Distributional Regression and Autoregression via Optimal Transport
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Many decision problems in science, engineering, and economics are affected by uncertainty, which is typically modeled by a random variable governed by an unknown probability distribution. For many practical applications, the probability distribution is onl ...
This paper addresses the problem of efficiently achieving visual predictive control tasks. To this end, a memory of motion, containing a set of trajectories built off-line, is used for leveraging precomputation and dealing with difficult visual tasks. Stan ...
The application of Bayesian modeling techniques is increasingly common in neuroscience due to the coherent and principled way in which the paradigm deals with uncertainty. The Bayesian framework is particularly valuable in the context of complex, ill-posed ...
EPFL2020
Background Privacy-preserving computations on genomic data, and more generally on medical data, is a critical path technology for innovative, life-saving research to positively and equally impact the global population. It enables medical research algorithm ...
2020
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This paper presents an empirical case study on applying game-based learning in an undergraduate finance course. The paper describes the experimental study context, protocol, and results. Using multivariate regression analysis, a significant game effect on ...
IEEE2021
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We tackle modelling and inference for variable selection in regression problems with many predictors and many responses. We focus on detecting hotspots, that is, predictors associated with several responses. Such a task is critical in statistical genetics, ...
INST MATHEMATICAL STATISTICS2020
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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
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Objective: To investigate the association between socioeconomic deprivation and the persistence of SARS-CoV-2 clusters. Methods: We analyzed 3,355 SARS-CoV-2 positive test results in the state of Geneva (Switzerland) from February 26 to April 30, 2020. We ...
FRONTIERS MEDIA SA2021
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We study generalization properties of distributed algorithms in the setting of nonparametric regression over a reproducing kernel Hilbert space (RKHS). We first investigate distributed stochastic gradient methods (SGM), with mini-batches and multi-passes o ...
Background: Understanding the association between motor capacity (MC) (what people can do in a standardized environment), mobility performance (MP) (what people actually do in real-life) and falls is important for early detection of and counteracting on fu ...
