Regularity

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Period ending 2026-09-14

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  1. A Weighted Kernel Method for Approximation that Adapts to Learned Multivariable Structure

    Sep 15, 2026John E. Darges, Laura WeidensagerReproducing Kernel Hilbert Spaces

  2. Computer-assisted global regularity across nonlinear families of three-dimensional periodic Navier-Stokes flows

    Sep 14, 2026Jose Luis Lima de Jesus SilvaRegularity

  3. ReLU Neural Network Approximation to Smooth Functional Operator: Dimensional Decay and Error Analysis

    Sep 14, 2026Shuhao JiaoNeural-Network ApproximationRegularity

  4. Rethinking Handwritten Character Recognition

    Sep 11, 2026Ranjit Raut, Aarav Subedi, Ashim ShresthaHandwritingRegularity

  5. Generalization Analysis of Distributed Kernel-based Robust Gradient Descent Algorithms

    Sep 10, 2026Jun-Yi Meng, Zheng-Chu Guo, Yuan MaoDistributional LearningGeneralization Bounds

  6. MiNCE: Nonparametric, Strongly Consistent Confidence Envelopes for Band-Limited Functions and their Smoothed Spectra

    Sep 8, 2026Balázs Csanád Csáji, Bálint HorváthExponential FamilyConfidence Intervals

  7. Optimal estimation for Functional Linear Regression with Noisy Discretized Data

    Sep 8, 2026Sixtine SphabmixayRegressionEstimators

  8. Revisiting Thinning Methods for Kernel Learning Problems

    Sep 7, 2026Blanca Cano-Camarero, Yago R. Aguado-Carrillo-de-Albornoz, Ángela Fernández-Pascual +1Reproducing Kernel Hilbert SpacesBackward

  9. Spectral Convergence of Random Feature Method in Multiple Dimensions

    Sep 3, 2026Pingbing Ming, Hao YuRegularitySpectral Algorithms

  10. Grassmann--Plücker Parametrization of Convolutional Filter Subspaces: Regularity and Closed Embeddings

    Sep 3, 2026Hongyu Yuan, Huaiqing ZuoParameter Space GeometryConvolutional

  11. A Closed-Form Formula for Consistent Lipschitz Regression on Metric Spaces with Sparse Neural Network Realizations

    Sep 2, 2026Ruiyang Hong, Hrad Ghoukasian, Anastasis KratsiosLipschitz ConstantMetric Spaces

  12. Kernel Reboot: Breaking the Boundaries of Neural Tangent Kernels for Neural Fields

    Sep 2, 2026Amir Mallak, Alaa Maalouf, Lior Wolf +2Neural FieldsNeural Tangent Kernel

  13. On Global Regulatability of Robot Manipulators by Classical PID

    Sep 1, 2026Cheng Zhao, Jingru Zhu, Lei GuoRobust ControlRobotic Manipulator

  14. Sharp Mixed Spectral Barron Regularity of Coulombic Many-Electron Wave Functions

    Sep 1, 2026Pingbing Ming, Hao YuRegularity

  15. DK-GBMKKM: Dynamic Kernel-Space Granular-Ball Multiple Kernel k-Means Clustering

    Sep 1, 2026Xiaoyu Lian, Yuchao Zhang, Shuyin Xia +2Granular-Ball ComputingK$-Means

  16. The Frame Kernel Method for Multiscale Operator Learning

    Aug 25, 2026Branden Frieden, Ryan Whitehead, M. Keith Ballard +2Probabilistic Operator LearningMultiscale Dynamics

  17. The Axiomatic Trader: Latent Regularity, Information Budgets, and the Canonical Form of a Quantitative Investment System

    Aug 24, 2026Jiayu LiAxiomPredictability

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

    Aug 12, 2026Adrien Weihs, Chunyang Liao, Jingmin Sun +1Probabilistic Operator LearningReproducing Kernel Hilbert Spaces

  19. A Joint-Distribution Route to Fair Representations with Continuous Sensitive Attributes

    Aug 11, 2026Yijin Ni, Xiaoming HuoFairness-Aware LearningDisparities

  20. GRACE: LLM-Grounded Semantic Metric Spaces for Scalable Mixed-Data Clustering

    Aug 8, 2026Zihua Yang, Zhencheng Xie, Junyang Chen +4ClusteringCluster

  21. Verifiable Regularity Criterion for Conditional Expectation Operators and Conditional Mean Embeddings with Applications to Nonparametric Regression, Bayesian Inverse Problems, and Koopman Operators

    Aug 6, 2026Maximiliano Hertel, Ilja Klebanov, Manuel Schaller +1Kernel Hilbert SpacesRegularity

  22. Fixed and Adaptive Topological DeepONets: Functional Measurements on Hausdorff Locally Convex Spaces

    Aug 5, 2026Khemraj Shukla, George Em KarniadakisFourier Neural OperatorsNeural Operators

  23. Random features for Grassmannian kernel approximation with bounded rank-one projections

    Aug 4, 2026Rémi Delogne, Laurent JacquesReproducing Kernel Hilbert SpacesLow-Rank Factorization

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

    Aug 4, 2026Álvaro Sánchez-Paniagua Ríos, Juan P. Llerena, Alberto Lastra +2Quantum KernelsReproducing Kernel Hilbert Spaces

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

    Jul 31, 2026Emmanuel Vazquez, Sébastien PetitReproducing Kernel Hilbert SpacesDynamic Regret Bounds

  26. Neural Network Approximation of Solutions to Fractional Parabolic Partial Differential Equations

    Jul 30, 2026Jae-Hwan Choi, Hyojae Lim, Jinsol Seo +2Neural-Network ApproximationRegularity

