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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 ...
Water temperature is a hydrological factor which affects the habitat suitability of many aquatic (fish) species, and is therefore of great concern in the actual context of climate change. Two types of models are currently used to simulate stream temperatur ...
In many fields, and especially in the medical and social sciences and in various recommender systems, data are often gathered through clinical studies or targeted surveys. Participants are generally reluctant to respond to all questions in a survey or they ...
This project attempts to tackle the problem of analysing the heat demand of build- ings at a large (district or city) scale. Specifically, building data from Geneva is used as a case study while building an environment with suitable tools for a continued a ...
Using data from student use of educational technologies to evaluate and improve cognitive models of learners is now a common approach in EDM. Such naturally occurring data poses modeling challenges when non-random factors drive what data is collected. Prio ...
We consider inference on a vector-valued parameter of interest in a linear exponential family, in the presence of a finite-dimensional nuisance parameter. Based on higher-order asymptotic theory for likelihood, we propose a directional test whose p-value i ...
Background: Airway bacterial colonization by potentially pathogenic microorganisms occurs in a proportion of patients with Chronic Obstructive Pulmonary Disease (COPD). It increases airway inflammation and influences outcomes negatively. Yet, its diagnosis ...
The paper introduces a functional time series (lagged) regression model. The impulse-response coefficients in such a model are operators acting on a separable Hilbert space, which is the function space L-2 in applications. A spectral approach to the estima ...
We propose three modeling methods using a mobile sensor network to generate high spatio-temporal resolution air pollution maps for urban environments. In our deployment in Lausanne (Switzerland), dedicated sensing nodes are anchored to the public buses and ...
This paper proposes a distributionally robust approach to logistic regression. We use the Wasserstein distance to construct a ball in the space of probability distributions centered at the uniform distribution on the training samples. If the radius of this ...