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COLT
2000
Springer
15 years 6 months ago
Average-Case Complexity of Learning Polynomials
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...
Frank Stephan, Thomas Zeugmann
116
Voted
ICGI
1998
Springer
15 years 6 months ago
Learning Stochastic Finite Automata from Experts
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...
Colin de la Higuera
126
Voted
CVPR
1997
IEEE
15 years 6 months ago
Learning Generic Prior Models for Visual Computation
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...
Song Chun Zhu, David Mumford
IAT
2009
IEEE
15 years 5 months ago
Learning in a Fixed or Evolving Network of Agents
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...
ATAL
2006
Springer
15 years 5 months ago
An adaptive plan-based dialogue agent: integrating learning into a BDI architecture
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...
Anh Nguyen, Wayne Wobcke