Publications related to Constrained expectation-maximization algorithm for stochastic inertial error modeling: study of feasibility

Fast K-Means with Accurate Bounds

We propose a novel accelerated exact

k

-means algorithm, which outperforms the current state-of-the-art low-dimensional algorithm in 18 of 22 experiments, running up to 3

\times

faster. We also propose a general improvement of existing state-of-the-art a ...

Idiap2016

A continuation multilevel Monte Carlo algorithm

Fabio Nobile, Erik Gustaf Bogislaw Von Schwerin

We propose a novel Continuation Multi Level Monte Carlo (CMLMC) algorithm for weak approximation of stochastic models. The CMLMC algorithm solves the given approximation problem for a sequence of decreasing tolerances, ending when the required error tolera ...

2015

Diffusion LMS Over Multitask Networks

Ali H. Sayed, Jie Chen

The diffusion LMS algorithm has been extensively studied in recent years. This efficient strategy allows to address distributed optimization problems over networks in the case where nodes have to collaboratively estimate a single parameter vector. Neverthe ...

Institute of Electrical and Electronics Engineers2015

Accuracy of Phase-Based Algorithms for the Estimation of the Specific Differential Phase Shift Using Simulated Polarimetric Weather Radar Data

Alexis Berne, Jacopo Grazioli, Marc Schneebeli Zeugin

The specific differential phase shift on propagation K-dp is widely employed in the study of precipitation, although little is known about the effective accuracy of its estimates. The aim of this letter is to analyze the quality of K-dp estimates, using re ...

Ieee-Inst Electrical Electronics Engineers Inc2014

MATHICSE Technical Report : A continuation multilevel Monte Carlo algorithm

Fabio Nobile, Erik Gustaf Bogislaw Von Schwerin

We propose a novel Continuation Multi Level Monte Carlo (CMLMC) algorithm for weak approximation of stochastic models that are described in terms of differential equations either driven by random measures or with random coefficients. The CMLMC algorithm so ...

MATHICSE2014

Generalized Method of Wavelet Moments for Inertial Navigation Filter Design

Jan Skaloud, Stéphane Guerrier, Yannick Stebler

The integration of observations issued from a satellite-based system (GNSS) with an inertial navigation system (INS) is usually performed through a Bayesian filter such as the extended Kalman filter (EKF). The task of designing the navigation EKF is strong ...

Institute of Electrical and Electronics Engineers2014

Portfolio construction under information asymmetry

Lionel Coulot

We introduce in this thesis the idea of a variable lookback model, i.e., a model whose predictions are based on a variable portion of the information set. We verify the intuition of this model in the context of experimental finance. We also propose a novel ...

EPFL2013

A Recommender System Based on Belief Propagation over Pairwise Markov Random Fields

Erman Ayday

Recommender systems enable service providers to predict and address the individual needs of their customers so as to deliver personalized experiences. In this paper, we formulate the recommendation problem as an inference problem on a Pairwise Markov Rando ...

Ieee2013

A Framework for Inertial Sensor Calibration Using Complex Stochastic Error Models

Jan Skaloud, Stéphane Guerrier, Yannick Stebler

Modeling and estimation of gyroscope and accelerometer errors is generally a very challenging task, especially for low-cost inertial MEMS sensors whose systematic errors have complex spectral structures. Consequently, identifying correct error-state parame ...

Ieee2012

Diffusion LMS for source and process estimation in sensor networks

Ali H. Sayed

We develop a least mean-squares (LMS) diffusion strategy for sensor network applications where it is desired to estimate parameters of physical phenomena that vary over space. In particular, we consider a regression model with space-varying parameters that ...

IEEE2012

Constrained expectation-maximization algorithm for stochastic inertial error modeling: study of feasibility

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Fast K-Means with Accurate Bounds

A continuation multilevel Monte Carlo algorithm

Diffusion LMS Over Multitask Networks

Accuracy of Phase-Based Algorithms for the Estimation of the Specific Differential Phase Shift Using Simulated Polarimetric Weather Radar Data

MATHICSE Technical Report : A continuation multilevel Monte Carlo algorithm

Generalized Method of Wavelet Moments for Inertial Navigation Filter Design

Portfolio construction under information asymmetry

A Recommender System Based on Belief Propagation over Pairwise Markov Random Fields

A Framework for Inertial Sensor Calibration Using Complex Stochastic Error Models

Diffusion LMS for source and process estimation in sensor networks

A continuation multilevel Monte Carlo algorithm

MATHICSE Technical Report : A continuation multilevel Monte Carlo algorithm

Accuracy of Phase-Based Algorithms for the Estimation of the Specific Differential Phase Shift Using Simulated Polarimetric Weather Radar Data

A Framework for Inertial Sensor Calibration Using Complex Stochastic Error Models

Portfolio construction under information asymmetry

Generalized Method of Wavelet Moments for Inertial Navigation Filter Design

Fast K-Means with Accurate Bounds

A Recommender System Based on Belief Propagation over Pairwise Markov Random Fields

Diffusion LMS Over Multitask Networks

Diffusion LMS for source and process estimation in sensor networks