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» Supervised feature selection via dependence estimation
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BVAI
2005
Springer
14 years 27 days ago
Learning Location Invariance for Object Recognition and Localization
A visual system not only needs to recognize a stimulus, it also needs to find the location of the stimulus. In this paper, we present a neural network model that is able to genera...
Gwendid T. van der Voort van der Kleij, Frank van ...
WSCG
2004
163views more  WSCG 2004»
13 years 8 months ago
Fairing of Polygon Meshes Via Bayesian Discriminant Analysis
Design of an anisotropic diffusion-based filter that performs Bayesian classification for automatic selection of a proper weight for fairing polygon meshes is proposed. The data a...
Chun-Yen Chen, Kuo-Young Cheng, Hong-Yuan Mark Lia...
EMNLP
2011
12 years 7 months ago
Structured Relation Discovery using Generative Models
We explore unsupervised approaches to relation extraction between two named entities; for instance, the semantic bornIn relation between a person and location entity. Concretely, ...
Limin Yao, Aria Haghighi, Sebastian Riedel, Andrew...
IJCAI
2007
13 years 8 months ago
Document Summarization Using Conditional Random Fields
Many methods, including supervised and unsupervised algorithms, have been developed for extractive document summarization. Most supervised methods consider the summarization task ...
Dou Shen, Jian-Tao Sun, Hua Li, Qiang Yang, Zheng ...
CGF
2008
75views more  CGF 2008»
13 years 7 months ago
Extraction Of Feature Lines On Surface Meshes Based On Discrete Morse Theory
We present an approach for extracting extremal feature lines of scalar indicators on surface meshes, based on discrete Morse Theory. By computing initial Morse-Smale complexes of ...
Jan Sahner, Britta Weber, Steffen Prohaska, Hans L...