Kernel Method

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Period ending 2026-09-21

9 new papers

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Period ending 2026-09-14

5 new papers

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Period ending 2026-09-07

7 new papers

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275 papers

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  1. Nonlinear Bias-Compensated Adaptive Filter and Its Application for Time-Series Prediction

    Jul 22, 2026Yi Peng, Haiquan Zhao, Jinhui HuMultivariate ForecastingNoise-Aware

  2. A Multiclass Quantum Aligned Centroid Kernel

    Jul 22, 2026Kilian Tscharke, Pascal DebusQuantum KernelsQubit

  3. Unsupervised Multi-kernel Learning for Automated Algorithm Selection

    Jul 21, 2026Yihang Lu, Tome Eftimov, Carola DoerrKernel MethodBlack-Box Optimization

  4. Information-Based Exploration via Random Features for Reinforcement Learning

    Jul 20, 2026Waris Radji, Odalric-Ambrym MaillardEfficient ExplorationAutonomous Exploration Strategies

  5. Kernelized Linear Attention: Breaking the Capacity Wall with Symmetric Cones

    Jul 19, 2026Ayoub Ghriss, Sourav ChakrabortyQuadratic AttentionDense Associative Memory

  6. Mathematical Discovery in the Wild: AI-Guided Proofs in Banach Space Theory

    Jul 19, 2026Antonio Acuaviva, Pablo AcuavivaMathematicsProof

  7. De-floored Principal Component Regression: When Rank Selection Alone Is Insufficient for Prediction

    Jul 18, 2026Peng ZhaoPrincipal Component AnalysisKernel Ridge Regression

  8. TraceSynth: Generating Production-Quality Kernel Traces with Constraint-Guided Diffusion Models

    Jul 13, 2026Yuvraj Sehgal, Sneh Patel, Mahsa Panahandeh +2Circuit TracingInference Workloads

  9. Neural Discovery of Memory and Nonlocal Kernels in Integro-Differential Equations with Constrained Kolmogorov--Arnold Networks

    Jul 13, 2026Aruzhan Tleubek, Salah A FaroughiKolmogorov-Arnold NetworksKernel Method

  10. The VC dimension of partial concept classes via Radon's theorem

    Jul 12, 2026Grigory Ivanov, Attila Jung, Márton NaszódiMetric SpacesTheorem

  11. DSSMs: State Space Models with Explicit Memory via Delay Differential Equations

    Jul 11, 2026Yixiao Qian, Song Chen, Jiaxu Liu +2State Space ModelsSequence Modeling

  12. Solving Stochastic Fixed-Point Equations with High Probability

    Jul 10, 2026Jelena DiakonikolasFixed-Point IterationVariance Reduction

  13. Group Invariant Spectral Embedding

    Jul 9, 2026Yeari Vigder, Paulina Hoyos, David Thong +3Graph LaplaciansSymmetry

  14. Near-Optimal Learning of Gaussian Sobolev Operators

    Jul 8, 2026Ben Adcock, Michael Griebel, Gregor MaierLogarithmic Sobolev InequalitiesProbabilistic Operator Learning

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

    Jul 7, 2026Mattia Marella, Shoichi KoyamaSound Source LocalizationKernel Method

  16. Lean-Quantum: Toward AI-Assisted Formalization of Quantum Information

    Jul 6, 2026Kazumi Kasaura, Kei Tsukamoto, Kento Mori +6FormalizationKernel Hilbert Spaces

  17. Sensitivity Sampling with Predictions for k-Means Clustering

    Jul 6, 2026Cristian Boldrin, Fabio VandinK-MeansKernel Method

  18. Non-Asymptotic Error Bounds for SMC with Biased Proposals: Application to Conditional Diffusion Sampling

    Jul 6, 2026Stanislas Strasman, Gabriel Victorino Cardoso, Sylvain Le Corff +2Diffusion SamplingMonte Carlo

  19. Learning dynamical systems from noisy data with Weak-form Kernel Ridge Regression

    Jun 30, 2026Max Kreider, John Harlim, Daning HuangKernel Ridge RegressionDynamical Systems

  20. Beyond the Expressivity-Trainability Paradox: A Dynamical Lie Algebra Perspective on Navigating Barren Plateaus in Quantum Machine Learning

