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Scaling Up Generalized Kernel Methods.

Kernel Approximation Methods for Speech Recognition

Predicting Reaction Yields via Supervised Learning.

Random Features for Kernel Approximation: A Survey in Algorithms, Theory, and Beyond

Evolutionary Overview and Prediction of Themes in the Field of Land Degradation

Parameter extraction with reservoir computing: Nonlinear time series analysis and application to industrial maintenance.

Oscillons, walking droplets, and skipping stones (an overview)

Graph-Adaptive Incremental Learning Using an Ensemble of Gaussian Process Experts

Amoebic Foraging Model of Metastatic Cancer Cells

Myths and mechanisms: RecBCD and Chi hotspots as determinants of self vs. non-self

Random Features Strengthen Graph Neural Networks

Online Unsupervised Learning Using Ensemble Gaussian Processes with Random Features

ANID-SEoKELM: Adaptive network intrusion detection based on selective ensemble of kernel ELMs with random features

Investigation of Event-Based Surfaces for High-Speed Detection, Unsupervised Feature Extraction, and Object Recognition

Quadruply Stochastic Gradients for Large Scale Nonlinear Semi-Supervised AUC Optimization

Subjective-Probability Approach to Design an Expert System for Assessment of States of complex Systems in Conditions of Non-Regular Destructive Influences

Fault Diagnosis of Railway Turnout Based on Random Forests

Random Features and Random Neurons for Brain-Inspired Big Data Analytics

MRC4: A Modified RC4 Algorithm Using Symmetric Random Function Generator for Improved Cryptographic Features

Variational and Hierarchical Recurrent Autoencoder

Scalable Semi-Supervised SVM via Triply Stochastic Gradients

Extreme Learning Machine-Based Heterogeneous Domain Adaptation for Classification of Hyperspectral Images

An adaptive dynamically low-dimensional approximation method for multiscale stochastic diffusion equations

A Random Features-Based Method for Interpolating Digital Terrain Models with High Efficiency

The Photovoltaic Output Prediction Based on Variational Mode Decomposition and Maximum Relevance Minimum Redundancy

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