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kernel regression

87 papers

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Co-occurring keywords

neural tangent kernel (205) kernel methods (1097) generalization error (285) gradient descent (1144) nonparametric regression (111) reproducing kernel hilbert space (334) random feature (89) gaussian process (1200) adaptive regression (5) support vector machine (978)

Papers

On the Similarity between the Laplace and Neural Tangent Kernels NIPS 2020
Understanding Double Descent Requires A Fine-Grained Bias-Variance Decomposition NIPS 2020
Sample complexity and effective dimension for regression on manifolds NIPS 2020
The Neural Tangent Kernel in High Dimensions: Triple Descent and a Multi-Scale Theory of Generalization ICML 2020
Decentralised Learning with Random Features and Distributed Gradient Descent ICML 2020
On Exact Computation with an Infinitely Wide Neural Net NIPS 2019
Kernel Machines Beat Deep Neural Networks on Mask-Based Single-Channel Speech Enhancement INTERSPEECH 2019
Variational Inference of Penalized Regression with Submodular Functions UAI 2019
Sublinear Time Numerical Linear Algebra for Structured Matrices AAAI 2019
Sparse Kernel Regression with Coefficient-based $\ell_q-$regularization JMLR 2019
On $b$-bit Min-wise Hashing for Large-scale Regression and Classification with Sparse Data JMLR 2018
Learning and Inference in Hilbert Space with Quantum Graphical Models NIPS 2018
Deep Reinforcement Learning in Continuous Action Spaces: a Case Study in the Game of Simulated Curling ICML 2018
Streaming kernel regression with provably adaptive mean, variance, and regularization JMLR 2018
Beyond Similar and Dissimilar Relations : A Kernel Regression Formulation for Metric Learning IJCAI 2018
Learning Theory of Distributed Regression with Bias Corrected Regularization Kernel Network JMLR 2017
Time-Accuracy Tradeoffs in Kernel Prediction: Controlling Prediction Quality JMLR 2017
Generative Local Metric Learning for Kernel Regression NIPS 2017
Multivariate Regression on the Grassmannian for Predicting Novel Domains CVPR 2016
Gradients Weights improve Regression and Classification JMLR 2016
A Nonlinear Regression Technique for Manifold Valued Data With Applications to Medical Image Analysis CVPR 2016
Theoretical Analyses on Ensemble and Multiple Kernel Regressors ACML 2014
Robust and Efficient Kernel Hyperparameter Paths with Guarantees ICML 2014
Blind Image Quality Assessment using Semi-supervised Rectifier Networks CVPR 2014
Robust Data-Driven Dynamic Programming NIPS 2013