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» INSPIRE: A New Method of Mapping Information Spaces
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AAAI
2010
13 years 7 months ago
Searching Without a Heuristic: Efficient Use of Abstraction
g Without a Heuristic: Efficient Use of Abstraction Bradford Larsen, Ethan Burns, Wheeler Ruml Department of Computer Science University of New Hampshire Durham, NH 03824 USA blars...
Bradford John Larsen, Ethan Burns, Wheeler Ruml, R...
SAC
2006
ACM
13 years 5 months ago
Combining supervised and unsupervised monitoring for fault detection in distributed computing systems
Fast and accurate fault detection is becoming an essential component of management software for mission critical systems. A good fault detector makes possible to initiate repair a...
Haifeng Chen, Guofei Jiang, Cristian Ungureanu, Ke...
TMI
2002
248views more  TMI 2002»
13 years 5 months ago
Adaptive Elastic Segmentation of Brain MRI via Shape Model Guided Evolutionary Programming
This paper presents a fully automated segmentation method for medical images. The goal is to localize and parameterize a variety of types of structure in these images for subsequen...
Alain Pitiot, Arthur W. Toga, Paul M. Thompson
PRL
2010
188views more  PRL 2010»
13 years 4 months ago
Sparsity preserving discriminant analysis for single training image face recognition
: Single training image face recognition is one of main challenges to appearance-based pattern recognition techniques. Many classical dimensionality reduction methods such as LDA h...
Lishan Qiao, Songcan Chen, Xiaoyang Tan
JMLR
2011
192views more  JMLR 2011»
13 years 22 days ago
Minimum Description Length Penalization for Group and Multi-Task Sparse Learning
We propose a framework MIC (Multiple Inclusion Criterion) for learning sparse models based on the information theoretic Minimum Description Length (MDL) principle. MIC provides an...
Paramveer S. Dhillon, Dean P. Foster, Lyle H. Unga...