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Less is More: Nyström Computational Regularization

16 July 2015

Papers citing "Less is More: Nyström Computational Regularization"

50 / 166 papers shown

Title
Learning Where to Learn: Training Distribution Selection for Provable OOD Performance Nicolas Guerra Nicholas H. Nelsen Yunan Yang OOD 81 0 0 27 May 2025
Computational Efficiency under Covariate Shift in Kernel Ridge Regression Andrea Della Vecchia Arnaud Mavakala Watusadisi Ernesto De Vito Lorenzo Rosasco 47 0 0 20 May 2025
Turbocharging Gaussian Process Inference with Approximate Sketch-and-Project Pratik Rathore Zachary Frangella Sachin Garg Shaghayegh Fazliani Michał Dereziński Madeleine Udell 55 0 0 19 May 2025
Random Forest Autoencoders for Guided Representation Learning Adrien Aumon Shuang Ni Myriam Lizotte Guy Wolf Kevin R. Moon Jake S. Rhodes 180 0 0 18 Feb 2025
Convergence Analysis of regularised Nyström method for Functional Linear Regression Naveen Gupta Sivananthan Sampath 83 0 0 25 Oct 2024
fastkqr: A Fast Algorithm for Kernel Quantile Regression Qian Tang Yuwen Gu Boxiang Wang 60 1 0 10 Aug 2024
Learning to Embed Distributions via Maximum Kernel Entropy Oleksii Kachaiev Stefano Recanatesi OOD 120 0 0 01 Aug 2024
A Hybrid Federated Kernel Regularized Least Squares Algorithm Celeste Damiani Yulia Rodina Sergio Decherchi FedML 61 3 0 24 Jul 2024
Have ASkotch: A Neat Solution for Large-scale Kernel Ridge Regression Pratik Rathore Zachary Frangella Madeleine Udell Michał Dereziński Madeleine Udell 108 3 0 14 Jul 2024
Operator World Models for Reinforcement Learning P. Novelli Marco Prattico Massimiliano Pontil C. Ciliberto OffRL 122 1 0 28 Jun 2024
Structured Prediction in Online Learning Pierre Boudart Alessandro Rudi Pierre Gaillard 33 0 0 18 Jun 2024
Deep Sketched Output Kernel Regression for Structured Prediction T. Ahmad Junjie Yang Pierre Laforgue Florence dÁlché-Buc UQCV 85 1 0 13 Jun 2024
Nyström Kernel Stein Discrepancy Florian Kalinke Zoltan Szabo Bharath K. Sriperumbudur 114 1 0 12 Jun 2024
On the Approximation of Kernel functions Paul Dommel Alois Pichler 132 0 0 11 Mar 2024
Linear quadratic control of nonlinear systems with Koopman operator learning and the Nyström method Edoardo Caldarelli Antoine Chatalic Adrià Colomé C. Molinari C. Ocampo‐Martinez Carme Torras Lorenzo Rosasco 105 0 0 05 Mar 2024
A Bound on the Maximal Marginal Degrees of Freedom Paul Dommel 191 1 0 20 Feb 2024
Closed-form Filtering for Non-linear Systems Théophile Cantelobre C. Ciliberto Benjamin Guedj Alessandro Rudi 30 0 0 15 Feb 2024
Towards Optimal Sobolev Norm Rates for the Vector-Valued Regularized Least-Squares Algorithm Zhu Li Dimitri Meunier Mattes Mollenhauer Arthur Gretton 143 8 0 12 Dec 2023
A Theoretical Analysis of the Test Error of Finite-Rank Kernel Ridge Regression Tin Sum Cheng Aurelien Lucchi Ivan Dokmanić Anastasis Kratsios David Belius 61 5 0 02 Oct 2023
A Structured Prediction Approach for Robot Imitation Learning Anqing Duan Iason Batzianoulis Raffaello Camoriano Lorenzo Rosasco Daniele Pucci A. Billard 50 5 0 26 Sep 2023
Adaptive Distributed Kernel Ridge Regression: A Feasible Distributed Learning Scheme for Data Silos Di Wang Xiaotong Liu Shao-Bo Lin Ding-Xuan Zhou 75 0 0 08 Sep 2023
On regularized Radon-Nikodym differentiation Duc Hoan Nguyen Werner Zellinger S. Pereverzyev 38 7 0 15 Aug 2023
Nonparametric Linear Feature Learning in Regression Through Regularisation Bertille Follain Francis R. Bach 65 4 0 24 Jul 2023
General regularization in covariate shift adaptation Hoan Duc Nguyen S. Pereverzyev Werner Zellinger 41 1 0 21 Jul 2023
