Publication
Compressibility of Deterministic and Random Infinite Sequences
Publications associées (64)
swissALPS: a Dataset for Imbalanced Land Cover Mapping in Alpine Regions
Our dataset consists of very high-resolution aerial images (50cm) and a digital elevation model (50cm) that covers approx. 2300 km2 of land above 2000m altitude in the southwestern part of Switzerland. Our land cover labels focus on alpine land cover that ...
IEEE DataPort2023Current propagation type self-consistent leader-return stroke model
A current propagation type return stroke model which is consistent with the estimated distribution of the charge on the leader channel is described. The model takes into account the dispersion of the return stroke current along the return stroke channel. T ...
2023Multiple testing with test statistics following heavy-tailed distributions
In multiple testing problems where the components come from a mixture model of noise and true effect, we seek to first test for the existence of the non-zero components, and then identify the true alternatives under a fixed significance level . Two ...
EPFL2021Influence of residual stresses on the buckling capacity of axially loaded steel columns
Over the past 60-80 years, the design methodology of steel structures comprising conventional steel profiles, such as HEA, HEB or HEM, has remained unchanged. However, during the 21st century, production methods have improved considerably. The aim of this ...
2021A Current Propagation Type Return Stroke Model Consistent with the Leader Charge Distribution
Marcos Rubinstein, Farhad Rachidi-Haeri
We describe a current propagation type return stroke model which is consistent with the estimated distribution of the charge on the leader channel. The model takes into account the dispersion of the return stroke current along the return stroke channel. Th ...
2021Robust Generalization despite Distribution Shift via Minimum Discriminating Information
Daniel Kuhn, Andreas Krause, Tobias Sutter
Training models that perform well under distribution shifts is a central challenge in machine learning. In this paper, we introduce a modeling framework where, in addition to training data, we have partial structural knowledge of the shifted test distribut ...
2021Fractional extreme distributions
We consider three classes of linear differential equations on distribution functions, with a fractional order alpha is an element of [0; 1]. The integer case alpha = 1 corresponds to the three classical extreme families. In general, we show that there is a ...
2020From Data to Decisions: Distributionally Robust Optimization is Optimal
Daniel Kuhn, Peyman Mohajerin Esfahani
We study stochastic programs where the decision-maker cannot observe the distribution of the exogenous uncertainties but has access to a finite set of independent samples from this distribution. In this setting, the goal is to find a procedure that transfo ...
2020The probability of intransitivity in dice and close elections
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 ...
2020Inference on the Angular Distribution of Extremes
The spectral distribution plays a key role in the statistical modelling of multivariate extremes, as it defines the dependence structure of multivariate extreme-value distributions and characterizes the limiting distribution of the relative sizes of the co ...
EPFL2020