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» Unsupervised Learning Using MML
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ICCV
2005
IEEE
16 years 3 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
15 years 8 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»
15 years 1 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
15 years 3 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»
15 years 2 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