Reproducing Kernel Hilbert Space, Mercer's Theorem, Eigenfunctions, Nyström Method, and Use of Kernels in Machine Learning: Tutorial and Survey

15 June 2021

Papers citing "Reproducing Kernel Hilbert Space, Mercer's Theorem, Eigenfunctions, Nyström Method, and Use of Kernels in Machine Learning: Tutorial and Survey"

22 / 22 papers shown

Title
A Distributional Treatment of Real2Sim2Real for Vision-Driven Deformable Linear Object Manipulation Georgios Kamaras Subramanian Ramamoorthy 32 0 0 25 Feb 2025
STAF: Sinusoidal Trainable Activation Functions for Implicit Neural Representation Alireza Morsali MohammadJavad Vaez Hossein Soltani A. Kazerouni Babak Taati Morteza Mohammad-Noori 144 1 0 02 Feb 2025
ProKeR: A Kernel Perspective on Few-Shot Adaptation of Large Vision-Language Models Yassir Bendou Amine Ouasfi Vincent Gripon A. Boukhayma VLM 51 0 0 19 Jan 2025
Convolutional Filtering with RKHS Algebras Alejandro Parada-Mayorga Leopoldo Agorio Alejandro Ribeiro J. Bazerque 38 0 0 02 Nov 2024
Learning to Embed Distributions via Maximum Kernel Entropy Oleksii Kachaiev Stefano Recanatesi OOD 49 0 0 01 Aug 2024
Attention as Robust Representation for Time Series Forecasting Peisong Niu Tian Zhou Xue Wang Liang Sun Rong Jin AI4TS 24 4 0 08 Feb 2024
Rethinking Backdoor Attacks on Dataset Distillation: A Kernel Method Perspective Ming-Yu Chung Sheng-Yen Chou Chia-Mu Yu Pin-Yu Chen Sy-Yen Kuo Tsung-Yi Ho DD 42 6 0 28 Nov 2023
Pseudo-keypoint RKHS Learning for Self-supervised 6DoF Pose Estimation Yangzheng Wu Michael A. Greenspan 18 1 0 16 Nov 2023
Optimal Transport for Kernel Gaussian Mixture Models Jung Hun Oh Rena Elkin Anish K. Simhal Jiening Zhu Joseph O. Deasy Allen Tannenbaum OT 35 0 0 28 Oct 2023
An Exact Kernel Equivalence for Finite Classification Models Brian Bell Michaela Geyer David Glickenstein Amanda Fernandez Juston Moore 27 2 0 01 Aug 2023
Taming graph kernels with random features K. Choromanski 32 12 0 29 Apr 2023
On Mitigating the Utility-Loss in Differentially Private Learning: A new Perspective by a Geometrically Inspired Kernel Approach Mohit Kumar Bernhard A. Moser Lukas Fischer 11 2 0 03 Apr 2023
Learning Inter-Annual Flood Loss Risk Models From Historical Flood Insurance Claims and Extreme Rainfall Data Joaquín Salas Anamitra Saha S. Ravela AI4CE 11 0 0 15 Dec 2022
Contrastive Corpus Attribution for Explaining Representations Christy Lin Hugh Chen Chanwoo Kim Su-In Lee SSL 19 8 0 30 Sep 2022
Parameterized Quantum Circuits with Quantum Kernels for Machine Learning: A Hybrid Quantum-Classical Approach Daniel T. Chang 30 4 0 28 Sep 2022
Understanding the Role of Nonlinearity in Training Dynamics of Contrastive Learning Yuandong Tian MLT 26 13 0 02 Jun 2022
Diverse Weight Averaging for Out-of-Distribution Generalization Alexandre Ramé Matthieu Kirchmeyer Thibaud Rahier A. Rakotomamonjy Patrick Gallinari Matthieu Cord OOD 199 128 0 19 May 2022
Spectral, Probabilistic, and Deep Metric Learning: Tutorial and Survey Benyamin Ghojogh A. Ghodsi Fakhri Karray Mark Crowley 52 20 0 23 Jan 2022
Generative Adversarial Networks and Adversarial Autoencoders: Tutorial and Survey Benyamin Ghojogh A. Ghodsi Fakhri Karray Mark Crowley GAN 34 12 0 26 Nov 2021
Sufficient Dimension Reduction for High-Dimensional Regression and Low-Dimensional Embedding: Tutorial and Survey Benyamin Ghojogh A. Ghodsi Fakhri Karray Mark Crowley 23 2 0 18 Oct 2021
Johnson-Lindenstrauss Lemma, Linear and Nonlinear Random Projections, Random Fourier Features, and Random Kitchen Sinks: Tutorial and Survey Benyamin Ghojogh A. Ghodsi Fakhri Karray Mark Crowley 21 11 0 09 Aug 2021
Unified Framework for Spectral Dimensionality Reduction, Maximum Variance Unfolding, and Kernel Learning By Semidefinite Programming: Tutorial and Survey Benyamin Ghojogh A. Ghodsi Fakhri Karray Mark Crowley 16 4 0 29 Jun 2021