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Constructive Semi-Supervised Classification Algorithm and Its Implement in Data Mining [chapter]

Arvind Singh Chandel, Aruna Tiwari, Narendra S. Chaudhari
2009 Lecture Notes in Computer Science  
In this paper, we propose a novel fast training algorithm called Constructive Semi-Supervised Classification Algorithm (CS-SCA) for neural network construction based on the concept of geometrical expansion  ...  This constructive learning avoids blind selection of neural network structure.  ...  Concluding Remarks A binary neural network based Semi-supervised classifier is constructed using the concept of geometrical expansion, which classify semi-labeled data.  ... 
doi:10.1007/978-3-642-11164-8_11 fatcat:wxxh3c2iefc5vkhq67uc6vr5au

Design and Implementation of Binary Neural Network Classification Learning Algorithm

Shweta Kori
2012 IOSR Journal of Computer Engineering  
In this paper a Binary Neural Network Learning (BNN-CLA)[1] is analyzed and implemented for solving multi class problem normally the classifier are construct by combining the outputs of several binary  ...  ones.  ...  Wang and Chaudhari [1] proposed a geometrical approach for the construction of binary neural networks called as Fast Covering Learning Algorithm (FCLA).  ... 
doi:10.9790/0661-0163642 fatcat:ngqlx4q4mfb3jpuez5awaruraq

A Conceptual Study On User Identification And Verification Process Using Face Recognition Techniques

K. Krishnaprasad, P. S. Aithal
2017 Zenodo  
Face recognition is one of the types of unique biometrics measure related to human characteristics, which can be used for identification or authentication purpose as individual's claimed identity.  ...  Based on face data acquisition, face recognition techniques can be broadly classified into three types as intensity images using local binary pattern, video sequences using training videos and 3D information  ...  Neural Networks Nonlinearity in the network is one prominent reason for usage of Neural Networks.  ... 
doi:10.5281/zenodo.810343 fatcat:q7suddtijvgrnhimptuzlfcfau

A Conceptual Study on User Identification and Verification Process using Face Recognition Technique

Krishnaprasad K., P. S. Aithal
2017 International journal of applied engineering and management letters  
Face recognition is one of the types of unique biometrics measure related to human characteristics, which can be used for identification or authentication purpose as individual's claimed identity.  ...  Based on face data acquisition, face recognition techniques can be broadly classified into three types as intensity images using local binary pattern, video sequences using training videos and 3D information  ...  Neural Networks Nonlinearity in the network is one prominent reason for usage of Neural Networks.  ... 
doi:10.47992/ijaeml.2581.7000.0002 fatcat:6ebpdcpkgfdljd7lsloui7zuhe

Towards Comprehensive Foundations of Computational Intelligence [chapter]

Włodzisław Duch
2007 Studies in Computational Intelligence  
such meta-learning, and a more general approach based on chains of transformations.  ...  Learning from partial observations is a natural extension towards reasoning based on perceptions, and an approach to intuitive solving of such problems is presented.  ...  This observation may serve as an inspiration for construction of better algorithms for data analysis.  ... 
doi:10.1007/978-3-540-71984-7_11 fatcat:vlfuzhxmgbbqlptp4wnpdty4ae

Nonlinear Quantum Neuron: A Fundamental Building Block for Quantum Neural Networks [article]

Shilu Yan, Hongsheng Qi, Wei Cui
2020 arXiv   pre-print
We present two quantum neuron examples based on the proposed framework. The quantum resources required to construct a single quantum neuron are the polynomial, in function of the input size.  ...  The powerful generalization of neural networks is attributed to nonlinear activation functions.  ...  Acknowledgments The authors acknowledge the support of IBM Quantum Experience for producing the experimental results. This work was supported partly by the National Key  ... 
arXiv:2011.03429v1 fatcat:mml6ni6s2nhuxjhhavpnrhd3wu

An Analysis of a BERT Deep Learning Strategy on a Technology Assisted Review Task

Alexandros Ioannidis
2021 Zenodo  
I test and evaluate the retrieval effectiveness of my DL strategy on the 2017 and 2018 CLEF eHealth collections.  ...  the articles with the aforementioned datasets, for the CLEF eHealth Technologically Assisted Reviews in Empirical Medicine Task.  ...  This NN (Neural Network) approach enhanced the performance of identifying relevant documents for SRs.  ... 
doi:10.5281/zenodo.4697891 fatcat:w4ks77xkdjfupi47vhsskoh6n4

Stochastic Network Models in Neuroscience: A Festschrift for Jack Cowan. Introduction to the Special Issue

Paul C. Bressloff, Bard Ermentrout, Olivier Faugeras, Peter J. Thomas
2016 Journal of Mathematical Neuroscience  
The Banff International Research Station hosted a workshop in his honor, on Stochastic Network Models of Neocortex, July 17-24, 2014.  ...  This accompanying Festschrift celebrates Cowan's contributions by assembling current research in stochastic phenomena in neural networks.  ...  Acknowledgements We would like to thank the Banff International Research Station for hosting the workshop Stochastic Network Models of Neocortex (a Festschrift for Jack Cowan), https://www.birs.ca/ events  ... 
doi:10.1186/s13408-016-0036-y pmid:27043152 pmcid:PMC4820414 fatcat:qoavoj5imnae7avsdqloxdcbau

