The present paper deals with the averagecase complexity of various algorithms for learning univariate polynomials. For this purpose an appropriate framework is introduced. Based o...
We present in this paper a new learning problem called learning distributions from experts. In the case we study the experts are stochastic deterministic finite automata (sdfa). W...
This paper presents a novel theory for learning generic prior models from a set of observed natural images based on a minimax entropy theory that the authors studied in modeling t...
This paper investigates incremental multiagent learning in static or evolving structured networks. Learning examples are incrementally distributed among the agents, and the object...
Gauvain Bourgne, Amal El Fallah-Seghrouchni, Henry...
We consider the problem of dialogue adaptation in our Smart Personal Assistant (SPA), which uses a plan-based dialogue model. We present a novel way of integrating learning into a...