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Analysing the effects of residential mobility behaviours on the composition of personal network in Switzerland

Related publications (34)

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Understanding the reconstruction of personal networks through residential trajectories

Vincent Kaufmann, Guillaume Simon Joseph Drevon, Gil Viry

This paper examines how residential trajectories influence the spatiality and composition of personal networks. Three mechanisms are considered: the addition of spatially close network members, the selection of spatially distant network members, and the su ...

2020

Correlating Twitter Language with Community-Level Health Outcomes

Martin Jaggi, Arno Schneuwly

We study how language on social media is linked to diseases such as atherosclerotic heart disease (AHD), diabetes and various types of cancer. Our proposed model leverages state-of-the-art sentence embeddings, followed by a regression model and clustering, ...

ASSOC COMPUTATIONAL LINGUISTICS-ACL2019

Fast Automatic Smoothing for Generalized Additive Models

Anthony Christopher Davison, Yousra El Bachir

Generalized additive models (GAMs) are regression models wherein parameters of probability distributions depend on input variables through a sum of smooth functions, whose degrees of smoothness are selected by L-2 regularization. Such models have become th ...

MICROTOME PUBL2019

Automatic L2 Regularization for Multiple Generalized Additive Models

Yousra El Bachir

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

A data-driven reduced basis (RB) method for parametrized time-dependent problems is proposed. This method requires the offline preparation of a database comprising the time history of the full-order solutions at parameter locations. Based on the full-order ...

2018

Decentralized machine learning is a promising emerging paradigm in view of global challenges of data ownership and privacy. We consider learning of linear classification and regression models, in the setting where the training data is decentralized over ma ...

NEURAL INFORMATION PROCESSING SYSTEMS (NIPS)2018

Despite recent developments, neighborhood-scale performance assessment at the early-design phase is seldom carried out in practice, notably due to high computational complexity, time requirement, and perceived need for expert knowledge, ultimately limiting ...

2017

Gaussian-Process-Based Emulators for Building Performance Simulation

Marilyne Andersen, Parag Rastogi, Mohammad Emtiyaz Khan

In this paper we present a novel emulator of a building simulator for the simulation-assisted design of high performance buildings. Our emulator is based on Gaussian-Process (GP) regression models. Such non-linear models are better suited than linear model ...

International Building Performance Simulation Association2017

On the sensitivity of buildings to climate

Parag Rastogi

Building simulation requires a large number of uncertain inputs and parameters. These include quantities that may be known with reasonable confidence, like the thermal properties of materials and building dimensions, but also inputs whose correct values ca ...

EPFL2016

Additive models are regression methods which model the response variable as the sum of univariate transfer functions of the input variables. Key benefits of additive models are their accuracy and interpretability on many real-world tasks. Additive models a ...

Institute of Electrical and Electronics Engineers2016