Holographic Automata for Ambient Immersive A. I. via Reservoir Computing [article]

Theophanes E. Raptis
2018 arXiv   pre-print
We also examine the significance of their dual representation on a frequency or wavelength domain as a superposition of plane waves for distributed computing applications including a new proposal for a  ...  Examples of the technique are presented for rules akin to the "edge-of-chaos" including the Turing universal rule 110 for further utilization in the area of reservoir computing.  ...  zero or one in this expansion C stand for an arbitrary circulant filter of which the L x L matrix representation is always decomposable to exactly L permutations as position m of any Boolean vector  ... 
arXiv:1806.05108v2 fatcat:wjgtes5ovfh5lm2vfw3ixnurwq

Realtime Trajectory Smoothing with Neural Nets [article]

Shohei Fujii, Quang-Cuong Pham
2022 arXiv   pre-print
Leveraging fast clearance inference by a novel neural network, the proposed method is able to consistently smooth the trajectories of a 6-DOF industrial robot arm within 200 ms on a commercial GPU.  ...  Here we propose a Realtime Trajectory Smoother based on the shortcutting technique to address this issue.  ...  An approach to integrate classic sampling-based planner with optimization-based planner [17] cannot still handle dynamic obstacles. D.  ... 
arXiv:2111.02165v2 fatcat:2onwykpghfbwnf45vevbygpdm4

Functional Complexity Based on Topology [chapter]

Hildegard Meyer-Ortmanns
2013 Advances in Network Complexity  
14j 1 Functional Complexity Based on Topology In summary, it is not all kind of dynamical systems to which we would apply this measure, but those in which the topology of the network has the main influence  ...  on the stationary states of the system.  ...  For a neural network, this number may give a hint on the storage capacity in terms of the abundance of special loop motifs.  ... 
doi:10.1002/9783527670468.ch01 fatcat:h7uz7npei5ejhdxovrctbpfpg4

Oversquashing in GNNs through the lens of information contraction and graph expansion [article]

Pradeep Kr. Banerjee, Kedar Karhadkar, Yu Guang Wang, Uri Alon, Guido Montúfar
2022 arXiv   pre-print
We compare the spectral expansion properties of our algorithm with that of an existing curvature-based non-local rewiring strategy.  ...  We present a framework for analyzing oversquashing based on information contraction.  ...  ACKNOWLEDGMENT The authors thank Anuran Makur, Chuteng Zhou, Florentin Münch and Jürgen Jost for helpful discussions.  ... 
arXiv:2208.03471v1 fatcat:atgouvbajre53mplubayfute2m

LIST OF AUTHORS AND TITLES 14TH ANNUAL MEETING OF THE JAPANESE SOCIETY OF COMPUTATIONAL STATISTICS

2000 Journal of the Japanese Society of Computational Statistics  
of Dichotomous Dependent Variables -An Extension o f Boolean Approach-• Y.  ...  Takeuchi (Osaka Sangyou University): Construction of Balanced Incomplete Block Designs by Neural Network May 26, 2000 (Friday: Day 2) Session 4 (Chair: M. Mizuta) • Y.  ... 
doi:10.5183/jjscs1988.13.49 fatcat:e5yucfh3arccbjghvqqzeoxxjm

Page 4328 of Mathematical Reviews Vol. , Issue 98G [page]

1998 Mathematical Reviews  
Contents: Peter Andras, Approximation of functions with tree- structured neural networks (1-8); Dorin Andrica, An abstract result in approximation theory (9-12); Dan Barbosu, On some Bernstein-Schoenberg  ...  spline interpolation procedures (13-20); Lu- cia Rodica Blaga, Liana Lupsa and Nicolaie Lupsa, An applica- tion of pseudo-Boolean programming in electric network (21-28); Mioara Boncut, A variational  ... 

Geometric Uncertainty in Patient-Specific Cardiovascular Modeling with Convolutional Dropout Networks [article]

Gabriel Maher, Casey Fleeter, Daniele Schiavazzi, Alison Marsden
2020 arXiv   pre-print
We demonstrate our approach by quantifying the effect of geometric uncertainty on the hemodynamics for three patient-specific anatomies, an aorto-iliac bifurcation, an abdominal aortic aneurysm and a sub-model  ...  A convolutional neural network architecture with dropout layers is first trained for vessel lumen segmentation using a regression approach, to enable Bayesian estimation of vessel lumen surfaces.  ...  (CDSE) grant 1508794, NSF CAREER award 1942662, National Institute of Health grants R01HL123689 and R01EB018302 and the American Heart Association Precision Medicine Platform.  ... 
arXiv:2009.07395v1 fatcat:meaucqnjavf7jgav27vc5ukskm
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