Sciweavers

ALT
2010
Springer
13 years 5 months ago
Towards General Algorithms for Grammatical Inference
Many algorithms for grammatical inference can be viewed as instances of a more general algorithm which maintains a set of primitive elements, which distributionally define sets of ...
Alexander Clark
ECAI
2008
Springer
13 years 5 months ago
Hierarchical explanation of inference in Bayesian networks that represent a population of independent agents
This paper describes a novel method for explaining Bayesian network (BN) inference when the network is modeling a population of conditionally independent agents, each of which is m...
Peter Sutovskú, Gregory F. Cooper
CPAIOR
2008
Springer
13 years 5 months ago
The Accuracy of Search Heuristics: An Empirical Study on Knapsack Problems
Theoretical models for the evaluation of quickly improving search strategies, like limited discrepancy search, are based on specific assumptions regarding the probability that a va...
Daniel H. Leventhal, Meinolf Sellmann
FLAIRS
2007
13 years 6 months ago
Guiding Inference with Policy Search Reinforcement Learning
Symbolic reasoning is a well understood and effective approach to handling reasoning over formally represented knowledge; however, simple symbolic inference systems necessarily sl...
Matthew E. Taylor, Cynthia Matuszek, Pace Reagan S...
AAAI
2007
13 years 6 months ago
Hybrid Inference for Sensor Network Localization Using a Mobile Robot
In this paper, we consider a hybrid solution to the sensor network position inference problem, which combines a real-time filtering system with information from a more expensive,...
Dimitri Marinakis, David Meger, Ioannis M. Rekleit...
AAAI
2008
13 years 6 months ago
Lifted First-Order Belief Propagation
Unifying first-order logic and probability is a long-standing goal of AI, and in recent years many representations combining aspects of the two have been proposed. However, infere...
Parag Singla, Pedro Domingos
AAAI
2008
13 years 6 months ago
Latent Tree Models and Approximate Inference in Bayesian Networks
We propose a novel method for approximate inference in Bayesian networks (BNs). The idea is to sample data from a BN, learn a latent tree model (LTM) from the data offline, and wh...
Yi Wang, Nevin Lianwen Zhang, Tao Chen
AAAI
2008
13 years 6 months ago
Incremental Algorithms for Approximate Compilation
Compilation is an important approach to a range of inference problems, since it enables linear-time inference in the size S of the compiled representation. However, the main drawb...
Alberto Venturini, Gregory M. Provan
EUROSSC
2009
Springer
13 years 6 months ago
Using Dempster-Shafer Theory of Evidence for Situation Inference
Abstract. In the domain of ubiquitous computing, the ability to identify the occurrence of situations is a core function of being ’contextaware’. Given the uncertain nature of ...
Susan McKeever, Juan Ye, Lorcan Coyle, Simon A. Do...
FGR
2004
IEEE
129views Biometrics» more  FGR 2004»
13 years 7 months ago
Multiple Frame Motion Inference Using Belief Propagation
We present an algorithm for automatic inference of human upper body motion. A graph model is proposed for inferring human motion, and motion inference is posed as a mapping proble...
Jiang Gao, Jianbo Shi