MULTI-VIEW LEARNING

25 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

Datasets


Greatest papers with code

Neural News Recommendation with Attentive Multi-View Learning

microsoft/recommenders 12 Jul 2019

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

Trusted Multi-View Classification

hanmenghan/CPM_Nets ICLR 2021

To this end, we propose a novel multi-view classification method, termed trusted multi-view classification, which provides a new paradigm for multi-view learning by dynamically integrating different views at an evidence level.

Classification General Classification +1

CPM-Nets: Cross Partial Multi-View Networks

hanmenghan/CPM_Nets NeurIPS 2019

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

Deep Tensor CCA for Multi-view Learning

jameschapman19/cca_zoo 25 May 2020

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

jameschapman19/cca_zoo 9 Feb 2015

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 Dual Retrieval Module for Semi-supervised Relation Extraction

INK-USC/DualRE 20 Feb 2019

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

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

wrlife/RNN_depth_pose 15 Apr 2019

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

Depth Estimation MULTI-VIEW LEARNING +1

COMPLETER: Incomplete Multi-view Clustering via Contrastive Prediction

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

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.

Clustering Incomplete multi-view clustering +1

Learning Autoencoders with Relational Regularization

HongtengXu/Relational-AutoEncoders ICML 2020

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

MULTI-VIEW LEARNING