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IFM
2005
Springer
16 years 12 days ago
A Fixpoint Semantics of Event Systems With and Without Fairness Assumptions
Abstract. We present a fixpoint semantics of event systems. The semantics is presented in a general framework without concerns of fairness. Soundness and completeness of rules for...
Héctor Ruíz Barradas, Didier Bert
AAAI
2010
15 years 8 months ago
Reinforcement Learning via AIXI Approximation
This paper introduces a principled approach for the design of a scalable general reinforcement learning agent. This approach is based on a direct approximation of AIXI, a Bayesian...
Joel Veness, Kee Siong Ng, Marcus Hutter, David Si...
COGSCI
2008
65views more  COGSCI 2008»
15 years 7 months ago
A Survey of Model Evaluation Approaches With a Tutorial on Hierarchical Bayesian Methods
We review current methods for evaluating models in the cognitive sciences, including theoretically-based approaches, such as Bayes Factors and MDL measures, simulation approaches,...
Richard M. Shiffrin, Michael D. Lee, Woojae Kim, E...
EWC
2008
85views more  EWC 2008»
15 years 7 months ago
Geometry based pre-processor for parallel fluid dynamic simulations using a hierarchical basis
The pre-processing stage of finite element analysis of the Navier-Stokes equations is becoming increasingly important as the desire for more general boundary conditions, as well a...
Anil Kumar Karanam, Kenneth E. Jansen, Christian H...
NECO
2010
97views more  NECO 2010»
15 years 5 months ago
Rademacher Chaos Complexities for Learning the Kernel Problem
In this paper we develop a novel generalization bound for learning the kernel problem. First, we show that the generalization analysis of the kernel learning problem reduces to in...
Yiming Ying, Colin Campbell