kernel-based learning algorithm
A feature selection method based on multiple kernel learning with expression profiles of different types
... weighting algorithm to es- timate the feature weights through local approximation rather than global measure- ...the algorithm was effective, when combining the proposed method with classic classifiers ...
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Kernel-based Informative Feature Extraction via Gradient Learning
... employ algorithm 2, the extension of KIFS, to perform dimension ...projection algorithm. Since our quantification method is based on a energy function which is similar to MMI, we empirically compared ...
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Practical Kernel-Based Reinforcement Learning
... We start the paper presenting some background material in Section 2. Then, in Sec- tion 3, we introduce the stochastic-factorization trick, the insight underlying the devel- opment of our algorithm. KBSF itself is ...
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Bounded Kernel-Based Online Learning
... first algorithm to overcome the unlimited growth of the support set was proposed by Crammer et ...online algorithm to have a fixed memory budget and a relative mistake bound is the Forgetron ...
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Kernel Based Learning of Hierarchical Multilabel Classification Models
... efficient learning algorithm relying a decom- position of the problem into single training example subproblems and conducting iterative condi- tional gradient ascent in marginal dual variable subspaces ...
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Effective use of WordNet Semantics via Kernel Based Learning
... ambiguation side effect. CD has been successfully applied to semantic tagging ((Basili et al., 2004)). As the WN hierarchies for other POS classes (i.e. verb and adjectives) have topological properties dif- ferent from ...
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Kernel Collaborative Representation Classification Based on Adaptive Dictionary Learning
... dictionary learning algorithm to expand the original dictionary and thus improve the classification ...dictionary learning method to get a discriminative structured ...dictionary learning ...
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Title: A Novel Kernel Based Fuzzy C Means Clustering With Cluster Validity Measures
... Gaussian-function-based kernel fuzzy clustering is corrected, and a kernel fuzzy c-means clustering-based fuzzy SVM algorithm (KFCM-FSVM) is developed by [14] to deal with the ...
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Kernel Based Extreme Learning Machine in Identifying Dermatological Disorders
... Extreme Learning Machine (ELM) was originally developed for single hidden layer feed forward neural ...(ANN) based classifiers can integrate both structural and statistical information and achieve better ...
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A Sampling Method Based on Gauss Kernel Learning and the Expanding Research
... new algorithm has been mentioned in this paper, which is effective in atomic space for keeping training samples' consistency in different space; Otherwise, increasing qty of positive samples, decreasing negative ...
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Kernel-Based Multilayer Extreme Learning Machines for Representation Learning
... Extreme learning machine (ELM) is an emerging learning algorithm for the generalized single hidden layer feedforward neural networks, of which the hidden node parameters are randomly generated and ...
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KeLP: a Kernel based Learning Platform for Natural Language Processing
... online learning models, ...to kernel- based methods, for tackling classification, regres- sion or clustering ...efficient learning algorithm can be adopted, like linear methods, ...
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Multi label Learning Based on Kernel Extreme Learning Machine
... multi-label learning with large scale class labels has turned out to be the research ...multi-label algorithm based on kernel learning machine in this ...the kernel extreme ...
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Clustering Spatial Data Using a Kernel-Based Algorithm
... The kernel methods are among the most researched subjects within machine-learning community in recent years and has been widely applied to pattern recognition and function ...20], kernel Fisher ...
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JKernelMachines: A Simple Framework for Kernel Machines
... for learning with ...sophisticated learning-based kernel combination methods such as Multiple Kernel Learning (MKL), and a recently published algorithm to learn powered ...
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An Improved Spectral Clustering Algorithm Based on Local Neighbors in Kernel Space
... Gong et al. proposed a spectral clustering method [10] which called LSC algorithm. Instead of using the pairwise relationship, they considered the linear neighbors relationship based on the idea of local ...
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Facial expression recognition using local binary patterns and discriminant kernel locally linear embedding
... a kernel- based learning, ...new kernel-based supervised manifold learning algorithm based on LLE, called discriminant kernel locally linear embedding ...
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Comparison of fuzzy integral fuzzy measure based ensemble algorithms with the state of the art ensemble algorithms
... combinations. Based on the expected potential of non-linear aggregation offered by the FI, its ap- plication to decision-level fusion in ensemble classifiers, ...Multiple Kernel Learning (DeFIMKL) ...
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Stock Market Prediction Using Support Vector Machine
... SVM are the techniques of mathematical programming and kernel functions. The parameters are found by solving a quadratic programming problem with linear equality and inequality constraints; rather than by solving ...
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Mixed Kernel Twin Support Vector Machines Based on the Shuffled Frog Leaping Algorithm
... mixed kernel function, MK-TWSVM can be able to achieve such significant ...mixed kernel function does not randomly select any kernel functions to be combined, but choose a global kernel ...
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