Publications related to Minimum-variance unbiased estimator

Stationary time-vertex signal processing

This paper considers regression tasks involving high-dimensional multivariate processes whose structure is dependent on some known graph topology. We put forth a new definition of time-vertex wide-sense stationarity, or joint stationarity for short, that g ...

2019

An order-statistics-inspired, fully-digital readout approach for analog SiPM arrays

Edoardo Charbon, Esteban Venialgo Araujo

In this paper we present a silicon photomultiplier (SiPM) readout system based on a field-programmable gate array (FPGA), which is capable of converting any commercial 16-channel analog SiPM array into a hybrid device with fully-digital readout for applica ...

2018

Demonstration of Multiple Kerr-Frequency-Comb Generation Using Different Lines from Another Kerr Comb Located up to a 50 km Distance

Tobias Kippenberg, Maxim Karpov, Martin Hubert Peter Pfeiffer, Arne Kordts, Fatemeh Alishahi, Lin Zhang, Ahmad Fallahpour

We experimentally demonstrate multiple Kerr-frequency-comb generation using different lines from another Kerr comb located up to a 50 km distance. The master and generated slave combs are mutually coherent and have a small variance of frequency error. ...

IEEE2018

Wasserstein Distributionally Robust Kalman Filtering

Daniel Kuhn, Viet Anh Nguyen, Soroosh Shafieezadeh Abadeh, Peyman Mohajerin Esfahani

We study a distributionally robust mean square error estimation problem over a nonconvex Wasserstein ambiguity set containing only normal distributions. We show that the optimal estimator and the least favorable distribution form a Nash equilibrium. Despit ...

2018

Not All Samples Are Created Equal: Deep Learning with Importance Sampling

François Fleuret, Angelos Katharopoulos

Deep neural network training spends most of the computation on examples that are properly handled, and could be ignored. We propose to mitigate this phenomenon with a principled importance sampling scheme that focuses computation on "informative" examples ...

Idiap2018

Periodic Splines and Gaussian Processes for the Resolution of Linear Inverse Problems

Michaël Unser, Julien René Pierre Fageot, Anaïs Laure Marie-Thérèse Badoual

This paper deals with the resolution of inverse problems in a periodic setting or, in other terms, the reconstruction of periodic continuous-domain signals from their noisy measurements. We focus on two reconstruction paradigms: variational and statistical ...

2018

Local estimation of the global horizontal irradiance using an all-sky camera

Mario Paolone, Fabrizio Sossan, Enrica Scolari

Localised and high-frequency measurements of the global horizontal irradiance (GHI) are a key information to assess the level of power production of distributed photovoltaic generation. The paper presents a supervised machine learning-based procedure to es ...

PERGAMON-ELSEVIER SCIENCE LTD2018

Residual-based a posteriori error estimation for contact problems approximated by Nitsche's method

Mathieu Jonathan Fabre, Yves Renard

We introduce a residual-based a posteriori error estimator for contact problems in two- and three-dimensional linear elasticity, discretized with linear and quadratic finite elements and Nitsche’s method. Efficiency and reliability of the estimator are pro ...

2018

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Minimum-variance unbiased estimator

Uncertainty-aware imitation learning using kernelized movement primitives

Stationary time-vertex signal processing

An order-statistics-inspired, fully-digital readout approach for analog SiPM arrays

Averaging Stochastic Gradient Descent on Riemannian Manifolds

Demonstration of Multiple Kerr-Frequency-Comb Generation Using Different Lines from Another Kerr Comb Located up to a 50 km Distance

Wasserstein Distributionally Robust Kalman Filtering

Not All Samples Are Created Equal: Deep Learning with Importance Sampling

Periodic Splines and Gaussian Processes for the Resolution of Linear Inverse Problems

Local estimation of the global horizontal irradiance using an all-sky camera

Residual-based a posteriori error estimation for contact problems approximated by Nitsche's method

Graph Chatbot

Chat with Graph Search

Stationary time-vertex signal processing

An order-statistics-inspired, fully-digital readout approach for analog SiPM arrays

Uncertainty-aware imitation learning using kernelized movement primitives

Local estimation of the global horizontal irradiance using an all-sky camera

Demonstration of Multiple Kerr-Frequency-Comb Generation Using Different Lines from Another Kerr Comb Located up to a 50 km Distance

Residual-based a posteriori error estimation for contact problems approximated by Nitsche's method

Not All Samples Are Created Equal: Deep Learning with Importance Sampling

Averaging Stochastic Gradient Descent on Riemannian Manifolds

Wasserstein Distributionally Robust Kalman Filtering

Periodic Splines and Gaussian Processes for the Resolution of Linear Inverse Problems