    Jun 30, 2026Kung-Ming Lan, Edward HuangQuantum Machine LearningQuantum Neural Networks

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

    Jun 27, 2026Donghwan Kim, Seung Hwan Park, Jun-Geol BaekRandom ForestDecision Trees

  22. Enhancing Numerical Prediction in LLMs via Smooth MMD Alignment

    Jun 26, 2026Zhuo Zuo, Li Yue, Wenhao Zheng +2Maximum Mean DiscrepancyKernel Method

  23. ScaleHP: Estimating Hand Pose in Metric Space

    Jun 24, 2026Ruitao Jing, Xingyu Chen, Hongyang Li +33D HandHand

  24. Solve for the Hyperparameter, Skip the Search: Kolmogorov-Optimal Scaling Laws for Spline Regression

    Jun 22, 2026Yong Yi Bay, Kathleen A. YearickKernel Ridge RegressionHyperparameter Optimization

  25. Time Series Classification through Diffeomorphic Time Warping (DiffTW)

    Jun 22, 2026Vicky Geneva Haney, Kamel Lahouel, Victor Rielly +1Time-Series ClassificationTime Series

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

    Jun 22, 2026Praveg VashishthaKernel MethodSingular Value Decomposition

  27. Generalized nonparametric regression in reproducing kernel Hilbert spaces: Consistency and rates of convergence

    Jun 22, 2026Ioannis KalogridisKernel Hilbert SpacesEstimators

  28. No Reference-Free Generalization in Quantum Machine Learning

    Jun 21, 2026Jeongho BangQuantum Machine LearningKernel Hilbert Spaces

  29. Subsampling for supervised learning in reproducing kernel Hilbert spaces

    Jun 19, 2026Eyal Vayness, Maxime SangnierKernel Hilbert SpacesSubsampling

  30. Orthogonal Discrepancy Kernels for Learning with Partial Physics

    Jun 19, 2026Swapnil Manna, Timothy J. Rogers, Lawrence BullSystem IdentificationDiscrepancy

  31. Effective Dimension Governs Generalization in Quantum Kernel Vision Models

    Jun 18, 2026Jian Xu, Delu Zeng, John Paisley +1Quantum KernelsEntanglement

  32. Spectral DPPs via NEPv: A Scalable Continuous Relaxation of Determinantal MAP for Diversity-Aware Data Selection

    Jun 17, 2026Richard Yi Da XuLargest EigenvalueKernel Method

  33. Kernel of Partition Paths: A Unified Representation for Tree Ensembles

    Jun 17, 2026Nicolas MahlerDecision TreesKernel Method

  34. Scalable Pairwise Kernel Learning with Stochastic Vec Trick

    Jun 15, 2026Napsu Karmitsa, Tapio Pahikkala, Antti AirolaKernel Method

  35. Deep Q-Learning on Hölder Spaces

    Jun 15, 2026Qian QiQ-LearningDeep Q-Networks

  36. Maximum Entropy Inverse Reinforcement Learning for Mean-Field Games with Average Reward

    Jun 15, 2026Şevket Kaan Alkır, Naci Saldı, Berkay Anahtarcı +1Entropy Regularized Reinforcement LearningBellman Equation

  37. Brownian Kernel Ladders

    Jun 14, 2026Mahdi Mohammadigohari, Giuseppe Di Fatta, Giuseppe Nicosia +1Kernel Hilbert SpacesStochastic Differential Equations

  38. Representation Costs in Data Science: Foundations and the Quasi-Banach Spaces of Deep Neural Networks

    Jun 12, 2026Greg Ongie, Rahul ParhiMetric SpacesKernel Hilbert Spaces

  39. Hybrid Uncertainty Sensitivity Analysis Based on the HSIC for High-Dimensional Responses with Aleatory--Epistemic Separation

    Jun 12, 2026Shijie Zhong, Jiangfeng Fu, Pengfei WeiModel SensitivityKernel Hilbert Spaces

