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On Kernel Target Alignment
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/3-540-44581-1_26openalex-snapshot
Estimating the Optimal Margins of Embeddings in Euclidean Half Spaces
inferredcites →https://doi.org/10.1007/978-1-4612-0711-5openalex-snapshot
A Probabilistic Theory of Pattern Recognition
inferredcites →https://doi.org/10.1017/cbo9780511801389openalex-snapshot
An Introduction to Support Vector Machines and Other Kernel-based Learning Methods
inferredcites →https://doi.org/10.1017/cbo9780511897467openalex-snapshot
Entropy, Compactness and the Approximation of Operators
inferredcites →https://doi.org/10.1017/cbo9781107359949.008openalex-snapshot
On the method of bounded differences
inferredcites →https://doi.org/10.1080/10556789208805504openalex-snapshot
Robust linear programming discrimination of two linearly inseparable sets
inferredcites →https://doi.org/10.1109/18.705570openalex-snapshot
Structural risk minimization over data-dependent hierarchies
inferredcites →https://doi.org/10.1137/0611030openalex-snapshot
Partitioning Sparse Matrices with Eigenvectors of Graphs
inferredcites →https://doi.org/10.1145/369133.369228openalex-snapshot
Gene functional classification from heterogeneous data
inferredcites →https://doi.org/10.1184/r1/6606860openalex-snapshot
Learning from Labeled and Unlabeled Data using Graph Mincuts
inferredcites →https://doi.org/10.5555/1005332.1005334openalex-snapshot
Learning the Kernel Matrix with Semi-Definite Programming
inferredcites →https://doi.org/10.5555/299094openalex-snapshot
Advances in kernel methods: support vector learning
inferredcites →https://doi.org/10.5555/645529.657980openalex-snapshot
Sparse Greedy Matrix Approximation for Machine Learning
inferredcites →https://doi.org/10.7551/mitpress/1120.003.0052openalex-snapshot
On Kernel-Target Alignment
inferredcites →https://doi.org/10.7551/mitpress/4170.001.0001openalex-snapshot
Learning Kernel Classifiers
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Svm Classifiers For Asr: A Discussion About Parameterization
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Alternatives to Parameter Selection for Kernel Methods
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Evolutionary Optimization of Sequence Kernels for Detection of Bacterial Gene Starts
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Application of Support Vector Machines in a Life Assurance Environment
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Multiple Kernel Learning for Hyperspectral Image Classification
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Learning based on Similarity
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Soft Kernel Target Alignment for Two-Stage Multiple Kernel Learning
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Stochastic Dykstra Algorithms for Metric Learning with Positive Definite Covariance Descriptors
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Direct Estimation of Spinal Cobb Angles by Structured Multi-output Regression
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Deep Kernelized Autoencoders
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Advances in Kernel Machines for Image Classification and Biophysical Parameter Retrieval
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Formulation of Two Stage Multiple Kernel Learning Using Regression Framework
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Stochastic Online Kernel Selection with Instantaneous Loss in Random Feature Space
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Hybrid RVM Algorithm Based on the Prediction Variance
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A Discussion of Nonlinear Variants of Biased Discriminants for Interactive Image Retrieval
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SVM-Based Feature Selection by Direct Objective Minimisation
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Efficient Hyperkernel Learning Using Second-Order Cone Programming
inferred← citeshttps://doi.org/10.1007/978-3-540-30115-8_7openalex-snapshot
Applying Support Vector Machines to Imbalanced Datasets
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Efficiently Learning the Metric with Side-Information
inferred← citeshttps://doi.org/10.1007/978-3-540-45179-2_72openalex-snapshot
Feasible Adaptation Criteria for Hybrid Wavelet – Large Margin Classifiers
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Equivalence Learning in Protein Classification
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Regularized Data Fusion Improves Image Segmentation
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Kernel Methods for Mining Instance Data in Ontologies
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Estimating Quality of Support Vector Machines Learning under Probabilistic and Interval Uncertainty: Algorithms and Computational Complexity
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Multiple Kernel Support Vector Regression for siRNA Efficacy Prediction
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Kernel Matrix Learning for One-Class Classification
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Microarray Design Using the Hilbert–Schmidt Independence Criterion
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Variable Selection for Kernel Classifiers: A Feature-to-Input Space Approach
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Learning Kernel Matrix from Gene Ontology and Annotation Data for Protein Function Prediction
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Optimal Double-Kernel Combination for Classification
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Application Research of Local Support Vector Machines in Condition Trend Prediction of Reactor Coolant Pump
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Similarity and Kernel Matrix Evaluation Based on Spatial Autocorrelation Analysis
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Margin and Radius Based Multiple Kernel Learning
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A Reformulation of Support Vector Machines for General Confidence Functions
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Accurate Probabilistic Error Bound for Eigenvalues of Kernel Matrix
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Affine Invariant Hyperspectral Image Descriptors Based upon Harmonic Analysis
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Similarity Scores Based on Background Samples
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The Application of Support Vector Regression in the Dual-Axis Tilt Sensor Modeling
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Laplacian Spectrum Learning
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Learning with Ensembles of Randomized Trees : New Insights
