Combining robustness and recovery for airline schedules
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The understanding of physical dynamics is crucial to provide scientifically credible information on lake ecosystem management. We show how the combination of in situ observations, remote sensing data, and three-dimensional hydrodynamic (3D) numerical simul ...
This paper considers safe robot mission planning in uncertain dynamical environments. This problem arises in applications such as surveillance, emergency rescue, and autonomous driving. It is a challenging problem due to mod-eling and integrating dynamical ...
The objective of this thesis is to develop a general methodology to incorporate a disaggregate demand representation in supply-oriented optimization problems that allows to capture the interplay between the behavior of individuals and the decisions to be o ...
In this thesis we investigate a number of problems related to 2-level polytopes, in particular from the point of view of the combinatorial structure and the extension complexity. 2-level polytopes were introduced as a generalization of stable set polytopes ...
The problem of control synthesis to maximize the probability of satisfying automata specifications for systems with uncertainty is addressed. Two types of uncertainty are considered; stochasticity in the dynamical system and in the sets defining the specif ...
String matching is the problem of deciding whether a given n-bit string contains a given k-bit pattern. We study the complexity of this problem in three settings. - Communication complexity. For small k, we provide near-optimal upper and lower bounds on th ...
Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik GmbH, Wadern/Saarbruecken, Germany2019
Pre-training complex language models is essential for the success of the recent methods such as BERT or OpenAI GPT. Their size makes not only the pre-training phase, but also consecutive applications to be computationally expensive. BERT-like models excel ...
It was previously shown that the problem of verifying whether a finite concurrent system is linearizable can be done with an EXPSPACE complexity. However, the best known lower bound is PSPACE-hardness, and can be obtained using a reduction from control-sta ...
We provide a framework for the sparse approximation of multilinear problems and show that several problems in uncertainty quantification fit within this framework. In these problems, the value of a multilinear map has to be approximated using approximation ...
Advances in experimental techniques and computational power allowing researchers to gather anatomical and electrophysiological data at unprecedented levels of detail have fostered the development of increasingly complex models in computational neuroscience ...