Abstract. We tackle the problem of multi-class relational sequence learning using relevant patterns discovered from a set of labelled sequences. To deal with this problem, firstly...
Nicola Di Mauro, Teresa Maria Altomare Basile, Ste...
— We present an algorithm that probabilistically covers a bounded region of the state space of a nonlinear system with a sparse tree of feedback stabilized trajectories leading t...
We develop multiattribute auctions that accommodate generalized additive independent (GAI) preferences. We propose an iterative auction mechanism that maintains prices on potentia...
Information networks are widely used to characterize the relationships between data items such as text documents. Many important retrieval and mining tasks rely on ranking the dat...
We study observation-based strategies for partially-observable Markov decision processes (POMDPs) with parity objectives. An observationbased strategy relies on partial information...
Krishnendu Chatterjee, Laurent Doyen, Thomas A. He...