Holdings: PROCEEDINGS OF ELM - 2014 : Algorithms and Theories

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PROCEEDINGS OF ELM - 2014 : Algorithms and Theories

Main Author:	Zhang, Jiannan;Xu, Zhixin, Huang, Shan;Tapson, Jonathan
Format:	Proceeding
Language:	Bahasa Inggris
Published:	Springer International Publishing Switzerland 2015
Subjects:	Sparse Bayesian ELM Handling with Missing Data for Multi class Classification (Zhang, Jiannan); A Fast Incremental Method Based on Regularized Extreme Learning Machine (Xu, Zhixin); Parallel Ensemble of Online Sequential Extreme Learning Machine Based on MapReduce (Huang, Shan); Explicit Computation of Input Weights in Extreme Learning Machines (Tapson, Jonathan); Subspace Detection on Concept Drifting Data Stream (Feng, Lin); Inductive Bias for Semi supervised Extreme Learning Machine (Bisio, Federica); ELM Based Efficient Probabilistic Threshold Query on Uncertain Data (Li, Jiajia); Sample Based Extreme Learning Machine Regression with Absent Data (Gao, Hang); Two Stages Query Processing Optimization Based on ELM in the Cloud (Ding, Linlin); Domain Adaptation Transfer Extreme Learning Machines (Zhang, Lei); Quasi Linear Extreme Learning Machine Model Based Nonlinear System Identification (Li, Dazi); A Novel Bio inspired Image Recognition Network with Extreme Learning Machine (Zhang, Lin); A Deep and Stable Extreme Learning Approach for Classification and Regression (Cao, Le le); Extreme Learning Machine Ensemble Classifier for Large Scale Data (Wang, Haocheng); Pruned Annular Extreme Learning Machine Optimization Based on RANSAC Multi Model Response Regularization (Singh, Lavneet); Learning ELM Network Weights Using Linear Discriminant Analysis (Chazal, Philip); An Algorithm for Classification over Uncertain Data Based on Extreme Learning Machine (Cao, Ke yan); Training Generalized Feedforword Kernelized Neural Networks on Very Large Datasets for Regression Using Minimal Enclosing Ball Approximation (Wang, Jun); An Online Multiple Model Approach to Univariate Time Series Prediction (George, Koshy); A Self Organizing Mixture Extreme Leaning Machine for Time Series Forecasting (Muzhou, Hou); Ensemble Extreme Learning Machine Based on a New Self adaptive AdaBoost.RT (Zhang, Pengbo); Machine Learning Reveals Different Brain Activities in Visual Pathway during TOVA Test (Sun, Haoqi); Online Sequential Extreme Learning Machine with New Weight Setting Strategy for Nonstationary Time Series Prediction (Wang, Jinwan); RMSE ELM: Recursive Model Based Selective Ensemble of Extreme Learning Machines for Robustness Improvement (Han, Bo); Extreme Learning Machine for Regression and Classification Using L 1 Norm and L 2 Norm (Luo, Xiong); A Semi supervised Online Sequential Extreme Learning Machine Method (Jia, Xibin); ELM Feature Mappings Learning: Single Hidden Layer Feedforward Network without Output Weight (Yang, Yimin); ROS ELM: A Robust Online Sequential Extreme Learning Machine for Big Data Analytics (Liu, Yang ); Deep Extreme Learning Machines for Classification (Tissera, Migel D.); C ELM: A Curious Extreme Learning Machine for Classification Problems (Wu, Qiong); Review of Advances in Neural Networks: Neural Design Technology Stack (WoÅºniak, Stanislaw); Applying Regularization Least Squares Canonical Correlation Analysis in Extreme Learning Machine for Multi label Classification Problems (Kongsorot, Yanika); Least Squares Policy Iteration Based on Random Vector Basis (Zuo, Lei); Identifying Indistinguishable Classes in Multi class Classification Data Sets Using ELM (Dwiyasa, Felis); Effects of Training Datasets on Both the Extreme Learning Machine and Support Vector Machine for Target Audience Identification on Twitter (Lo, Siaw Ling); Extreme Learning Machine for Clustering (Lekamalage, Chamara Kasun Liyanaarachchi).
Online Access:	http://oaipmh-jogjalib.umy.ac.idkatalog.php?opo=lihatDetilKatalog&id=82286

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