Papers Multiview Learning
“Multiview Learning” 태그가 달린 논문 41편 · 필터 해제
Hierarchical Consensus Network for Multiview Feature Learning
Multiview feature learning aims to learn discriminative features by integrating the distinct information in each view. However, most existing methods still face significant challenges in learning view-consistency feature…
Contrastive LearningMultiview LearningTowards the Generalization of Multi-view Learning: An Information-theoretical Analysis
Multiview learning has drawn widespread attention for its efficacy in leveraging cross-view consensus and complementarity information to achieve a comprehensive representation of data. While multi-view learning has under…
Generalization BoundsMultiview LearningMULTI-VIEW LEARNINGGRVFL-MV: Graph Random Vector Functional Link Based on Multi-View Learning
The classification performance of the random vector functional link (RVFL), a randomized neural network, has been widely acknowledged. However, due to its shallow learning nature, RVFL often fails to consider all the rel…
Graph EmbeddingMultiview LearningMULTI-VIEW LEARNINGMultiview Random Vector Functional Link Network for Predicting DNA-Binding Proteins
The identification of DNA-binding proteins (DBPs) is a critical task due to their significant impact on various biological activities. Understanding the mechanisms underlying protein-DNA interactions is essential for elu…
Multiview LearningEnhancing Multiview Synergy: Robust Learning by Exploiting the Wave Loss Function with Consensus and Complementarity Principles
Multiview learning (MvL) is an advancing domain in machine learning, leveraging multiple data perspectives to enhance model performance through view-consistency and view-discrepancy. Despite numerous successful multiview…
Multiview LearningMultiview learning with twin parametric margin SVM
Multiview learning (MVL) seeks to leverage the benefits of diverse perspectives to complement each other, effectively extracting and utilizing the latent information within the dataset. Several twin support vector machin…
Computational EfficiencyMultiview LearningStructure-Aware Consensus Network on Graphs with Few Labeled Nodes
Graph node classification with few labeled nodes presents significant challenges due to limited supervision. Conventional methods often exploit the graph in a transductive learning manner. They fail to effectively utiliz…
Graph Neural NetworkMultiview LearningNode ClassificationTransductive LearningBayesian Joint Additive Factor Models for Multiview Learning
It is increasingly common in a wide variety of applied settings to collect data of multiple different types on the same set of samples. Our particular focus in this article is on studying relationships between such multi…
Multiview LearningUncertainty QuantificationmvlearnR and Shiny App for multiview learning
The package mvlearnR and accompanying Shiny App is intended for integrating data from multiple sources or views or modalities (e.g. genomics, proteomics, clinical and demographic data). Most existing software packages fo…
Data IntegrationMultiview LearningAugmentation is AUtO-Net: Augmentation-Driven Contrastive Multiview Learning for Medical Image Segmentation
The utilisation of deep learning segmentation algorithms that learn complex organs and tissue patterns and extract essential regions of interest from the noisy background to improve the visual ability for medical image d…
GPUImage SegmentationMedical Image SegmentationMultiview Learning+2Unconstrained Stochastic CCA: Unifying Multiview and Self-Supervised Learning
The Canonical Correlation Analysis (CCA) family of methods is foundational in multiview learning. Regularised linear CCA methods can be seen to generalise Partial Least Squares (PLS) and be unified with a Generalized Eig…
Multiview LearningMULTI-VIEW LEARNINGSelf-Supervised LearningLearning from Semantic Alignment between Unpaired Multiviews for Egocentric Video Recognition
We are concerned with a challenging scenario in unpaired multiview video learning. In this case, the model aims to learn comprehensive multiview representations while the cross-view semantic information exhibits variatio…
Multiview LearningVideo RecognitionInterpretable and intervenable ultrasonography-based machine learning models for pediatric appendicitis
Appendicitis is among the most frequent reasons for pediatric abdominal surgeries. Previous decision support systems for appendicitis have focused on clinical, laboratory, scoring, and computed tomography data and have i…
ClassificationInterpretable Machine LearningMultiview LearningInterpretable Deep Learning Methods for Multiview Learning
Technological advances have enabled the generation of unique and complementary types of data or views (e.g. genomics, proteomics, metabolomics) and opened up a new era in multiview learning research with the potential to…
Deep Learningfeature selectionMultiview LearningMulti-View Hypercomplex Learning for Breast Cancer Screening
Traditionally, deep learning methods for breast cancer classification perform a single-view analysis. However, radiologists simultaneously analyze all four views that compose a mammography exam, owing to the correlations…
Breast Tumour ClassificationCancer ClassificationCancer-no cancer per breast classificationClassification+2Stationary Diffusion State Neural Estimation for Multiview Clustering
Although many graph-based clustering methods attempt to model the stationary diffusion state in their objectives, their performance limits to using a predefined graph. We argue that the estimation of the stationary diffu…
ClusteringGraph Neural NetworkMultiview ClusteringMultiview LearningUnderstanding Latent Correlation-Based Multiview Learning and Self-Supervision: An Identifiability Perspective
Multiple views of data, both naturally acquired (e.g., image and audio) and artificially produced (e.g., via adding different noise to data samples), have proven useful in enhancing representation learning. Natural views…
ClusteringDisentanglementMultiview LearningRepresentation Learning+1Assessing the Severity of Health States based on Social Media Posts
The unprecedented growth of Internet users has resulted in an abundance of unstructured information on social media including health forums, where patients request health-related information or opinions from other users.…
Multiview LearningNatural Language UnderstandingActive Ensemble Deep Learning for Polarimetric Synthetic Aperture Radar Image Classification
Although deep learning has achieved great success in image classification tasks, its performance is subject to the quantity and quality of training samples. For classification of polarimetric synthetic aperture radar (Po…
Active LearningClassificationDeep LearningGeneral Classification+4Biconditional Generative Adversarial Networks for Multiview Learning with Missing Views
In this paper, we present a conditional GAN with two generators and a common discriminator for multiview learning problems where observations have two views, but one of them may be missing for some of the training sample…
Machine TranslationMultiview Learning