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Meta-analysis of microarray studies to produce an overall gene list is relatively straightforward when complete data are available. When some studies lack information, for example, having only a ranked list of genes instead of complete primary data, it is ...
The promise of Bayesian methods for big data sets has not fully been realized due to the lack of scalable computational algorithms. For massive data, it is necessary to store and process subsets on different machines in a distributed manner. We propose a s ...
This document describes the softwares, data, models and raw results associated to: Danalet, A., Tinguely, L., Lapparent, M. d. and Bierlaire, M. (2016). Location choice with longitudinal WiFi data, Journal of Choice Modelling 18: 1–17. URL: https://dx.doi. ...
Machine learning applications can benefit greatly from vast amounts of data, provided that reliable labels are available. Mobilizing crowds to annotate the unlabeled data is a common solution. Although the labels provided by the crowd are subjective and no ...
My master thesis proposes a general methodology to model pedestrian destination choice from WiFi localization in multimodal transport facilities (e.g., airports, railway stations). It is based on the output of [Danalet, A., B. Farooq and M. Bierlaire (2014 ...
Accurate models of real behaviour that are determined through measurements help engineers avoid expensive interventions and structural replacement. Model calibration by “curve-fitting” measurements to predictions is not appropriate for full-scale structure ...
This thesis develops models of activity and destination choices in pedestrian facilities from WiFi traces. We adapt the activity-based travel demand analysis of urban mobility to pedestrians and to digital footprints. We are interested in understanding the ...
This work aims to forecast rain locally in Tambarga, Burkina Faso, to be able to fight against a worm inducing the disease called schistosomiasis. The chosen approach relies on a machine-leaning technique called Artificial Neural Networks, which simulates ...
An ubiquitous assessment of swimming velocity (main metric of the performance) is essential for the coach to provide a tailored feedback to the trainee. We present a probabilistic framework for the data-driven estimation of the swimming velocity at every c ...
In this thesis, we explore the application of data mining and machine learning techniques to several practical problems. These problems have roots in various fields such as social science, economics, and political science. We show that computer science tec ...
