About

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

Benchmarks

You can find evaluation results in the subtasks. You can also submitting evaluation metrics for this task.

Subtasks

Datasets

Greatest papers with code

Neural News Recommendation with Attentive Multi-View Learning

12 Jul 2019microsoft/recommenders

In the user encoder we learn the representations of users based on their browsed news and apply attention mechanism to select informative news for user representation learning.

MULTI-VIEW LEARNING REPRESENTATION LEARNING

CPM-Nets: Cross Partial Multi-View Networks

NeurIPS 2019 hanmenghan/CPM_Nets

Despite multi-view learning progressed fast in past decades, it is still challenging due to the difficulty in modeling complex correlation among different views, especially under the context of view missing.

MULTI-VIEW LEARNING

Recurrent Neural Network for (Un-)supervised Learning of Monocular VideoVisual Odometry and Depth

15 Apr 2019wrlife/RNN_depth_pose

Deep learning-based, single-view depth estimation methods have recently shown highly promising results.

DEPTH ESTIMATION MULTI-VIEW LEARNING VISUAL ODOMETRY

Learning Dual Retrieval Module for Semi-supervised Relation Extraction

20 Feb 2019INK-USC/DualRE

In this paper, we leverage a key insight that retrieving sentences expressing a relation is a dual task of predicting relation label for a given sentence---two tasks are complementary to each other and can be optimized jointly for mutual enhancement.

MULTI-VIEW LEARNING RELATION EXTRACTION

Deep Tensor CCA for Multi-view Learning

25 May 2020jameschapman19/cca_zoo

We present Deep Tensor Canonical Correlation Analysis (DTCCA), a method to learn complex nonlinear transformations of multiple views (more than two) of data such that the resulting representations are linearly correlated in high order.

MULTI-VIEW LEARNING TENSOR DECOMPOSITION

Tensor Canonical Correlation Analysis for Multi-view Dimension Reduction

9 Feb 2015jameschapman19/cca_zoo

As a consequence, the high order correlation information contained in the different views is explored and thus a more reliable common subspace shared by all features can be obtained.

DIMENSIONALITY REDUCTION MULTI-VIEW LEARNING

Learning Autoencoders with Relational Regularization

ICML 2020 HongtengXu/Relational-AutoEncoders

A new algorithmic framework is proposed for learning autoencoders of data distributions.

MULTI-VIEW LEARNING

COMPLETER: Incomplete Multi-view Clustering via Contrastive Prediction

22 Mar 2021XLearning-SCU/2021-CVPR-Completer

In this paper, we study two challenging problems in incomplete multi-view clustering analysis, namely, i) how to learn an informative and consistent representation among different views without the help of labels and ii) how to recover the missing views from data.

INCOMPLETE MULTI-VIEW CLUSTERING UNSUPERVISED REPRESENTATION LEARNING

Dual Adversarial Domain Adaptation

1 Jan 2020yaoyueduzhen/DADA

Recent experiments have shown that when the discriminator is provided with domain information in both domains and label information in the source domain, it is able to preserve the complex multimodal information and high semantic information in both domains.

MULTI-VIEW LEARNING UNSUPERVISED DOMAIN ADAPTATION