/15324430152748236
@nl
Sparse Bayesian learning and the relevance vector machine
@en
type
label
10.1162/15324430152748236
@nl
Sparse Bayesian learning and the relevance vector machine
@en
prefLabel
10.1162/15324430152748236
@nl
Sparse Bayesian learning and the relevance vector machine
@en
P1476
Sparse Bayesian learning and the relevance vector machine
@en
P2093
Michael E. Tipping
P304
P407
P577
2000-01-01T00:00:00Z