Results 21 to 30 of about 354,374 (221)
MSGWO-MKL-SVM: A Missing Link Prediction Method for UAV Swarm Network Based on Time Series
Mathematics, 2022 Missing link prediction technology (MLP) is always a hot research area in the field of complex networks, and it has been extensively utilized in UAV swarm network reconstruction recently.
Mingyu Nan +4 more
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Unsupervised Robust Multiple Kernel Learning via Extracting Local and Global Noises
IEEE Access, 2019 Kernel-based clustering methods can capture the non-linear structure and identify arbitrarily shaped clusters, so they have been widely used in machine learning tasks.
Peng Zhou, Fan Ye, Liang Du
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Pareto-Path Multi-Task Multiple Kernel Learning [PDF]
, 2014 A traditional and intuitively appealing Multi-Task Multiple Kernel Learning (MT-MKL) method is to optimize the sum (thus, the average) of objective functions with (partially) shared kernel function, which allows information sharing amongst tasks.
Anagnostopoulos, Georgios C. +2 more
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Online Supervised Learning Algorithm for Spiking Neuron Based on Spiking Sequence Composite Kernel [PDF]
Jisuanji gongcheng, 2017 Spiking neural network uses temporal coding for data processing,which is an effective tool for complex spatial and temporal information processing.In view of this,this paper applies multiple sequence composite kernel into the spiking sequence processing ...
LIN Xianghong,LI Dan,WANG Xiangwen,ZHANG Ning
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Sensors, 2017 A novel classification model, named the quantum-behaved particle swarm optimization (QPSO)-based weighted multiple kernel extreme learning machine (QWMK-ELM), is proposed in this paper. Experimental validation is carried out with two different electronic
Yulin Jian +8 more
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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020 This article proposes a novel unsupervised domain adaptation (DA) method called ideal regularized discriminative multiple kernel subspace alignment (IRDMKSA) for hyperspectral image (HSI) classification.
Weidong Yang, Jiangtao Peng, Weiwei Sun
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Hierarchical Multiple Kernel K-Means Algorithm Based on Sparse Connectivity [PDF]
Jisuanji kexue, 2023 Multiple kernel learning(MKL) aims to find an optimal consistent kernel function.In the hierarchical multiple kernel clustering(HMKC) algorithm,the sample features are extracted layer by layer from high-dimensional space to maximize the retention of ...
WANG Lei, DU Liang, ZHOU Peng
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Error Bounds for lp-Norm Multiple Kernel Learning with Least Square Loss
Abstract and Applied Analysis, 2012 The problem of learning the kernel function with linear combinations of multiple kernels has attracted considerable attention recently in machine learning.
Shao-Gao Lv, Jin-De Zhu
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Boosted Multiple Kernel Learning for First-Person Activity Recognition [PDF]
, 2017 Activity recognition from first-person (ego-centric) videos has recently gained attention due to the increasing ubiquity of the wearable cameras. There has been a surge of efforts adapting existing feature descriptors and designing new descriptors for ...
Arabaci, Mehmet Ali +3 more
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Learning Output Kernels for Multi-Task Problems [PDF]
, 2013 Simultaneously solving multiple related learning tasks is beneficial under a variety of circumstances, but the prior knowledge necessary to correctly model task relationships is rarely available in practice. In this paper, we develop a novel kernel-based
Dinuzzo, Francesco
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