  27. HOMER: Huber-of-Means for Efficient and Robust Estimation in Hilbert Spaces

    Jul 29, 2026Kisung You, Boram ChoEstimatorsKernel Hilbert Spaces

  28. PIKS: Universal Physics-Informed Kernel Methods

    Jul 29, 2026Joachim Bona-Pellissier, Giacomo Meanti, Matteo Santacesaria +1Reproducing Kernel Hilbert SpacesMultiscale Dynamics

  29. Minimax Lower Bounds of Kernel Discrepancy Estimation: MMD, HSIC, KSD

    Jul 27, 2026Jose Cribeiro-Ramallo, Florian Kalinke, Zoltán SzabóMaximum Mean DiscrepancyKernel Hilbert Spaces

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

    Jul 26, 2026Masoud Badiei Khuzani, Sharath Honnaiah, Atiq Islam +2Feature LearningTransformer Attention

  31. Nesterov acceleration in optimizing over probability measures

    Jul 25, 2026Jiaqi Tang, Qin Li, Wilfrid GangboNesterovProbability Measures

  32. Learning from the Descent Direction: Adaptive Gradient Descent under One-Sided Hölder Regularity

    Jul 24, 2026Arzu Ahmadova, Ismail HuseynovGradient DescentDescent

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

    Jul 23, 2026Sergio A. AlvarezReproducing Kernel Hilbert SpacesPrincipal Component Analysis

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

    Jul 19, 2026Antonio Acuaviva, Pablo AcuavivaMathematicsTheoretical Foundations

  35. Regularity as seen by Alice and Bob

    Jul 15, 2026Omid Yaghoubi, Mikołaj Bojańczyk, Aliaume Lopez +1ComputableRegularity

  36. What is a Musical Scale? Regularity and Convention in the Organization of Pitch

    Jul 14, 2026John M McBrideMusical StructureTheoretical Foundations

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

    Jul 13, 2026Aruzhan Tleubek, Salah A FaroughiKolmogorov-Arnold NetworksReproducing Kernel Hilbert Spaces

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

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

  39. Approximation of Analytic Functions by ReLU Neural Networks with Adjustable Depth and Width

    Jul 12, 2026Yanming Lai, Defeng Sun, Yang WangRectified Linear Unit NetworksRegularity

  40. Solving Stochastic Fixed-Point Equations with High Probability

    Jul 10, 2026Jelena DiakonikolasFixed-Point IterationStochastic Approximation

  41. Nonconvex Composite Functional Constraints via First-Order Augmented Lagrangian Methods under Local Regularity

    Jul 9, 2026Linglingzhi Zhu, Jiajin LiPrimal-Dual MethodsNonconvex

  42. Near-Optimal Learning of Gaussian Sobolev Operators

    Jul 8, 2026Ben Adcock, Michael Griebel, Gregor MaierProbabilistic Operator LearningRegularity

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

    Jul 7, 2026Rüdiger KempfProbabilistic Operator LearningReproducing Kernel Hilbert Spaces

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

    Jul 7, 2026Mattia Marella, Shoichi KoyamaSound Source LocalizationConventional Physics-Informed Neural Networks

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

    Jul 6, 2026Kazumi Kasaura, Kei Tsukamoto, Kento Mori +6Information-Theoretic LimitsFormalization

  46. Minimum Block Width for Universal Approximation by Residual Neural Networks with Inner Width One

    Jul 6, 2026Qi Zhou, Xuan Zhou, Xiao-Song YangResidual ConnectionsRegularity

  47. Boundary-layer asymptotics for Gaussian-smoothed singular measures

    Jul 5, 2026Nicolas Brosse, Arnak S. DalalyanRegularityRegularization Methods

  48. Tightening the Score Matching Gap for Diffusion Models

    Jul 5, 2026Benjamin Dupuis, Tyler Farghly, Maxime Haddouche +2Score-Based Diffusion ModelKullback-Leibler Divergence

  49. 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 LearningQuantum Neural Networks

  50. On the stability of scale-space metrics

    Jun 25, 2026William LeebWasserstein DistanceRegularity

  51. ScaleHP: Estimating Hand Pose in Metric Space

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

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

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

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

    Jun 22, 2026Ioannis KalogridisKernel Hilbert SpacesExponential Family

  54. No Reference-Free Generalization in Quantum Machine Learning

    Jun 21, 2026Jeongho BangQuantum LearningQuantum

  55. Subsampling for supervised learning in reproducing kernel Hilbert spaces

    Jun 19, 2026Eyal Vayness, Maxime SangnierReproducing Kernel Hilbert SpacesKernel Hilbert Spaces

  56. Generalization Guarantees for Multi-Input Neural Operator Learning in Sobolev Spaces

    Jun 16, 2026Yahong Yang, Zecheng Zhang, Wei Zhu +2Probabilistic Operator LearningRegularity

  57. Sobolev Approximation by Fixed-Size Neural Networks with Arbitrary Accuracy

    Jun 15, 2026Baicheng Li, Haizhao Yang, Shijun ZhangNeural-Network ApproximationActivation Functions

  58. Deep Q-Learning on Hölder Spaces

    Jun 15, 2026Qian QiQ-LearningDeep Q-Networks

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

    Jun 15, 2026Şevket Kaan Alkır, Naci Saldı, Berkay Anahtarcı +1Mean Field GamesBellman Equation

  60. Brownian Kernel Ladders

    Jun 14, 2026Mahdi Mohammadigohari, Giuseppe Di Fatta, Giuseppe Nicosia +1Kernel Hilbert SpacesOptimal Sample Complexity