Search Results - (( using sparse method algorithm ) OR ( using optimization method algorithm ))
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Proximal linearized method for sparse equity portfolio optimization with minimum transaction cost
Published 2023“…We develop an efficient algorithm to find the optimal portfolio and prove its global convergence. …”
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Taylor-Bird Swarm Optimization-Based Deep Belief Network For Medical Data Classification
Published 2022“…Then, the selected features are given as input to the DBN classifier which is trained using the Taylor-based bird swarm algorithm (Taylor-BSA). …”
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Optimization of k-Nearest Neighbour to categorize Indonesian’s news articles
Published 2021“…There are several filter-based feature selection methods; some are Chi-Square, Information Gain, Genetic Algorithm, and Particle Swarm Optimization (PSO). …”
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Bayesian Framework based Brain Source Localization Using High SNR EEG Data
Published 2019“…These sources can be localized using different optimization algorithms. This localization information is usable for diagnoses of brain disorders such as epilepsy, Schizophrenia, depression and Alzheimer. …”
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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method
Published 2024thesis::doctoral thesis -
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Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning
Published 2016“…Moreover, instead of concatenating feature vectors together and send to classifier, sparse coding and dictionary learning methods are used and instead of considering all features as one view (visual feature), K-SVD algorithm that is one of the famous algorithms for sparse representation is optimized and developed to multi-view model.The experimental results prove that the proposed methods has improved accuracy by 53.77% compared to concatenating features and classic K-SVD dictionary learning model as well.…”
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7
Kernerlized Correlation Filters Parameters Optimization For Enhanced Visual Tracking
Published 2017“…In our case, our target is to obtain a better accuracy, which is higher overlap ratio and lower centre location error than the result from the algorithms available in public. A simple optimization is used in here, where the global best results with respect to the value of the parameters are selected through a range of values defined in our work. …”
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Modified quasi-Newton type methods using gradient flow system for solving unconstrained optimization
Published 2016“…We investigate the possible use of control theory, particularly theory on gradient ow system to derive some modified line search and trust region methods for optimization. …”
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3D LiDAR Vehicle Perception and Classification Using 3D Machine Learning Algorithm
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Physics-guided deep neural network to characterize non-Newtonian fluid flow for optimal use of energy resources
Published 2021“…In this research, a novel algorithm (Herschel Bulkley Network) is introduced to simulate the non-Newtonian fluid flow in a pipe using data redundant deep neural network (DNN) for fully developed, laminar, and incompressible flow conditions. …”
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Robust correlation feature selection based support vector machine approach for high dimensional datasets
Published 2025“…Correlation-based feature selection methods are popular tools used to select the most important variables to include the true model in the analysis of sparse and high-dimensional models. …”
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Information fusion and data augmentation with deep features for a deep learning-based baby cry recognition / Zhang Ke
Published 2024“…The Whale optimization algorithm-Variational mode decomposition is used to optimally decompose the baby cry signals. …”
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13
Class binarization with self-adaptive algorithm to improve human activity recognition
Published 2018“…Therefore, feature selection using Relief-f with self-adaptive Differential Evolution (rsaDE) algorithm is proposed to select the most significant features. …”
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Bayesian random forests for high-dimensional classification and regression with complete and incomplete microarray data
Published 2018“…Random Forests (RF) are ensemble of trees methods widely used for data prediction, interpretation and variable selection purposes. …”
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Energy balancing mechanisms for decentralized routing protocols in wireless sensor networks
Published 2012“…Finally, we propose Self-Decision Route Selection scheme which is an improvement of the Hop-based Spanning Tree (HST) algorithm that is used in some routing protocols such as AODV and DSR. …”
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17
Evaluation of sparsifying algorithms for speech signals
Published 2012“…Sparse representations of signals have been used in many areas of signal and image processing. …”
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An improved plant identification system by Fuzzy c-means bag of visual words model and sparse coding
Published 2020“…Performance of proposed methods surpass the classic bag of words algorithm for plant identification tasks.…”
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Blind Source Separation Using Two-Dimensional Nonnegative Matrix Factorization In Biomedical Field
Published 2018“…Theoretically,β and α is parameters that used to vary the NMF2D algorithm in order to yield high SDR value. …”
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