  40. Approximating Gaussian Whittle-Matern Fields over Well-Centered Triangulations of Riemannian Manifolds

    Jun 11, 2026Srinivas NambirajanRiemannian ManifoldsKernel Hilbert Spaces

  41. ERTS: Adversarial Robustness Testing of Ethical AI via Semantic Perturbation in a Bounded Consequence Space

    Jun 11, 2026Pratyush ChaudhariEthicsAdversarial Evaluation

  42. CLARITree: Cholesky and Lookahead Accelerations for Regression with Interpretable Piecewise Linear Trees

    Jun 11, 2026Yixiao Wang, Hayden McTavish, Varun Babbar +2Decision TreesKernel Ridge Regression

  43. Flexible Kernels for Protein Property Prediction

    Jun 9, 2026Martin Jankowiak, Yerdos Ordabayev, Rudraksh Tuwani +4Protein Data BankProtein Design

  44. kk-Nearest Neighbors in Gromov--Wasserstein Space

    Jun 9, 2026Kaitlyn Hohmeier, Nicolas Fraiman, Caroline MoosmuellerGromov--WassersteinApproximate Nearest-Neighbor Search

  45. Bernstein-Schur Kernels: Random Features by Sketched Modulation and Radial Randomization

    Jun 8, 2026Taha BouhsineKernel Hilbert SpacesFourier

  46. Maximum Matching Accuracy: An Instance Segmentation Evaluation Metric Utilizing Globally Optimal Matching

    Jun 8, 2026Kaden Stillwagon, Alexandra D. VandeLoo, Craig R. ForestSharp Boundary DelineationMultiple Instance Learning

  47. Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization

    Jun 8, 2026Ray Zhang, Marcus Greiff, Thomas Lew +1Point Cloud Registration3D Single Object Tracking

  48. Structuring agentic AI for HPC code modernization

    Jun 7, 2026Anthony Marinov, Igor SfiligoiHigh-Performance ComputingCoding Agents

  49. Orthogonality and Dimensionality in Airline Cluster Analysis using PCA and Kernel PCA

    Jun 6, 2026Andreas SchlapbachPrincipal Component AnalysisCluster Structure

  50. How Deep Are Deep GPs, Really? A Sharp Threshold and a Non-Gaussian Limit for Compositional GPs

    Jun 6, 2026Mark Kozdoba, Shie MannorGaussian ProcessCentral Limit Theorem

  51. Frequency-Scale Saliency for Spectral Descriptor Analysis in 3D Shape Retrieval

    Jun 5, 2026Jianru ShenMultiscaleKernel Method

  52. Non-Archimedean Polydisc Spaces and Applications to Optimisation

    Jun 5, 2026Paul Lezeau, Yiannis Fam, Anthea Monod +1Metric SpacesInformation-Geometric Optimization

  53. TorchKM: A GPU-Oriented Library for Kernel Learning and Model Selection

    Jun 4, 2026Yikai Zhang, Gaoxiang Jia, Jie Ding +1Graphics Processing Unit KernelsPytorch

  54. When New Generators Arrive: Lifelong Machine-Generated Text Attribution via Ridge Feature Transfer

    Jun 4, 2026Zhen Sun, Yifan Liao, Zhicong Huang +4Text GenerationGenerators

  55. Generating Financial Time Series by Matching Random Convolutional Features

    Jun 3, 2026Konrad J. Mueller, Nikita Zozoulenko, Ben Wood +2Synthetic Time SeriesTime Series

  56. KODA: Contrastive Representation Comparison and Alignment for Vision-Language Foundation Models

    Jun 2, 2026Youqi Wu, Mohammad Jalali, Farzan FarniaVision-LanguageContrastive

  57. FFR: Forward-Forward Learning for Regression

    Jun 2, 2026Xinyang Liu, Xuanyu Liang, Shiqi Ding +4BackpropagationSingle Forward Pass

  58. A Doeblin-Anchored Contrastive Chart for Learning Markov Transition Kernels

    Jun 1, 2026Ao XuMarkovTransitions

  59. Blurry Window Attention

    May 31, 2026Axel Laborieux, Christos Sourmpis, Juan Gabriel Kostelec +1Softmax AttentionKernel Method

  60. What Makes a Strong Model? A Unified Spectral Analysis of Knowledge Transfer over High-dimensional Linear Regression

    May 31, 2026Wendao Wu, Fangqing Zhang, Haihan Zhang +1Knowledge DistillationKernel Ridge Regression