98 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- ETH ZurichCH4 papers
- École Polytechnique Fédérale de LausanneCH2 papers
- Columbia UniversityUS1 paper
- Institute for Dynamic Systems and ControlCH1 paper
- Institute of Robotics and Intelligent SystemsCH1 paper
- Novartis Institutes for BioMedical Research1 paper
- Swiss Data Science CenterCH1 paper
- Swiss Federal Laboratories for Materials Science and TechnologyCH1 paper
- University of California, BerkeleyUS1 paper
- University of IdahoUS1 paper
5 papers
How Bad is Selfish Driving? Bounding the Inefficiency of Equilibria in Urban Driving Games
Alessandro Zanardi, Pier Giuseppe Sessa, Nando Käslin +3
We consider the interaction among agents engaging in a driving task and we model it as general-sum game. This class of games exhibits a plurality of different equilibria posing the…
Facilitated machine learning for image-based fruit quality assessment
Manuel Knott, Fernando Perez-Cruz, Thijs Defraeye
Image-based machine learning models can be used to make the sorting and grading of agricultural products more efficient. In many regions, implementing such systems can be difficult…
Convex Regression in Multidimensions: Suboptimality of Least Squares Estimators
Gil Kur, Fuchang Gao, Adityanand Guntuboyina +1
Under the usual nonparametric regression model with Gaussian errors, Least Squares Estimators (LSEs) over natural subclasses of convex functions are shown to be suboptimal for esti…
Forecasting intracranial hypertension using multi-scale waveform metrics
Matthias Hüser, Adrian Kündig, Walter Karlen +2
Objective: Acute intracranial hypertension is an important risk factor of secondary brain damage after traumatic brain injury. Hypertensive episodes are often diagnosed reactively,…
Correlations between thresholds and degrees: An analytic approach to model attacks and failure cascades
Rebekka Burkholz, Frank Schweitzer
Two node variables determine the evolution of cascades in random networks: a node's degree and threshold. Correlations between both fundamentally change the robustness of a network…