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» Statistical Modelling of CSP Solving Algorithms Performance
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ANSS
1996
IEEE
15 years 2 months ago
Computation of the Asymptotic Bias and Variance for Simulation of Markov Reward Models
The asymptotic bias and variance are important determinants of the quality of a simulation run. In particular, the asymptotic bias can be used to approximate the bias introduced b...
Aad P. A. van Moorsel, Latha A. Kant, William H. S...
AI
2007
Springer
14 years 10 months ago
Learning action models from plan examples using weighted MAX-SAT
AI planning requires the definition of action models using a formal action and plan description language, such as the standard Planning Domain Definition Language (PDDL), as inp...
Qiang Yang, Kangheng Wu, Yunfei Jiang
ICML
2010
IEEE
14 years 11 months ago
Simple and Efficient Multiple Kernel Learning by Group Lasso
We consider the problem of how to improve the efficiency of Multiple Kernel Learning (MKL). In literature, MKL is often solved by an alternating approach: (1) the minimization of ...
Zenglin Xu, Rong Jin, Haiqin Yang, Irwin King, Mic...
SIAMIS
2011
14 years 5 months ago
Large Scale Bayesian Inference and Experimental Design for Sparse Linear Models
Abstract. Many problems of low-level computer vision and image processing, such as denoising, deconvolution, tomographic reconstruction or superresolution, can be addressed by maxi...
Matthias W. Seeger, Hannes Nickisch
VLDB
2004
ACM
104views Database» more  VLDB 2004»
15 years 10 months ago
Retrieval effectiveness of an ontology-based model for information selection
Technology in the field of digital media generates huge amounts of nontextual information, audio, video, and images, along with more familiar textual information. The potential for...
Latifur Khan, Dennis McLeod, Eduard H. Hovy