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On the Complexity of Neural Network Classifiers: A Comparison Between Shallow and Deep Architectures
On the Complexity of Neural Network Classifiers: A Comparison Between Shallow and Deep Architectures
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On the Complexity of Neural Network Classifiers: A Comparison Between Shallow and Deep Architectures

Bianchini, Monica ; Scarselli, Franco

IEEE transaction on neural networks and learning systems, 2014-08, Vol.25 (8), p.1553-1565

New York, NY: IEEE

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2
Feature Learning for Image Classification Via Multiobjective Genetic Programming
Feature Learning for Image Classification Via Multiobjective Genetic Programming
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Feature Learning for Image Classification Via Multiobjective Genetic Programming

Shao, Ling ; Liu, Li ; Li, Xuelong

IEEE transaction on neural networks and learning systems, 2014-07, Vol.25 (7), p.1359-1371

New York, NY: IEEE

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3
Novel Cascade FPGA Accelerator for Support Vector Machines Classification
Novel Cascade FPGA Accelerator for Support Vector Machines Classification
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Novel Cascade FPGA Accelerator for Support Vector Machines Classification

Papadonikolakis, M. ; Bouganis, C.

IEEE transaction on neural networks and learning systems, 2012-07, Vol.23 (7), p.1040-1052

New York, NY: IEEE

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4
Bidirectional Extreme Learning Machine for Regression Problem and Its Learning Effectiveness
Bidirectional Extreme Learning Machine for Regression Problem and Its Learning Effectiveness
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Bidirectional Extreme Learning Machine for Regression Problem and Its Learning Effectiveness

Yang, Yimin ; Wang, Yaonan ; Yuan, Xiaofang

IEEE transaction on neural networks and learning systems, 2012-09, Vol.23 (9), p.1498-1505

New York, NY: IEEE

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5
Classification in the Presence of Label Noise: A Survey
Classification in the Presence of Label Noise: A Survey
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Classification in the Presence of Label Noise: A Survey

Frenay, Benoit ; Verleysen, Michel

IEEE transaction on neural networks and learning systems, 2014-05, Vol.25 (5), p.845-869

New York, NY: IEEE

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6
A Comprehensive Review of Stability Analysis of Continuous-Time Recurrent Neural Networks
A Comprehensive Review of Stability Analysis of Continuous-Time Recurrent Neural Networks
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A Comprehensive Review of Stability Analysis of Continuous-Time Recurrent Neural Networks

Zhang, Huaguang ; Wang, Zhanshan ; Liu, Derong

IEEE transaction on neural networks and learning systems, 2014-07, Vol.25 (7), p.1229-1262

New York, NY: IEEE

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7
Adaptive Consensus Control for a Class of Nonlinear Multiagent Time-Delay Systems Using Neural Networks
Adaptive Consensus Control for a Class of Nonlinear Multiagent Time-Delay Systems Using Neural Networks
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Adaptive Consensus Control for a Class of Nonlinear Multiagent Time-Delay Systems Using Neural Networks

Chen, C. L. Philip ; Guo-Xing Wen ; Yan-Jun Liu ; Fei-Yue Wang

IEEE transaction on neural networks and learning systems, 2014-06, Vol.25 (6), p.1217-1226

New York, NY: IEEE

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8
Policy Iteration Adaptive Dynamic Programming Algorithm for Discrete-Time Nonlinear Systems
Policy Iteration Adaptive Dynamic Programming Algorithm for Discrete-Time Nonlinear Systems
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Policy Iteration Adaptive Dynamic Programming Algorithm for Discrete-Time Nonlinear Systems

Liu, Derong ; Wei, Qinglai

IEEE transaction on neural networks and learning systems, 2014-03, Vol.25 (3), p.621-634

New York, NY: IEEE

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9
Global and Local Structure Preservation for Feature Selection
Global and Local Structure Preservation for Feature Selection
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Global and Local Structure Preservation for Feature Selection

Liu, Xinwang ; Wang, Lei ; Zhang, Jian ; Yin, Jianping ; Liu, Huan

IEEE transaction on neural networks and learning systems, 2014-06, Vol.25 (6), p.1083-1095

New York, NY: IEEE

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10
ERNN: A Biologically Inspired Feedforward Neural Network to Discriminate Emotion From EEG Signal
ERNN: A Biologically Inspired Feedforward Neural Network to Discriminate Emotion From EEG Signal
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ERNN: A Biologically Inspired Feedforward Neural Network to Discriminate Emotion From EEG Signal

Khosrowabadi, Reza ; Chai Quek ; Kai Keng Ang ; Wahab, Abdul

IEEE transaction on neural networks and learning systems, 2014-03, Vol.25 (3), p.609-620

New York, NY: IEEE

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