A survey on active learning: State-of-the-art, practical challenges and research directions

A Tharwat, W Schenck - Mathematics, 2023‏ - mdpi.com
Despite the availability and ease of collecting a large amount of free, unlabeled data, the
expensive and time-consuming labeling process is still an obstacle to labeling a sufficient …

[HTML][HTML] A survey on machine learning for recurring concept drifting data streams

AL Suárez-Cetrulo, D Quintana, A Cervantes - Expert Systems with …, 2023‏ - Elsevier
The problem of concept drift has gained a lot of attention in recent years. This aspect is key
in many domains exhibiting non-stationary as well as cyclic patterns and structural breaks …

Fuzzy neural networks and neuro-fuzzy networks: A review the main techniques and applications used in the literature

PV de Campos Souza - Applied soft computing, 2020‏ - Elsevier
This paper presents a review of the central theories involved in hybrid models based on
fuzzy systems and artificial neural networks, mainly focused on supervised methods for …

[HTML][HTML] Unsupervised real-time anomaly detection for streaming data

S Ahmad, A Lavin, S Purdy, Z Agha - Neurocomputing, 2017‏ - Elsevier
We are seeing an enormous increase in the availability of streaming, time-series data.
Largely driven by the rise of connected real-time data sources, this data presents technical …

Evolving fuzzy and neuro-fuzzy approaches in clustering, regression, identification, and classification: A survey

I Škrjanc, JA Iglesias, A Sanchis, D Leite, E Lughofer… - Information …, 2019‏ - Elsevier
Major assumptions in computational intelligence and machine learning consist of the
availability of a historical dataset for model development, and that the resulting model will, to …

Recent advances in neuro-fuzzy system: A survey

KV Shihabudheen, GN Pillai - Knowledge-Based Systems, 2018‏ - Elsevier
Neuro-fuzzy systems have attracted the growing interest of researchers in various scientific
and engineering areas due to its effective learning and reasoning capabilities. The neuro …

Meta-ADD: A meta-learning based pre-trained model for concept drift active detection

H Yu, Q Zhang, T Liu, J Lu, Y Wen, G Zhang - Information Sciences, 2022‏ - Elsevier
Abstract Concept drift is a phenomenon that commonly happened in data streams and need
to be detected, because it means the statistical properties of a target variable, which the …

Action recognition based on joint trajectory maps with convolutional neural networks

P Wang, W Li, C Li, Y Hou - Knowledge-Based Systems, 2018‏ - Elsevier
Abstract Convolutional Neural Networks (ConvNets) have recently shown promising
performance in many computer vision tasks, especially image-based recognition. How to …

A large-scale comparison of concept drift detectors

RSM Barros, SGTC Santos - Information Sciences, 2018‏ - Elsevier
Online learning involves extracting information from large quantities of data (streams)
usually affected by changes in the distribution (concept drift). A drift detector is a small …

Smart grid load forecasting using online support vector regression

P Vrablecová, AB Ezzeddine, V Rozinajová… - Computers & Electrical …, 2018‏ - Elsevier
Smart grid, an integral part of a smart city, provides new opportunities for efficient energy
management, possibly leading to big cost savings and a great contribution to the …