Semi-supervised_learningAprendizaje_semisupervisado%DB%8C%D8%A7%D8%AF%DA%AF%DB%8C%D8%B1%DB%8C_%D9%86%DB%8C%D9%85%D9%87%E2%80%8C%D9%86%D8%B8%D8%A7%D8%B1%D8%AA%DB%8CApprentissage_semi-supervis%C3%A9%EC%A4%80_%EC%A7%80%EB%8F%84_%ED%95%99%EC%8A%B5%D0%9E%D0%B1%D1%83%D1%87%D0%B5%D0%BD%D0%B8%D0%B5_%D1%81_%D1%87%D0%B0%D1%81%D1%82%D0%B8%D1%87%D0%BD%D1%8B%D0%BC_%D0%BF%D1%80%D0%B8%D0%B2%D0%BB%D0%B5%D1%87%D0%B5%D0%BD%D0%B8%D0%B5%D0%BC_%D1%83%D1%87%D0%B8%D1%82%D0%B5%D0%BB%D1%8F%D0%9D%D0%B0%D0%BF%D1%96%D0%B2%D0%B0%D0%B2%D1%82%D0%BE%D0%BC%D0%B0%D1%82%D0%B8%D1%87%D0%BD%D0%B5_%D0%BD%D0%B0%D0%B2%D1%87%D0%B0%D0%BD%D0%BD%D1%8FH%E1%BB%8Dc_n%E1%BB%ADa_gi%C3%A1m_s%C3%A1tQ1041418
about
Semi-supervised cluster analysis of imaging dataSemi-supervised methods to predict patient survival from gene expression dataSemi-supervised dependency parsing using generalized tri-trainingPrediction of disease-related interactions between microRNAs and environmental factors based on a semi-supervised classifierA semi-supervised method for drug-target interaction prediction with consistency in networksA Semi-Supervised Approach for Refining Transcriptional Signatures of Drug Response and Repositioning PredictionsNLLSS: Predicting Synergistic Drug Combinations Based on Semi-supervised LearningSemi-supervised Convolutional Neural Networks for Text Categorization via Region EmbeddingSemi-supervised learning for potential human microRNA-disease associations inferenceDenoising by semi-supervised kernel PCA preimagingEfficient Non-Parametric Function Induction in Semi-Supervised LearningSemi-supervised learning with deep generative modelsSemi-Supervised Generation with Cluster-aware Generative ModelsSemi-Supervised Classification with Graph Convolutional NetworksA semi-supervised Support Vector Machine model for predicting the language outcomes following cochlear implantation based on pre-implant brain fMRI imaging.Semi-supervised learning of the electronic health record for phenotype stratification.A semi-supervised method for predicting transcription factor-gene interactions in Escherichia coli.A semi-supervised approach to projected clustering with applications to microarray data.Simultaneous inference of biological networks of multiple species from genome-wide data and evolutionary information: a semi-supervised approach.Determining effects of non-synonymous SNPs on protein-protein interactions using supervised and semi-supervised learning.Identifying nuclear phenotypes using semi-supervised metric learningONLINE THREE-DIMENSIONAL DENDRITIC SPINES MOPHOLOGICAL CLASSIFICATION BASED ON SEMI-SUPERVISED LEARNINGA semi-supervised tensor regression model for siRNA efficacy prediction.Active semi-supervised learning method with hybrid deep belief networks.Bioimaging-based detection of mislocalized proteins in human cancers by semi-supervised learning.Active semi-supervised community detection based on must-link and cannot-link constraintsModeling electroencephalography waveforms with semi-supervised deep belief nets: fast classification and anomaly measurement.Semi-supervised Learning for the BioNLP Gene Regulation Network.Semi-Supervised Fuzzy Clustering with Feature Discrimination.Target localization in wireless sensor networks using online semi-supervised support vector regression.A semi-supervised method for predicting cancer survival using incomplete clinical data.A novel semi-supervised algorithm for the taxonomic assignment of metagenomic readsLocally Embedding Autoencoders: A Semi-Supervised Manifold Learning Approach of Document RepresentationCancer survival analysis using semi-supervised learning method based on Cox and AFT models with L1/2 regularizationFRaC: a feature-modeling approach for semi-supervised and unsupervised anomaly detectionSemi-Supervised Feature Transformation for Tissue Image ClassificationSemi-Supervised Sparse Representation Based Classification for Face Recognition With Insufficient Labeled Samples.Graph-based semi-supervised learning with genomic data integration using condition-responsive genes applied to phenotype classification.SimNest: Social Media Nested Epidemic Simulation via Online Semi-supervised Deep Learning.Semi-supervised multimodal relevance vector regression improves cognitive performance estimation from imaging and biological biomarkers.
