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We develop approximate inference and learning methods for facilitating the use of probabilistic modeling techniques motivated by applications in two different areas. First, we consider the ill-posed inverse problem of recovering an image from an underdeter ...
This thesis addresses statistical inference for the resolution of inverse problems. Our work is motivated by the recent trend whereby classical linear methods are being replaced by nonlinear alternatives that rely on the sparsity of naturally occurring sig ...
Political cohesion is a key form of collective socio-ethical manifestations of solidarity and cooperation in groups. The disappearance of traditional political lines among voters and in the political elite destabilizes political institutions. Research find ...
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 ...
Evaluating the (dis)similarity of crystalline, disordered and molecular compounds is a critical step in the development of algorithms to navigate automatically the configuration space of complex materials. For instance, a structural similarity metric is cr ...
In this dissertation, I address the political and moral geography of Swiss federal participatory votes for the period between 1981 and 2014 to re-investigate some of the fundamental questions left open in urban sciences: how and why socio-ethical, moral an ...
In many fields, and especially in the medical and social sciences and in recommender systems, data are gathered through clinical studies or targeted surveys. Participants are generally reluctant to respond to all questions in a survey or they may lack info ...
We consider the model selection consistency or sparsistency of a broad set of ℓ1-regularized M-estimators for linear and non-linear statistical models in a unified fashion. For this purpose, we propose the local structured smoothness condition (LSS ...
We consider online predictions of vote results, where regions across a country vote on an issue under discussion. Such online predictions before and during the day of the vote are useful to media agencies, polling institutes, and political parties, e.g., t ...
Bartering is a timeless practice that is becoming increasingly popular on the Web. Recommending trades for an online bartering platform shares many similarities with traditional approaches to recommendation, in particular the need to model the preferences ...