Robust Sparse Voting

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Parliament dynamics might seem erratic at times. Predicting future voting patterns could support policy design based on the simulation of voting scenarios. The availability of open data on legislative activities and machine learning tools might enable such ...

Poor decisions and selfish behaviors give rise to seemingly intractable global problems, such as the lack of transparency in democratic processes, the spread of conspiracy theories, and the rise in greenhouse gas emissions. However, people are more predict ...

This thesis is composed of two essays that study the effectiveness of shareholder democracy. In the first essay, I analyze the firm value implications of shareholder-initiated proposals. I show that managerial resistance precludes half of shareholder-init ...

While technology is often claimed to be “democratizing”, the technologizing of society has more often yielded undemocratic or even anti-democratic outcomes. Is technology fundamentally at odds with democracy, or is it merely a rich and infinitely-adaptable ...

We introduce a comprehensive benchmark for local features and robust estimation algorithms, focusing on the downstream task-the accuracy of the reconstructed camera pose-as our primary metric. Our pipeline's modular structure allows easy integration, confi ...

We study the phenomenon of intransitivity in models of dice and voting. First, we follow a recent thread of research for n-sided dice with pairwise ordering induced by the probability, relative to 1/2, that a throw from one die is higher than the other. We ...

The strongest threat model for voting systems considers coercion resistance: protection against coercers that force voters to modify their votes, or to abstain. Existing remote voting systems either do not provide this property; require expensive operation ...

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 ...

Voting can abstractly model any decision-making scenario and as such it has been extensively studied over the decades. Recently, the related literature has focused on quantifying the impact of utilizing only limited information in the voting process on the ...

Scholarly studies and common accounts of national politics enjoy pointing out the resilience of ideological divides among populations. Building on the image of political cleavages and geographic polarization, the regionalization of politics has become a tr ...

The combination of Global Navigation Satellite Systems (GNSS) and Inertial Navigation System (INS) has become the baseline of many vehicular applications. However, in challenging GNSS scenarios, classical GNSS/INS integration estimators are very sensitive ...

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 ...

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 ...

Switzerland has a long tradition of direct democracy, which makes it an ideal laboratory for research on real-world politics. Similar to recent open government initiatives launched worldwide, the Swiss government regularly releases datasets related to stat ...

A new method for robust fixed-order H∞ controller design for uncertain time-delayed MIMO systems is presented. It is shown that the H∞ robust performance condition can be represented by a set of convex constraints with respect to the parameters of a linear ...

Bayesian estimation problems involving Gaussian distributions often result in linear estimation techniques. Nevertheless, there are no general statements as to whether the linearity of the Bayesian estimator is restricted to the Gaussian case. The two comm ...

Accurate segmentation of lymph nodes in head and neck (H&N) CT images is essential for the radiotherapy planning of the H&N cancer. Atlas-based segmentation methods are widely used for the automated segmentation of such structures. Multi-atlas approaches a ...

In recent years, multi-atlas fusion methods have gained significant attention in medical image segmentation. In this paper, we propose a general Markov Random Field (MRF) based framework that can perform edge-preserving smoothing of the labels at the time ...

A networked set of agents holding binary opinions does not seem to be able to compute its majority opinion by means of local binary interactions only. However, the majority problem can be solved using two or more bits, instead of one [1]. Pairs of agents a ...

We show how to express an arbitrary integer interval

I = [0, H]

as a sumset

I = \sum_{i=1}^\ell G_i * [0, u - 1] + [0, H']

of smaller integer intervals for some small values

\ell

u

, and

H' < u - 1

, where

b * A = \{b a : a \in A\}

and $A + B = ...

Robust Sparse Voting

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Predicting party switching through machine learning and open data

Discrete-Choice Mining of Social Processes

Empirical Evidence on the Effectiveness of Shareholder Democracy

Technologizing Democracy or Democratizing Technology? A Layered-Architecture Perspective on Potentials and Challenges

Image Matching Across Wide Baselines: From Paper to Practice

The probability of intransitivity in dice and close elections

VOTEAGAIN: A scalable coercion-resistant voting system

Wasserstein Distributionally Robust Learning

The Distortion of Distributed Voting

The geographic evolution of political cleavages in Switzerland: A network approach to assessing levels and dynamics of polarization between local populations

Tightly Coupled GNSS/INS Integration based on Robust M-Estimators

Moral Matrices : Space Through the Unfolding of Direct Democracy in Switzerland

Online Collaborative Prediction of Regional Vote Results

Mining Democracy

H∞ smith predictor design for time-delayed MIMO systems via convex optimization

On the Linearity of Bayesian Interpolators for Non-Gaussian Continuous-Time AR(1) Processes

Evaluation of Atlas Fusion Strategies for Segmentation of Head and Neck Lymph Nodes for Radiotherapy Planning

Fusion of Multi-Atlas Segmentations with Spatial Distribution Modeling

The Distributed Multiple Voting Problem

Additive Combinatorics and Discrete Logarithm Based Range Protocols