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» Evaluating learning algorithms and classifiers
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ESWA
2008
140views more  ESWA 2008»
15 years 18 days ago
Web taxonomy integration with hierarchical shrinkage algorithm and fine-grained relations
We address the problem of integrating web taxonomies from different real Internet applications. Integrating web taxonomies is to transfer instances from a source to target taxonom...
Chia-Wei Wu, Richard Tzong-Han Tsai, Cheng-Wei Lee...
92
Voted
ACL
2004
15 years 1 months ago
Deep Dependencies from Context-Free Statistical Parsers: Correcting the Surface Dependency Approximation
We present a linguistically-motivated algorithm for reconstructing nonlocal dependency in broad-coverage context-free parse trees derived from treebanks. We use an algorithm based...
Roger Levy, Christopher D. Manning
104
Voted
ICML
2007
IEEE
16 years 1 months ago
Bottom-up learning of Markov logic network structure
Markov logic networks (MLNs) are a statistical relational model that consists of weighted firstorder clauses and generalizes first-order logic and Markov networks. The current sta...
Lilyana Mihalkova, Raymond J. Mooney
173
Voted
CVPR
2009
IEEE
16 years 7 months ago
Towards Total Scene Understanding: Classification, Annotation and Segmentation in an Automatic Framework
Given an image, we propose a hierarchical generative model that classifies the overall scene, recognizes and segments each object component, as well as annotates the image with ...
Fei-Fei Li 0002, Li-Jia Li, Richard Socher
181
Voted
CVPR
2001
IEEE
16 years 2 months ago
Rapid Object Detection using a Boosted Cascade of Simple Features
This paper describes a machine learning approach for visual object detection which is capable of processing images extremely rapidly and achieving high detection rates. This wor...
Paul A. Viola, Michael J. Jones