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Unsupervised Selective Transfer Learning for Object Recognition
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Radial Basis Function Kernel Optimization for Pattern Classification
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Formulating Distance Functions
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Relational Kernel Machines for Learning from Graph-Structured RDF Data
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Generalized Augmentation of Multiple Kernels
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Two-Stage Augmented Kernel Matrix for Object Recognition
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Variable Sparse Multiple Kernels Learning for Novelty Detection
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Kernel Construction via Generalized Eigenvector Decomposition
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On the Choice of a Tensor Distance for DTI White Matter Segmentation
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A General Approach for Adaptive Kernels in Semi-Supervised Clustering
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Learning and Inference in Probabilistic Classifier Chains with Beam Search
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Kernel Methods for Structured Data
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Multiple Kernel Learning Method Using MRMR Criterion and Kernel Alignment
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Kernel Alignment Inspired Linear Discriminant Analysis
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Kernel-Distance Target Alignment
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Research on Kernel Function of Support Vector Machine
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Kernel Learning with Hilbert-Schmidt Independence Criterion
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A Conformal Geometric Algebra Based Clustering Method and Its Applications
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Fuzzy clustering with learnable cluster-dependent kernels
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A survey of the state of the art in learning the kernels
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Supervised data-dependent kernel sparsity preserving projection for image recognition
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Cross-covariance based affinity for graphs
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Indoor Localization via Discriminatively Regularized Least Square Classification
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Combined SVM-Based Feature Selection and Classification
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Model-based transductive learning of the kernel matrix
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Fast learning of relational kernels
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Online Multiple Kernel Classification
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Alignment based kernel learning with a continuous set of base kernels
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Beam search algorithms for multilabel learning
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Data complexity meta-features for regression problems
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Boosted kernel for image categorization
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A random walk based multi-kernel graph learning framework
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Data-dependent kernel sparsity preserving projection and its application for semi-supervised classification
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Only overlay text: novel features for TV news broadcast video segmentation
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A Novel Regularization Learning for Single-View Patterns: Multi-View Discriminative Regularization
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A Study on Multi-Scale Kernel Optimisation via Centered Kernel-Target Alignment
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Alignment Based Kernel Selection for Multi-Label Learning
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Alignment Based Feature Selection for Multi-label Learning
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Twin Gaussian Processes for Structured Prediction
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Identifying Join Candidates in the Cairo Genizah
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First-Person Activity Recognition: Feature, Temporal Structure, and Prediction
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Entropy Power Inequality for Learning Optimal Combination of Kernel Functions
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Kernel selection with spectral perturbation stability of kernel matrix
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Approximation of kernel matrices by circulant matrices and its application in kernel selection methods
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Co-metric: a metric learning algorithm for data with multiple views
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PSO based combined kernel learning framework for recognition of first-person activity in a video
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FTWSVM-SR: DNA-Binding Proteins Identification via Fuzzy Twin Support Vector Machines on Self-Representation
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Multi-scale feature fusion based on swarm intelligence collaborative learning for full-stage anti-interference object tracking
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Kernel learning and optimization with Hilbert–Schmidt independence criterion
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Graph-regularized multi-view semantic subspace learning
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Kernel alignment-based three-way clustering on attribute space and its application in stroke risk identification
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Multi-label learning based on operator-valued kernels
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$$\mathrm{Q(AI)}^2$$: Quantum Artificial Intelligence for the Automotive Industry
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Issues and challenges of class imbalance problem in classification
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A kernel-based quantum random forest for improved classification
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Capturing the Development of Internal Representations in a High-Performing Deep Network for Sleep Stage Classification
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Information-Driven Path Planning
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Kernel-based outlier preserving clustering with representativity coefficients
