MULTI-VIEW LEARNING

49 papers with code • 0 benchmarks • 1 datasets

Multi-View Learning is a machine learning framework where data are represented by multiple distinct feature groups, and each feature group is referred to as a particular view.

Source: Dissimilarity-based representation for radiomics applications

Libraries

Use these libraries to find MULTI-VIEW LEARNING models and implementations

Datasets


Reliable Conflictive Multi-View Learning

jiajunsi/rcml 24 Feb 2024

To solve this, we point out a new Reliable Conflictive Multi-view Learning (RCML) problem, which requires the model to provide decision results and attached reliabilities for conflictive multi-view data.

40
24 Feb 2024

Unconstrained Stochastic CCA: Unifying Multiview and Self-Supervised Learning

jameschapman19/ssl-ey 2 Oct 2023

The Canonical Correlation Analysis (CCA) family of methods is foundational in multiview learning.

1
02 Oct 2023

Explainable Multi-View Deep Networks Methodology for Experimental Physics

scientific-computing-lab-nrcn/multi-view-explainability 16 Aug 2023

In this paper, we suggest different multi-view architectures for the vision domain, each suited to another problem, and we also present a methodology for explaining these models.

6
16 Aug 2023

A Comparative Assessment of Multi-view fusion learning for Crop Classification

fmenat/multiviewcropclassification 10 Aug 2023

Instead, we present a comparison of multi-view fusion methods for three different datasets and show that, depending on the test region, different methods obtain the best performance.

12
10 Aug 2023

Multi-View Fusion and Distillation for Subgrade Distresses Detection based on 3D-GPR

zhouchunpong/multi-view-3DGPR 9 Aug 2023

To address these challenges, we introduce a novel methodology for the subgrade distress detection task by leveraging the multi-view information from 3D-GPR data.

3
09 Aug 2023

Semantic Invariant Multi-view Clustering with Fully Incomplete Information

PengxinZeng/2023-TPAMI-SMILE 22 May 2023

To address this problem, we present a novel framework called SeMantic Invariance LEarning (SMILE) for multi-view clustering with incomplete information that does not require any paired samples.

1
22 May 2023

Dual Contrastive Prediction for Incomplete Multi-view Representation Learning

XLearning-SCU/2022-TPAMI-DCP IEEE Transactions on Pattern Analysis and Machine Intelligence 2023

In this article, we propose a unified framework to solve the following two challenging problems in incomplete multi-view representation learning: i) how to learn a consistent representation unifying different views, and ii) how to recover the missing views.

34
01 Apr 2023

Siamese DETR

zx55/siamesedetr CVPR 2023

In this work, we present Siamese DETR, a Siamese self-supervised pretraining approach for the Transformer architecture in DETR.

32
31 Mar 2023

Deep Double Incomplete Multi-view Multi-label Learning with Incomplete Labels and Missing Views

justsmart/DIMC-mindspore IEEE Transactions on Neural Networks and Learning Systems 2023

View missing and label missing are two challenging problems in the applications of multi-view multi-label classification scenery.

4
23 Mar 2023

ConsRec: Learning Consensus Behind Interactions for Group Recommendation

fdudsde/www2023consrec 7 Feb 2023

Since group activities have become very common in daily life, there is an urgent demand for generating recommendations for a group of users, referred to as group recommendation task.

15
07 Feb 2023