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» Unsupervised Learning Using MML
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ICCV
2005
IEEE
14 years 10 months ago
Combining Generative Models and Fisher Kernels for Object Recognition
Learning models for detecting and classifying object categories is a challenging problem in machine vision. While discriminative approaches to learning and classification have, in...
Alex Holub, Max Welling, Pietro Perona
SIGIR
2009
ACM
14 years 3 months ago
Named entity recognition in query
This paper addresses the problem of Named Entity Recognition in Query (NERQ), which involves detection of the named entity in a given query and classification of the named entity...
Jiafeng Guo, Gu Xu, Xueqi Cheng, Hang Li
TCSV
2008
175views more  TCSV 2008»
13 years 8 months ago
Expandable Data-Driven Graphical Modeling of Human Actions Based on Salient Postures
This paper presents a graphical model for learning and recognizing human actions. Specifically, we propose to encode actions in a weighted directed graph, referred to as action gra...
Wanqing Li, Zhengyou Zhang, Zicheng Liu
FLAIRS
2008
13 years 11 months ago
Learning in the Lexical-Grammatical Interface
Children are facile at both discovering word boundaries and using those words to build higher-level structures in tandem. Current research treats lexical acquisition and grammar i...
Tom Armstrong, Tim Oates
SDM
2010
SIAM
259views Data Mining» more  SDM 2010»
13 years 10 months ago
Semi-supervised Bio-named Entity Recognition with Word-Codebook Learning
We describe a novel semi-supervised method called WordCodebook Learning (WCL), and apply it to the task of bionamed entity recognition (bioNER). Typical bioNER systems can be seen...
Pavel P. Kuksa, Yanjun Qi