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» Comparing Computer Models Solving Number Series Problems
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AGI
2015
3 years 1 months ago
Comparing Computer Models Solving Number Series Problems
Inductive reasoning requires to find for given instances a general rule. This makes inductive reasoning an excellent test-bed for artificial general intelligence (AGI). An exampl...
Ute Schmid, Marco Ragni
CORR
2010
Springer
171views Education» more  CORR 2010»
8 years 5 months ago
Solving Inverse Problems with Piecewise Linear Estimators: From Gaussian Mixture Models to Structured Sparsity
A general framework for solving image inverse problems is introduced in this paper. The approach is based on Gaussian mixture models, estimated via a computationally efficient MAP...
Guoshen Yu, Guillermo Sapiro, Stéphane Mall...
ICDM
2002
IEEE
133views Data Mining» more  ICDM 2002»
8 years 10 months ago
Estimating the number of segments in time series data using permutation tests
Segmentation is a popular technique for discovering structure in time series data. We address the largely open problem of estimating the number of segments that can be reliably di...
Kari Vasko, Hannu Toivonen
ICMLA
2008
8 years 6 months ago
A Bayesian Approach to Switching Linear Gaussian State-Space Models for Unsupervised Time-Series Segmentation
Time-series segmentation in the fully unsupervised scenario in which the number of segment-types is a priori unknown is a fundamental problem in many applications. We propose a Ba...
Silvia Chiappa
WSC
2008
8 years 7 months ago
Solving volume and capacity planning problems in semiconductor manufaturing: A computational study
In this paper, we suggest a linear programming formulation that allows for solving volume and capacity planning problems in semiconductor manufacturing systems. We assume a genera...
Christoph Habla, Lars Mönch
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