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Deep Learning with Convolutional Neural Network for Proportional Control of Finger Movements from surface EMG Recordings

Publications associées (36)

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Functional lagged regression with sparse noisy observations

Victor Panaretos, Tomas Rubin

A functional (lagged) time series regression model involves the regression of scalar response time series on a time series of regressors that consists of a sequence of random functions. In practice, the underlying regressor curve time series are not always ...

WILEY2020

Force Characterization Of Meso-Scale Haptic Devices

Jamie Paik, Sagar Dattatray Joshi, Frédéric Henri Vaskin Giraud

Recent advances with haptic devices have shown great potential in physically simulating contact with an object. In meso-scale (1 to 10 cm) haptic devices, although the actuation level can be controlled, their small form-factor makes it difficult to measure ...

2019

Multiple generalized additive models are a class of statistical regression models wherein parameters of probability distributions incorporate information through additive smooth functions of predictors. The functions are represented by basis function expan ...

EPFL2019

We study generalization properties of distributed algorithms in the setting of nonparametric regression over a reproducing kernel Hilbert space (RKHS). We investigate distributed stochastic gradient methods (SGM), with mini-batches and multi-passes over th ...

2018

Modeling, Regression and Optimization

Julien Léo Billeter

This lecture describes the following topics: • Preamble on Linear Algebra • Dynamic and Static Models • Solving Dynamic and Static Models • Solving Regression Problems • Solving Static and Dynamic Optimization Probl ...

2016

A Geometric View on Constrained M-Estimators

Volkan Cevher, Yen-Huan Li, Ya-Ping Hsieh, Nissim Zerbib

We study the estimation error of constrained M-estimators, and derive explicit upper bounds on the expected estimation error determined by the Gaussian width of the constraint set. Both of the cases where the true parameter is on the boundary of the constr ...

2015

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This study aims towards an improved estimation of annual heat demand of the building stock for an entire region. This requires the holistic representation of aspects influencing the heat demand of buildings, namely their geometry, fabric, users and surroun ...

Elsevier2015

We study the problem of distributed adaptive estimation over networks where nodes cooperate to estimate physical parameters that can vary over both space and time domains. We use a set of basis functions to characterize the space-varying nature of the para ...

2014

Exploratory Analysis of Endogeneity in Discrete Choice Models

Michel Bierlaire, Anna Fernández Antolín, Amanda Blomberg Stathopoulos

A model is said to be affected by endogeneity when its deterministic part is correlated with the error term. This is an issue that affects both linear models such as regression and non-linear models like discrete choice models. It is a classical and well s ...

2014

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Aggregation of particles is fundamental for improving the performance of many solid/liquid processes. Aggregation can be induced by different means, and one of the most common is based on the addition of polymeric additives, namely polyelectrolytes. In thi ...

Elsevier Science Sa2013