Who Cited It

Ensemble deep learning: A review

2022 · Engineering Applications of Artificial Intelligence · 2,136 citations · 0 from inside this corpus

M. A. Ganaie, Minghui Hu, A. K. Malik, M. Tanveer low, Ponnuthurai Nagaratnam Suganthan

No abstract in the source record.

Ensemble deep learning: A review (2022)Ensemble deep learning: A rev…Random Forests (2001)Random ForestsDropout: a simple way to prevent neural networks from overfitting (2014)Dropout: a simple way to prev…Greedy function approximation: A gradient boosting machine. (2001)Greedy function approximation…Reinforcement Learning: An Introduction (2005)Reinforcement Learning: An In…Bagging Predictors (1996)Bagging PredictorsBagging predictors (1996)Bagging predictorsAdvances in Neural Information Processing Systems 28 (2015)Advances in Neural Informatio…Advances in neural information processing systems 7 (1996)Advances in neural informatio…Distilling the Knowledge in a Neural Network (2015)Distilling the Knowledge in a…Understanding the difficulty of training deep feedforward neural networks (2010)Understanding the difficulty …Ensemble Methods in Machine Learning (2000)Ensemble Methods in Machine L…Stacked generalization (1992)Stacked generalizationExperiments with a new boosting algorithm (1996)Experiments with a new boosti…The random subspace method for constructing decision forests (1998)The random subspace method fo…Proceedings of the 25th international conference on Machine learning (2008)Proceedings of the 25th inter…Playing Atari with Deep Reinforcement Learning (2013)Playing Atari with Deep Reinf…Neural network ensembles (1990)Neural network ensemblesSemi-Supervised Learning Literature Survey (2005)Semi-Supervised Learning Lite…Neural Networks and the Bias/Variance Dilemma (1992)Neural Networks and the Bias/…Ensemble learning: A survey (2018)Ensemble learning: A surveyMulti-Label Classification (2007)Multi-Label ClassificationBoosting the margin: a new explanation for the effectiveness of voting methods (1998)Boosting the margin: a new ex…Classifier chains for multi-label classification (2011)Classifier chains for multi-l…Neural Network Ensembles, Cross Validation, and Active Learning (1994)Neural Network Ensembles, Cro…Deep Learning: Methods and Applications (2014)Deep Learning: Methods and Ap…2013 IEEE International Conference on Acoustics, Speech and Signal Processing (2013)2013 IEEE International Confe…
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What this paper cites, inside the corpus

PaperYearCited
Random Forests2001131,109
Dropout: a simple way to prevent neural networks from overfitting201434,236
Greedy function approximation: A gradient boosting machine.200130,137
Reinforcement Learning: An Introduction200525,758
Bagging Predictors199617,191
Bagging predictors199616,468
Advances in Neural Information Processing Systems 28201514,672
Advances in neural information processing systems 7199614,393
Distilling the Knowledge in a Neural Network201514,099
Understanding the difficulty of training deep feedforward neural networks201012,673
Ensemble Methods in Machine Learning20008,058
Stacked generalization19927,777
Experiments with a new boosting algorithm19967,582
The random subspace method for constructing decision forests19986,904
Proceedings of the 25th international conference on Machine learning20085,551
Playing Atari with Deep Reinforcement Learning20135,104
Neural network ensembles19904,288
Semi-Supervised Learning Literature Survey20053,879
Neural Networks and the Bias/Variance Dilemma19923,612
Ensemble learning: A survey20183,088
Multi-Label Classification20072,518
Boosting the margin: a new explanation for the effectiveness of voting methods19982,344
Classifier chains for multi-label classification20112,307
Neural Network Ensembles, Cross Validation, and Active Learning19941,803
Deep Learning: Methods and Applications20141,801
2013 IEEE International Conference on Acoustics, Speech and Signal Processing20131,462

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Topics

Anomaly Detection Techniques and ApplicationsComputer Science
Machine Learning and ELMComputer Science
Domain Adaptation and Few-Shot LearningComputer Science

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