113 search results - page 12 / 23 » Average-Case Complexity of Learning Polynomials |
88
Voted
ATAL
2006
Springer
15 years 1 months ago
2006
Springer
Factored representations, model-based learning, and hierarchies are well-studied techniques for improving the learning efficiency of reinforcement-learning algorithms in large-sca...
FOCS
2008
IEEE
15 years 4 months ago
2008
IEEE
Learning problems form an important category of computational tasks that generalizes many of the computations researchers apply to large real-life data sets. We ask: what concept ...
ICML
2008
IEEE
15 years 10 months ago
2008
IEEE
Rich representations in reinforcement learning have been studied for the purpose of enabling generalization and making learning feasible in large state spaces. We introduce Object...
NIPS
2007
14 years 11 months ago
2007
This contribution develops a theoretical framework that takes into account the effect of approximate optimization on learning algorithms. The analysis shows distinct tradeoffs for...
COCO
2010
Springer
15 years 1 months ago
2010
Springer
Abstract—We consider two natural extensions of the communication complexity model that are inspired by distributed computing. In both models, two parties are equipped with synchr...