Proceedings of ELM-2014 Volume 1 Algorithms and Theories [Paperback]

This book contains some selected papers from the International Conference on Extreme Learning Machine 2014, which was held in Singapore, December 8-10, 2014. This conference brought together the researchers and practitioners of Extreme Learning Machine (ELM) from a variety of fields to promote research and development of learning without iterative tuning. ?The book covers theories, algorithms and applications of ELM. It gives the readers a glance of the most recent advances of ELM.

Sparse Bayesian ELM handling with missing data for multi-class classification.- A Fast Incremental Method Based on Regularized Extreme Learning Machine.- Parallel Ensemble of Online Sequential Extreme Learning Machine Based on MapReduce.- Explicit Computation of Input Weights in Extreme Learning Machines.- Subspace Detection on Concept Drifting Data Stream.- Inductive Bias for Semi-supervised Extreme Learning Machine.- ELM based Efficient Probabilistic Threshold Query on Uncertain Data.- Sample-based Extreme Learning Machine Regression with Absent Data.- Two Stages Query Processing Optimization based on ELM in the Cloud.- Domain Adaption Transfer Extreme Learning Machine.- Quasi-linear extreme learning machine model based nonlinear system identification.- A novel bio-inspired image recognition network with extreme learning machine.- A Deep and Stable Extreme Learning Approach for Classification and Regression.- Extreme Learning Machine Ensemble Classifier for Large-scale Data.- Pruned Extreme Learning Machine Optimization based on RANSAC Multi Model Response Regularization.- Learning ELM network weights using linear discriminant analysis.- An Algorithm for Classification over Uncertain Data based on Extreme Learning Machine.- Training Generalized Feedforward Kernelized Neural Networks on Very Large Datasets for Regression Using Minimal-Enclosing-Ball Approximation.- An Online Multiple Model Approach to Improve Performance in Univariate Time-Series Prediction.-l³Z