Nonlinear Meta-Learning Can Guarantee Faster Rates Dimitri Meunier Zhu Li Arthur Gretton Samory Kpotufe 170 7 0 20 Jul 2023
Nearly Optimal Algorithms with Sublinear Computational Complexity for Online Kernel Regression Junfan Li Shizhong Liao 139 0 0 14 Jun 2023
Estimating Koopman operators with sketching to provably learn large scale dynamical systems Giacomo Meanti Antoine Chatalic Vladimir Kostic P. Novelli Massimiliano Pontil Lorenzo Rosasco 90 11 0 07 Jun 2023
Label Shift Quantification with Robustness Guarantees via Distribution Feature Matching Bastien Dussap Gilles Blanchard Badr-Eddine Chérief-Abdellatif OOD 46 8 0 07 Jun 2023
The Galerkin method beats Graph-Based Approaches for Spectral Algorithms Vivien A. Cabannes Francis R. Bach 66 3 0 01 Jun 2023
Generalized equivalences between subsampling and ridge regularization Pratik V. Patil Jin-Hong Du 91 5 0 29 May 2023
Lp- and Risk Consistency of Localized SVMs Hannes Köhler 117 0 0 16 May 2023
Snacks: a fast large-scale kernel SVM solver Sofiane Tanji Andrea Della Vecchia François Glineur S. Villa 29 0 0 17 Apr 2023
Fast kernel methods for Data Quality Monitoring as a goodness-of-fit test Gaia Grosso Nicolò Lai Marco Letizia J. Pazzini Marco Rando Lorenzo Rosasco A. Wulzer M. Zanetti 43 6 0 09 Mar 2023
Sketching with Spherical Designs for Noisy Data Fitting on Spheres Shao-Bo Lin Di Wang Ding-Xuan Zhou 57 2 0 08 Mar 2023
Kernel-Based Distributed Q-Learning: A Scalable Reinforcement Learning Approach for Dynamic Treatment Regimes Di Wang Yao Wang Shaojie Tang OffRL 143 1 0 21 Feb 2023
Sketch In, Sketch Out: Accelerating both Learning and Inference for Structured Prediction with Kernels T. Ahmad Luc Brogat-Motte Pierre Laforgue Florence dÁlché-Buc BDL 86 6 0 20 Feb 2023
Kernelized Diffusion maps Loucas Pillaud-Vivien Francis R. Bach 68 7 0 13 Feb 2023
Vector-Valued Least-Squares Regression under Output Regularity Assumptions Luc Brogat-Motte Alessandro Rudi Céline Brouard Juho Rousu Florence dÁlché-Buc 77 6 0 16 Nov 2022
Asymptotics of the Sketched Pseudoinverse Daniel LeJeune Pratik V. Patil Hamid Javadi Richard G. Baraniuk Robert Tibshirani 54 10 0 07 Nov 2022
Target alignment in truncated kernel ridge regression Arash A. Amini R. Baumgartner Dai Feng 51 3 0 28 Jun 2022
Sum-of-Squares Relaxations for Information Theory and Variational Inference Francis R. Bach 63 12 0 27 Jun 2022
Fast Kernel Methods for Generic Lipschitz Losses via $p$ -Sparsified Sketches T. Ahmad Pierre Laforgue Florence dÁlché-Buc 107 5 0 08 Jun 2022
Collaborative likelihood-ratio estimation over graphs Alejandro de la Concha Nicolas Vayatis Argyris Kalogeratos 67 1 0 28 May 2022
Active Labeling: Streaming Stochastic Gradients Vivien A. Cabannes Francis R. Bach Vianney Perchet Alessandro Rudi 110 2 0 26 May 2022
Fast Instrument Learning with Faster Rates Ziyu Wang Yuhao Zhou Jun Zhu 100 3 0 22 May 2022
Wind power predictions from nowcasts to 4-hour forecasts: a learning approach with variable selection Dimitri Bouche Rémi Flamary Florence dÁlché-Buc R. Plougonven Marianne Clausel J. Badosa P. Drobinski 21 14 0 20 Apr 2022
Learning new physics efficiently with nonparametric methods Marco Letizia Gianvito Losapio Marco Rando Gaia Grosso A. Wulzer M. Pierini M. Zanetti Lorenzo Rosasco OOD 83 32 0 05 Apr 2022
Information Theory with Kernel Methods Francis R. Bach 60 43 0 17 Feb 2022
Efficient Kernel UCB for Contextual Bandits Houssam Zenati A. Bietti Eustache Diemert Julien Mairal Matthieu Martin Pierre Gaillard 117 4 0 11 Feb 2022
Measuring dissimilarity with diffeomorphism invariance Théophile Cantelobre C. Ciliberto Benjamin Guedj Alessandro Rudi 126 1 0 11 Feb 2022