conftrace_

kernel machine

27 papers

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Co-occurring keywords

kernel methods (1097) support vector machine (978) generalization bound (652) low-rank approximation (323) random feature (89) nyström approximation (19) collaborative learning (148) conjugate gradient (43) kernel ridge regression (111) label noise (498)

Papers

Geometrically Inspired Kernel Machines for Collaborative Learning Beyond Gradient Descent (Abstract Reprint) AAAI 2026
On the Nyström Approximation for Preconditioning in Kernel Machines AISTATS 2024
Unsupervised Neighborhood Propagation Kernel Layers for Semi-supervised Node Classification AAAI 2024
Quantized Fourier and Polynomial Features for more Expressive Tensor Network Models AISTATS 2024
Primal-Attention: Self-attention through Asymmetric Kernel SVD in Primal Representation NIPS 2023
Tensor-based Kernel Machines with Structured Inducing Points for Large and High-Dimensional Data AISTATS 2023
Toward Large Kernel Models ICML 2023
Knowledge Distillation: Bad Models Can Be Good Role Models NIPS 2022
Understanding and Mitigating Data Contamination in Deep Anomaly Detection: A Kernel-based Approach IJCAI 2022
Conjugate Gradients for Kernel Machines JMLR 2020
Hard Shape-Constrained Kernel Machines NIPS 2020
Kernel Machines Beat Deep Neural Networks on Mask-Based Single-Channel Speech Enhancement INTERSPEECH 2019
Overfitting or perfect fitting? Risk bounds for classification and regression rules that interpolate NIPS 2018
KELP: a Kernel-based Learning Platform JMLR 2018
To Understand Deep Learning We Need to Understand Kernel Learning ICML 2018
Learning Kernels with Random Features NIPS 2016
Preconditioning Kernel Matrices ICML 2016
Computationally Efficient Nyström Approximation using Fast Transforms ICML 2016
Fast Prediction for Large-Scale Kernel Machines NIPS 2014
Infinite Markov-Switching Maximum Entropy Discrimination Machines ICML 2013
Collaborative Active Learning of a Kernel Machine Ensemble for Recognition ICCV 2013
JKernelMachines: A Simple Framework for Kernel Machines JMLR 2013
Support Vector Machines with a Reject Option NIPS 2008
Preventing Over-Fitting during Model Selection via Bayesian Regularisation of the Hyper-Parameters JMLR 2007
Random Features for Large-Scale Kernel Machines NIPS 2007