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| In particular, big data challenges are tackled via randomised, sampling or decomposition approaches that at the same time guarantee some (expected) approximation. | In particular, big data challenges are tackled via randomised, sampling or decomposition approaches that at the same time guarantee some (expected) approximation. | ||
| - | Algorithm engineering requires thorough experimentation and evaluation of our new algorithms for real problems. We have experience with a variety of applications such as graph (network) visualisation problems, cheminformatics (drug design), bioinformatics, archeology, statistical physics, and logistic problems such as network design. | + | Algorithm engineering requires thorough experimentation and evaluation of our new algorithms for real problems. We have experience with a variety of applications such as graph (network) visualisation problems, cheminformatics (drug design), bioinformatics, archeology, statistical physics, and logistic problems such as network design and optimization. |
| ===== Group ===== | ===== Group ===== | ||