Proceedings of ELM-2014 Volume 1 (Record no. 54305)
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| fixed length control field | 05272nam a22005175i 4500 |
| 001 - CONTROL NUMBER | |
| control field | 978-3-319-14063-6 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20200421111649.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 141204s2015 gw | s |||| 0|eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9783319140636 |
| -- | 978-3-319-14063-6 |
| 082 04 - CLASSIFICATION NUMBER | |
| Call Number | 006.3 |
| 245 10 - TITLE STATEMENT | |
| Title | Proceedings of ELM-2014 Volume 1 |
| Sub Title | Algorithms and Theories / |
| 300 ## - PHYSICAL DESCRIPTION | |
| Number of Pages | VIII, 446 p. 124 illus. |
| 490 1# - SERIES STATEMENT | |
| Series statement | Proceedings in Adaptation, Learning and Optimization, |
| 505 0# - FORMATTED CONTENTS NOTE | |
| Remark 2 | 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 -- A Self-organizing Mixture Extreme Leaning Machine for Time Series Forecasting -- A Robust AdaBoost.RT based Ensemble Extreme Learning Machine -- Machine learning reveals different brain activities during TOVA test -- Online Sequential Extreme Learning Machine with New Weight-setting Strategy or Non stationary Time Series Prediction -- RMSE-ELM: Recursive Model based Selective Ensemble of Extreme Learning Machines for Robustness Improvement -- Extreme Learning Machine for Regression and Classification Using L1-Norm and L2-Norm -- A Semi-supervised Online Sequential Extreme Learning Machine Method -- ELM feature mappings learning: Single-hidden-layer feed forward network without output weight -- ROS-ELM: A Robust Online Sequential Extreme Learning Machine for Big Data -- Deep Extreme Learning Machines for Classification -- C-ELM: A Curious Extreme Learning Machine for Classification Problems -- Review of Advances in Neural Networks: Neural Design Technology Stack -- Applying Regularization Least Squares Canonical Correction Analysis in Extreme Learning Machine formulti-label classification problems -- Least Squares Policy Iteration based on Random Vector Basis -- Identifying Indistinguishable Classes in Multi-class Classification Data Sets using ELM -- Effects of Training Datasets on both the Extreme Learning Machine and Support Vector Machine for Target Audience Identification on Twitter -- Extreme Learning Machine for Clustering. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | 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. . |
| 700 1# - AUTHOR 2 | |
| Author 2 | Cao, Jiuwen. |
| 700 1# - AUTHOR 2 | |
| Author 2 | Mao, Kezhi. |
| 700 1# - AUTHOR 2 | |
| Author 2 | Cambria, Erik. |
| 700 1# - AUTHOR 2 | |
| Author 2 | Man, Zhihong. |
| 700 1# - AUTHOR 2 | |
| Author 2 | Toh, Kar-Ann. |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | http://dx.doi.org/10.1007/978-3-319-14063-6 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | eBooks |
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| -- | Cham : |
| -- | Springer International Publishing : |
| -- | Imprint: Springer, |
| -- | 2015. |
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| -- | text |
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| -- | computer |
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| -- | rdamedia |
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| -- | online resource |
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| -- | text file |
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| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Engineering. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Artificial intelligence. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Computational intelligence. |
| 650 14 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Engineering. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Computational Intelligence. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Artificial Intelligence (incl. Robotics). |
| 830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE | |
| -- | 2363-6084 ; |
| 912 ## - | |
| -- | ZDB-2-ENG |
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