Publications related to On the stability and convergence of Feintuch's algorithm for adaptive IIR filtering

Distributional Regression and Autoregression via Optimal Transport

We present a framework for performing regression when both covariate and response are probability distributions on a compact and convex subset of

\R^d

. Our regression model is based on the theory of optimal transport and links the conditional Fr'echet m ...

EPFL2023

Bayes-optimal Learning of Deep Random Networks of Extensive-width

Florent Gérard Krzakala, Lenka Zdeborová, Hugo Chao Cui

We consider the problem of learning a target function corresponding to a deep, extensive-width, non-linear neural network with random Gaussian weights. We consider the asymptotic limit where the number of samples, the input dimension and the network width ...

2023

A multichannel versatile brain activity classification and closed loop neuromodulation system, device and method using a highly multiplexed mixed-signal front-end

Mahsa Shoaran, Uisub Shin, Bingzhao Zhu

A closed-loop neuromodulation system, including an electrode array that is implantable to a brain of a subject, analog front-end device (AFD) for selectively selecting and reading a plurality of channels from electrode array, a finite impulse response (FIR ...

2023

Distribution-on-distribution regression via optimal transport maps

Victor Panaretos, Laya Ghodrati

We present a framework for performing regression when both covariate and response are probability distributions on a compact interval. Our regression model is based on the theory of optimal transportation, and links the conditional Frechet mean of the resp ...

OXFORD UNIV PRESS2022

Daily Contributors of Tinnitus Loudness and Distress: An Ecological Momentary Assessment Study

Patrick Karl Alois Neff

BackgroundTinnitus is a heterogeneous condition which may be associated with moderate to severe disability, but the reasons why only a subset of individuals is burdened by the condition are not fully clear. Ecological momentary assessment (EMA) allows a be ...

FRONTIERS MEDIA SA2022

One Fuzz Doesn’t Fit All: Optimizing Directed Fuzzing via Target-tailored Program State Restriction

Mathias Josef Payer

Fuzzing is the de-facto default technique to discover software flaws, randomly testing programs to discover crashing test cases. Yet, a particular scenario may only care about specific code regions (for, e.g., bug reproduction, patch or regression testing) ...

ASSOC COMPUTING MACHINERY2022

Gaussian Process Regression for Materials and Molecules

Michele Ceriotti, David Mark Wilkins

We provide an introduction to Gaussian process regression (GPR) machinelearning methods in computational materials science and chemistry. The focus of the present review is on the regression of atomistic properties: in particular, on the construction of in ...

AMER CHEMICAL SOC2021

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

Silvestro Micera, Vincent Alexandre Mendez, Leonardo Pollina, Fiorenzo Artoni

The control of robotic prosthetic hands (RPHs) for upper limb amputees is far from optimal. Simultaneous and proportional finger control of a RPH based on EMG signals is still challenging. Based on EMG and kinematics recordings of subjects following a pre- ...

IEEE2021

Sparsest piecewise-linear regression of one-dimensional data

Michaël Unser, Julien René Pierre Fageot, Thomas Jean Debarre, Quentin Alain Denoyelle

We study the problem of one-dimensional regression of data points with total-variation (TV) regularization (in the sense of measures) on the second derivative, which is known to promote piecewise-linear solutions with few knots. While there are efficient a ...

Elsevier2021

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

On the stability and convergence of Feintuch's algorithm for adaptive IIR filtering

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Distributional Regression and Autoregression via Optimal Transport

Bayes-optimal Learning of Deep Random Networks of Extensive-width

A multichannel versatile brain activity classification and closed loop neuromodulation system, device and method using a highly multiplexed mixed-signal front-end

Distribution-on-distribution regression via optimal transport maps

Daily Contributors of Tinnitus Loudness and Distress: An Ecological Momentary Assessment Study

One Fuzz Doesn’t Fit All: Optimizing Directed Fuzzing via Target-tailored Program State Restriction

Gaussian Process Regression for Materials and Molecules

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

Sparsest piecewise-linear regression of one-dimensional data

Functional lagged regression with sparse noisy observations

Distributional Regression and Autoregression via Optimal Transport

A multichannel versatile brain activity classification and closed loop neuromodulation system, device and method using a highly multiplexed mixed-signal front-end

Bayes-optimal Learning of Deep Random Networks of Extensive-width

Gaussian Process Regression for Materials and Molecules

One Fuzz Doesn’t Fit All: Optimizing Directed Fuzzing via Target-tailored Program State Restriction

Distribution-on-distribution regression via optimal transport maps

Daily Contributors of Tinnitus Loudness and Distress: An Ecological Momentary Assessment Study

Functional lagged regression with sparse noisy observations

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

Sparsest piecewise-linear regression of one-dimensional data