Publications associées à Multikernel Regression with Sparsity Constraint

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Lower Bounds on Regret for Noisy Gaussian Process Bandit Optimization

Volkan Cevher, Jonathan Mark Scarlett, Ilija Bogunovic

In this paper, we consider the problem of sequentially optimizing a black-box function

f

based on noisy samples and bandit feedback. We assume that

f

is smooth in the sense of having a bounded norm in some reproducing kernel Hilbert space (RKHS), yield ...

2017

Multikernel Regression with Sparsity Constraint

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Kernel Regression for Graph Signal Prediction in Presence of Sparse Noise

Mean-Field methods for Structured Deep-Learning in Computer Vision

Advancing the State of Network Switch ASIC Offloading in the Linux Kernel

Lower Bounds on Regret for Noisy Gaussian Process Bandit Optimization

A New Formulation of the Cooray-Rubinstein Expression in Time Domain

Semi-supervised and unsupervised kernel-based novelty detection with application to remote sensing images

The Movement Error Rate for Evaluation of Machine Learning Methods for sEMG-based Hand Movement Classification

Learning Parametric Dictionaries for Signals on Graphs

Sparse projections onto the simplex

Efficient Image Reconstruction Under Sparsity Constraints With Application To Mri And Bioluminescence Tomography

The Movement Error Rate for Evaluation of Machine Learning Methods for sEMG-based Hand Movement Classification

Semi-supervised and unsupervised kernel-based novelty detection with application to remote sensing images

A New Formulation of the Cooray-Rubinstein Expression in Time Domain

Lower Bounds on Regret for Noisy Gaussian Process Bandit Optimization

Advancing the State of Network Switch ASIC Offloading in the Linux Kernel

Mean-Field methods for Structured Deep-Learning in Computer Vision

Kernel Regression for Graph Signal Prediction in Presence of Sparse Noise

Learning Parametric Dictionaries for Signals on Graphs

Efficient Image Reconstruction Under Sparsity Constraints With Application To Mri And Bioluminescence Tomography

Sparse projections onto the simplex