ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1703.06683
  4. Cited By
A Systematic Study of Online Class Imbalance Learning with Concept Drift

A Systematic Study of Online Class Imbalance Learning with Concept Drift

20 March 2017
Shuo Wang
Leandro L. Minku
Xin Yao
ArXiv (abs)PDFHTML

Papers citing "A Systematic Study of Online Class Imbalance Learning with Concept Drift"

21 / 21 papers shown
Title
SiameseDuo++: Active Learning from Data Streams with Dual Augmented Siamese Networks
SiameseDuo++: Active Learning from Data Streams with Dual Augmented Siamese Networks
Kleanthis Malialis
S. Filippou
C. Panayiotou
Marios M. Polycarpou
AI4TS
63
0
0
06 Apr 2025
Employing Two-Dimensional Word Embedding for Difficult Tabular Data
  Stream Classification
Employing Two-Dimensional Word Embedding for Difficult Tabular Data Stream Classification
P. Zyblewski
47
1
0
24 Apr 2024
Imbalanced Data Stream Classification using Dynamic Ensemble Selection
P. S
H. S
V. R
12
0
0
17 Sep 2023
Autoencoder-based Anomaly Detection in Streaming Data with Incremental
  Learning and Concept Drift Adaptation
Autoencoder-based Anomaly Detection in Streaming Data with Incremental Learning and Concept Drift Adaptation
Jin Li
Kleanthis Malialis
Marios M. Polycarpou
50
11
0
15 May 2023
Machine Learning for QoS Prediction in Vehicular Communication:
  Challenges and Solution Approaches
Machine Learning for QoS Prediction in Vehicular Communication: Challenges and Solution Approaches
Alexandros Palaios
Christian L. Vielhaus
D. Külzer
Cara Watermann
Rodrigo Hernangómez
...
Martin Kasparick
G. Fettweis
F. Fitzek
Hans D. Schotten
Sławomir Stańczak
59
13
0
23 Feb 2023
Cold Start Streaming Learning for Deep Networks
Cold Start Streaming Learning for Deep Networks
Cameron R. Wolfe
Anastasios Kyrillidis
CLL
55
2
0
09 Nov 2022
Data augmentation on-the-fly and active learning in data stream
  classification
Data augmentation on-the-fly and active learning in data stream classification
Kleanthis Malialis
Dimitris Papatheodoulou
S. Filippou
C. Panayiotou
Marios M. Polycarpou
50
8
0
13 Oct 2022
Nonstationary data stream classification with online active learning and
  siamese neural networks
Nonstationary data stream classification with online active learning and siamese neural networks
Kleanthis Malialis
C. Panayiotou
Marios M. Polycarpou
57
31
0
03 Oct 2022
A survey on learning from imbalanced data streams: taxonomy, challenges,
  empirical study, and reproducible experimental framework
A survey on learning from imbalanced data streams: taxonomy, challenges, empirical study, and reproducible experimental framework
Gabriel J. Aguiar
Bartosz Krawczyk
Alberto Cano
AI4TS
101
99
0
07 Apr 2022
From Concept Drift to Model Degradation: An Overview on
  Performance-Aware Drift Detectors
From Concept Drift to Model Degradation: An Overview on Performance-Aware Drift Detectors
Firas Bayram
Bestoun S. Ahmed
A. Kassler
65
225
0
21 Mar 2022
Concept Drift Detection from Multi-Class Imbalanced Data Streams
Concept Drift Detection from Multi-Class Imbalanced Data Streams
Lukasz Korycki
Bartosz Krawczyk
45
41
0
20 Apr 2021
Tackling Virtual and Real Concept Drifts: An Adaptive Gaussian Mixture
  Model
Tackling Virtual and Real Concept Drifts: An Adaptive Gaussian Mixture Model
Gustavo H. F. M. Oliveira
Leandro L. Minku
Adriano Oliveira
75
35
0
11 Feb 2021
Key Technology Considerations in Developing and Deploying Machine
  Learning Models in Clinical Radiology Practice
Key Technology Considerations in Developing and Deploying Machine Learning Models in Clinical Radiology Practice
V. Kulkarni
M. Gawali
A. Kharat
VLM
113
21
0
03 Feb 2021
Data-efficient Online Classification with Siamese Networks and Active
  Learning
Data-efficient Online Classification with Siamese Networks and Active Learning
Kleanthis Malialis
C. Panayiotou
Marios M. Polycarpou
37
14
0
04 Oct 2020
Challenges in Benchmarking Stream Learning Algorithms with Real-world
  Data
Challenges in Benchmarking Stream Learning Algorithms with Real-world Data
Vinicius M. A. Souza
Denis Moreira dos Reis
André Gustavo Maletzke
Gustavo E. A. P. A. Batista
OODAI4TS
72
132
0
30 Apr 2020
Concept Drift Detection via Equal Intensity k-means Space Partitioning
Concept Drift Detection via Equal Intensity k-means Space Partitioning
Anjin Liu
Jie Lu
Guangquan Zhang
85
66
0
24 Apr 2020
Diverse Instances-Weighting Ensemble based on Region Drift Disagreement
  for Concept Drift Adaptation
Diverse Instances-Weighting Ensemble based on Region Drift Disagreement for Concept Drift Adaptation
Anjin Liu
Jie Lu
Guangquan Zhang
43
49
0
13 Apr 2020
Spiking Neural Networks and Online Learning: An Overview and
  Perspectives
Spiking Neural Networks and Online Learning: An Overview and Perspectives
J. Lobo
Javier Del Ser
Albert Bifet
N. Kasabov
83
227
0
23 Jul 2019
Online Anomaly Detection with Sparse Gaussian Processes
Online Anomaly Detection with Sparse Gaussian Processes
Jingjing Fei
Shiliang Sun
AI4TS
44
21
0
14 May 2019
Queue-based Resampling for Online Class Imbalance Learning
Queue-based Resampling for Online Class Imbalance Learning
Kleanthis Malialis
C. Panayiotou
Marios M. Polycarpou
OnRL
45
12
0
27 Sep 2018
Concept Drift Detection and Adaptation with Hierarchical Hypothesis
  Testing
Concept Drift Detection and Adaptation with Hierarchical Hypothesis Testing
Shujian Yu
Zubin Abraham
Heng Wang
Mohak Shah
Yantao Wei
José C. Príncipe
72
53
0
25 Jul 2017
1