Machine Learning
Error reduction through learning multiple descriptions
Machine Learning
Learning to remove Internet advertisements
Proceedings of the third annual conference on Autonomous Agents
A patent search and classification system
Proceedings of the fourth ACM conference on Digital libraries
Least Squares Support Vector Machine Classifiers
Neural Processing Letters
Machine Learning
Machine learning in automated text categorization
ACM Computing Surveys (CSUR)
Ensembling neural networks: many could be better than all
Artificial Intelligence
IWANN '97 Proceedings of the International Work-Conference on Artificial and Natural Neural Networks: Biological and Artificial Computation: From Neuroscience to Technology
RCV1: A New Benchmark Collection for Text Categorization Research
The Journal of Machine Learning Research
Pattern Recognition and Machine Learning (Information Science and Statistics)
Pattern Recognition and Machine Learning (Information Science and Statistics)
Introduction to the special issue on patent processing
Information Processing and Management: an International Journal
Letters: Convex incremental extreme learning machine
Neurocomputing
Variations of the two-spiral task
Connection Science
Sales forecasting using extreme learning machine with applications in fashion retailing
Decision Support Systems
Incorporating Prior Knowledge into Task Decomposition for Large-Scale Patent Classification
ISNN 2009 Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II
Artificial Intelligence: A Modern Approach
Artificial Intelligence: A Modern Approach
Adaptive Ensemble Models of Extreme Learning Machines for Time Series Prediction
ICANN '09 Proceedings of the 19th International Conference on Artificial Neural Networks: Part II
Hadoop: The Definitive Guide
ICONIP'10 Proceedings of the 17th international conference on Neural information processing: theory and algorithms - Volume Part I
Improvement on response performance of min-max modular classifier by symmetric module selection
ISNN'05 Proceedings of the Second international conference on Advances in neural networks - Volume Part II
Gender recognition using a min-max modular support vector machine
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part II
A modular k-nearest neighbor classification method for massively parallel text categorization
CIS'04 Proceedings of the First international conference on Computational and Information Science
Task decomposition using geometric relation for min-max modular SVMs
ISNN'05 Proceedings of the Second international conference on Advances in Neural Networks - Volume Part I
IEEE Transactions on Neural Networks
Universal approximation using incremental constructive feedforward networks with random hidden nodes
IEEE Transactions on Neural Networks
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Extreme Learning Machine (ELM) as an emergent technology has shown its promising performance in many applications. This paper proposes a parallelized ELM ensemble based on the Min-Max Modular network (M^3-network) to meet the challenge of the so-called big data. The proposed M^3-ELM first decomposes classification problems into smaller subproblems, then trains an ELM for each subproblem, and in the end ensembles these ELMs with the M^3-network. Twelve data sets including both benchmarks and real-world applications are employed to test the proposed method. The experimental results show that M^3-ELM not only speeds up the training phrases by 1.6-4.6 times but also reduces the test errors by 0.37-19.51% compared with the normal ELM. The results also indicate that M^3-ELM possesses scalability on large-scale tasks and accuracy improvement on imbalanced tasks.