Markov decisionprocesses(MDPs) haveproven to be popular models for decision-theoretic planning, but standard dynamic programming algorithms for solving MDPs rely on explicit, stat...
Sparse coding—that is, modelling data vectors as sparse linear combinations of basis elements—is widely used in machine learning, neuroscience, signal processing, and statisti...
Julien Mairal, Francis Bach, Jean Ponce, Guillermo...
We initiate the study of the smoothed complexity of the Closest String problem by proposing a semi-random model of Hamming distance. We restrict interest to the optimization versio...
Abstract. We propose a formal definition of the robustness of association rules for interestingness measures. It is a central concept in the evaluation of the rules and has only be...
Yannick Le Bras, Patrick Meyer, Philippe Lenca, St...
This paper studies the fundamental trade-off between communication cost and delay cost arising in various contexts such as control message aggregation or organization theory. An o...
Yvonne Anne Pignolet, Stefan Schmid, Roger Wattenh...