Semi-supervised multiview embedding for hyperspectral data classification

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Testing for equality of two high-dimensional distributions is a challenging problem, and this becomes even more challenging when the sample size is small. Over the last few decades, several graph-based two-sample tests have been proposed in the literature, ...

Semi-supervised multiview embedding for hyperspectral data classification

Chattez avec Graph Search

A Real-time Synchrophasor Data Compression Method Using Singular Value Decomposition

Spectral Measurement and Classification in the Era of Big Data

Tests of mutual independence among several random vectors using univariate and multivariate ranks of nearest neighbours

Video Prediction Recalling Long-term Motion Context via Memory Alignment Learning

Manifold Learning-Based Polynomial Chaos Expansions For High-Dimensional Surrogate Models

A Stepwise Domain Adaptive Segmentation Network With Covariate Shift Alleviation for Remote Sensing Imagery

A Variational Inference Approach to Learning Multivariate Wold Processes

Common Information Components Analysis

A machine learning approach to portfolio pricing and risk management for high-dimensional problems

Failure and success of the spectral bias prediction for Laplace Kernel Ridge Regression: the case of low-dimensional data

MOSES: A Streaming Algorithm for Linear Dimensionality Reduction

Role of stochastic noise and generalization error in the time propagation of neural-network quantum states

Chemiscope: interactive structure-property explorer for materials and molecules

Oblivious Sketching of High-Degree Polynomial Kernels

Genuinely distributed Byzantine machine learning

Neural Set Function Extensions: Learning with Discrete Functions in High Dimensions

On some graph-based two-sample tests for high dimension, low sample size data