Kernel Methods

Momentum

18 papers in the last four weeks, up 125% on the four weeks before. 0.2% of all new papers.

Jul 13Week of Sep 28

Latest papers 168

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  1. Learning with Volterra Neural Networks: A System Theoretic Perspective

    Sep 1, 2026Haoyu Yun, Hamid Krim, Yufang BaoKernel MethodsNeural Operators

  2. DK-GBMKKM: Dynamic Kernel-Space Granular-Ball Multiple Kernel kk-Means Clustering

    Sep 1, 2026Xiaoyu Lian, Yuchao Zhang, Shuyin Xia +2ClusteringKernel Methods

  3. The Frame Kernel Method for Multiscale Operator Learning

    Aug 25, 2026Branden Frieden, Ryan Whitehead, M. Keith Ballard +2PDE Surrogate ModelingKernel Methods

  4. Finding the Needle in a Haystack: Test-Time Analog Circuit Representation Adaptation for Bayesian Optimization

    Aug 13, 2026Fin Amin, Sounak Dutta, Paul D. FranzonRepresentation LearningTest-Time Adaptation

  5. Kernel Methods for Learning Operators with Multiple Inputs and Outputs

    Aug 12, 2026Adrien Weihs, Chunyang Liao, Jingmin Sun +1Kernel MethodsPDE Operator Learning

  6. Improving TensorSketch Using Complex Random Variables

    Aug 11, 2026Amit Sharma, Mohammad Azhar Khan, Rameshwar Pratap +1Randomized SketchingKernel Methods

  7. Multi-kernel spectral clustering: Entrywise eigenvector perturbation bounds and exact recovery

    Aug 9, 2026Zeqin Lin, Guangming Pan, Zhixiang Zhang +1ClusteringUnsupervised Clustering

  8. Tensor Network Kernel Machines: A JAX Framework for Machine Learning and Nonlinear System Identification

    Aug 7, 2026Albert Saiapin, Kim BatselierTensor NetworksNonlinear System Identification

  9. Beyond the Gegenbauer Paradigm: q-Orthogonal Kernels for Machine Learning

    Aug 4, 2026Álvaro Sánchez-Paniagua Ríos, Juan P. Llerena, Alberto Lastra +2Support Vector MachinesKernel Methods

  10. Simple-regret rates and minimax optimality of fixed-prior expected improvement in Matérn and squared-exponential RKHSs

    Jul 31, 2026Emmanuel Vazquez, Sébastien PetitBayesian OptimizationGaussian Processes

  11. Integrating Contextual Embeddings into Evaluation of Expressive MIDI Piano Performances

    Jul 30, 2026Dmitrii Gavrilev, Ilya Borovik, Vladimir ViroKernel MethodsMusic Information Retrieval

  12. PIKS: Universal Physics-Informed Kernel Methods

    Jul 29, 2026Joachim Bona-Pellissier, Giacomo Meanti, Matteo Santacesaria +1Kernel MethodsPhysics-Informed ML

  13. A Coulomb Particle Model for Learning Kernel Attention in Transformers

    Jul 26, 2026Masoud Badiei Khuzani, Sharath Honnaiah, Atiq Islam +2Transformer AttentionEfficient Attention

  14. Deep Convolutional Large-Margin ℓp\ell_p-SVDD for Visual Anomaly Detection

    Jul 24, 2026Alireza Dastmalchi Saei, Shervin Rahimzadeh ArashlooKernel MethodsOne-Class Classification

  15. Data eccentricity, asymptotics of Gaussian RBF reproducing kernel Hilbert space, and kernel PCA

    Jul 23, 2026Sergio A. AlvarezPrincipal Component AnalysisReproducing Kernel Hilbert Spaces

  16. A Structure-Adaptive Random Feature Method for High-Dimensional Elliptic PDEs

    Jul 22, 2026Jiale Linghu, Hao Dong, Yangshuai WangPDE SolvingRandom Feature Methods

  17. A Multiclass Quantum Aligned Centroid Kernel

    Jul 22, 2026Kilian Tscharke, Pascal DebusMulticlass ClassificationQuantum Kernel Methods

  18. Unsupervised Multi-kernel Learning for Automated Algorithm Selection

    Jul 21, 2026Yihang Lu, Tome Eftimov, Carola DoerrBlack-Box OptimizationUnsupervised Clustering

  19. Improving Improved Kernel PLS

    Jul 17, 2026Ole-Christian Galbo EngstrømHigh-Performance ComputingKernel Methods

  20. QCNN with Rough Path Signature Kernels

    Jul 8, 2026Leonardo Nogueira Falabella, Vasily SazonovTime Series ClassificationQuantum Convolutional Neural Networks

  21. Kernel-based Operator Learning: Error Analysis, Budget Allocation, and a Physics-Informed Extension

    Jul 7, 2026Rüdiger KempfKernel MethodsPDE Operator Learning

  22. Learning-based Physics-Constrained Neural Kernel for Sound Field Estimation With Source-Position-Dependent Directional Weighting

    Jul 7, 2026Mattia Marella, Shoichi KoyamaKernel RegressionImplicit Neural Representations

  23. Structured Gaussian Processes for Uncertainty-Aware Classification of High-Dimensional, Small-Sampled Omics Data

    Jul 2, 2026Yue Zhang, Nandini Amit Gadhia, Georgios Karagiannis +1Gaussian ProcessesKernel Methods

  24. A Kernel Fisher Discriminant Analysis-Based Tree Ensemble Classifier: KFDA Forest

    Jun 27, 2026Donghwan Kim, Seung Hwan Park, Jun-Geol BaekEnsemble LearningClassification

  25. XMSE-Aware Adaptive Empirical Bayes Estimation

    Jun 25, 2026Minghao Chen, Jiale ZhengParameter EstimationEmpirical Bayes

  26. Differential Spectral Damping Gap Adaptive Regularization for Ill-Conditioned Kernel Methods

    Jun 22, 2026Praveg VashishthaSpectral RegularizationSupport Vector Machines