Publications associées à Deconvolution of Gaussian Random Fields using the Graph Fourier Transform

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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

Deconvolution of Gaussian Random Fields using the Graph Fourier Transform

Graph Chatbot

Chattez avec Graph Search

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

The Mutual Information in Random Linear Estimation Beyond i.i.d. Matrices

Lower Bounds on Active Learning for Graphical Model Selection

Functional data analysis by matrix completion

When Slepian Meets Fiedler: Putting a Focus on the Graph Spectrum

A Prediction-Error Covariance Estimator for Adaptive Kalman Filtering in Step-Varying Processes: Application to Power-System State Estimation

Lower Bounds on Regret for Noisy Gaussian Process Bandit Optimization

Tracking Time-Vertex Propagation using Dynamic Graph Wavelets

Graph-Based Representation and Coding of Multiview Images

Graph Signal Processing

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

The Mutual Information in Random Linear Estimation Beyond i.i.d. Matrices

Lower Bounds on Active Learning for Graphical Model Selection

When Slepian Meets Fiedler: Putting a Focus on the Graph Spectrum

Functional data analysis by matrix completion

A Prediction-Error Covariance Estimator for Adaptive Kalman Filtering in Step-Varying Processes: Application to Power-System State Estimation

Tracking Time-Vertex Propagation using Dynamic Graph Wavelets

Lower Bounds on Regret for Noisy Gaussian Process Bandit Optimization

Graph Signal Processing

Graph-Based Representation and Coding of Multiview Images