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Short-term load forecasting using a kernel-based support vector regression combination model
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Low-rank decomposition meets kernel learning: A generalized Nyström method
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Modeling adaptive kernels from probabilistic phylogenetic trees
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A new semi-supervised clustering algorithm with pairwise constraints by competitive agglomeration
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Some sets of orthogonal polynomial kernel functions
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The deep kernelized autoencoder
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Human protein subcellular localization identification via fuzzy model on Kernelized Neighborhood Representation
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Exploiting local label correlation from sample perspective for multi-label classification via three-way decision theory
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ISHM-based intelligent fusion prognostics for space avionics
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A Community Challenge for Inferring Genetic Predictors of Gene Essentialities through Analysis of a Functional Screen of Cancer Cell Lines
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Advanced clustering methods for mining chemical databases in forensic science
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Cross-validatory framework for optimal parameter estimation of KPCA and KPLS models
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Optimizing kernel methods to reduce dimensionality in fault diagnosis of industrial systems
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Cross-Gram matrices and their use in transfer learning: Application to automatic REM detection using heart rate
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Predict DLBCL patients' recurrence within two years with Gaussian mixture model cluster oversampling and multi-kernel learning
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Semi-supervised Laplacian regularized least squares algorithm for localization in wireless sensor networks
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Self-supervised contrastive learning on agricultural images
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Identification of human microRNA-disease association via hypergraph embedded bipartite local model
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Variable selection in kernel Fisher discriminant analysis by means of recursive feature elimination
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Combining visual dictionary, kernel-based similarity and learning strategy for image category retrieval
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Enhanced representation and multi-task learning for image annotation
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Biologically inspired task oriented gist model for scene classification
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Classifying NIR spectra of textile products with kernel methods
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AdaBoost with SVM-based component classifiers
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Kernel optimization using conformal maps for the minimal complexity machine
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Feature selection for SVM via optimization of kernel polarization with Gaussian ARD kernels
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A novel multi-view classifier based on Nyström approximation
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Centered kernel alignment inspired fuzzy support vector machine
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Scaling the kernel function based on the separating boundary in input space: A data-dependent way for improving the performance of kernel methods
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Optimal learning rates of lp -type multiple kernel learning under general conditions
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An efficient Gaussian kernel optimization based on centered kernel polarization criterion
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Efficient learning of supervised kernels with a graph-based loss function
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Content-based histopathology image retrieval using a kernel-based semantic annotation framework
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LSCDFS-MKL: A multiple kernel based method for lung squamous cell carcinomas disease-free survival prediction with pathological and genomic data
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Evaluating deep transfer learning for whole-brain cognitive decoding
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MatrixSim: A new method for detecting the evolution paths of research topics
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Rebooting data-driven soft-sensors in process industries: A review of kernel methods
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Image distance metric learning based on neighborhood sets for automatic image annotation
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Content-based image retrieval model based on cost sensitive learning
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Unsupervised non-parametric kernel learning algorithm
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Two-stage multiple kernel learning with multiclass kernel polarization
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Multi-kernel classification machine with reduced complexity
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Identification of Drug–Target Interactions via Dual Laplacian Regularized Least Squares with Multiple Kernel Fusion
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Learning with Hilbert–Schmidt independence criterion: A review and new perspectives
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Variant of Gaussian kernel and parameter setting method for nonlinear SVM
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Learning by local kernel polarization
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A novel robust kernel for visual learning problems
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Learning low-rank kernel matrices for constrained clustering
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Low-rank quadratic semidefinite programming
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An efficient multiple kernel computation method for regression analysis of economic data
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Locally adaptive multiple kernel clustering
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