P921
Q24623229-576ae65f-4799-9b65-bee6-10d6c35aa9f3Q24804682-3f63f2b5-4047-5ed2-6ed4-a6bbb5cc4a13Q28458123-d3d74a2e-4399-6e09-6ff2-1dfa8fa9263bQ28482644-4514eb83-4304-a366-3ddf-c1d7ddef322fQ28487735-62f07c92-44d1-ab6d-3d40-f64effe6f9fdQ28550159-1d8a0d47-4d6f-1801-e521-429c2d1f0495Q28552626-1cecee39-4c63-df13-b689-35fecdcb9723Q28604262-0c4edc39-4295-05ed-f3d8-43bd4a511f19Q28656510-3fd09a15-4fe9-7168-237a-bcf6058f405bQ28824039-88a942ac-4d20-fe47-0262-df733d264965Q29017669-a81a6965-4b81-66c2-aa63-3380eb05de2aQ29022461-465d6a57-4368-86bb-c470-ab944d4a9ebaQ29182663-4b35f28c-46e6-3edd-d0af-0d8c39eb240eQ30278192-7e564361-4332-aa61-89da-2b6cd9f33d25Q30393241-302b9bfb-4faa-2d74-2f67-6974a2ee3de0Q30490181-7dea9c39-4762-3f7e-b349-7c3dff8837efQ33325896-5ec1f176-4b8f-1654-ac41-0b9af765683fQ33485321-62491954-4bf9-2cc5-81fd-9d8ab57ce9d2Q33494777-7ae4a843-4560-0149-096c-6acaac53d162Q33552939-683d4200-48ec-f7ca-9233-501b389a7571Q34849923-5b286a86-4102-4da4-f84a-1133d67563daQ35209229-e8aca23a-449b-5723-dd2d-1d3175501d96Q35233194-4a35915b-448a-0a09-f677-ce5485c9f7fcQ35246077-08bb53c8-4e03-aed4-085c-de714214273aQ35246345-013d86f6-4940-2af1-b21f-4277e015b4d6Q35348845-722d9a5c-4f04-b2af-b8a2-1aedfe6ff142Q35354788-a60eda6f-4403-b93c-0cf0-f004e8c85990Q35707362-a5a434d1-4b2d-39be-81c6-9eeb2d05684dQ35760875-848c962d-419f-b98c-a1ec-7a14645442baQ35866782-332d9cd6-41c9-700c-98cd-81b0acfff033Q35886943-617bf004-4b93-6a92-2c0b-45409ffed26aQ35887793-ea7d2a24-4994-3365-30cd-5c4e75c961cdQ35897661-27528372-43dc-f8e9-ee7a-302ffa370803Q35942318-1798adc1-45df-b638-ca63-63d3d6cbc386Q35983953-12678cf7-4cb8-e9c6-d44a-7feb3adcad0cQ36211850-a0687e04-41c9-749d-8ad8-c1365788c659Q36329811-b6e13c90-4ca1-713a-9b3e-ec3229eb5101Q36372190-5f2ca4bb-41b5-d923-2b02-76da4890fefcQ37113875-1c050cc7-49d4-1b7e-6489-985e3e71c861Q37137520-20db2fd8-43e8-89b8-1efc-c649ff9c93c8
P921
description
clase de técnicas de aprendizaje automático que utiliza datos de entrenamiento
@es
class of machine learning techniques
@en
classe de técnicas de aprendizagem de máquina
@pt
name
Học nửa giám sát
@vi
apprendimento semi-supervisionato
@it
apprentissage semi-supervisé
@fr
aprendizagem semi-supervisionada
@pt
aprendizaje semisupervisado
@es
duonsuperrigardata lernado
@eo
semi-supervised learning
@en
semi-superviseret læring
@da
Напівавтоматичне навчання
@uk
Обучение с частичным привлечением учителя
@ru
type
label
Học nửa giám sát
@vi
apprendimento semi-supervisionato
@it
apprentissage semi-supervisé
@fr
aprendizagem semi-supervisionada
@pt
aprendizaje semisupervisado
@es
duonsuperrigardata lernado
@eo
semi-supervised learning
@en
semi-superviseret læring
@da
Напівавтоматичне навчання
@uk
Обучение с частичным привлечением учителя
@ru
altLabel
aprendizaje semi supervisado
@es
aprendizaje semi-supervisado
@es
semisupervised learning
@en
半监督学习
@zh
半监督式学习
@zh
半监督式学习
@zh-cn
半监督式学习
@zh-hans
半監督式學習
@zh-hant
반 교사 학습
@ko
prefLabel
Học nửa giám sát
@vi
apprendimento semi-supervisionato
@it
apprentissage semi-supervisé
@fr
aprendizagem semi-supervisionada
@pt
aprendizaje semisupervisado
@es
duonsuperrigardata lernado
@eo
semi-supervised learning
@en
semi-superviseret læring
@da
Напівавтоматичне навчання
@uk
Обучение с частичным привлечением учителя
@ru
P6366
P646
P2179
P279
P3417
Semi-supervised-Learning