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» Learning Mid-Level Features For Recognition
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ACL
2010
13 years 5 months ago
Hierarchical Joint Learning: Improving Joint Parsing and Named Entity Recognition with Non-Jointly Labeled Data
One of the main obstacles to producing high quality joint models is the lack of jointly annotated data. Joint modeling of multiple natural language processing tasks outperforms si...
Jenny Rose Finkel, Christopher D. Manning
TNN
2011
137views more  TNN 2011»
13 years 2 months ago
Learning Pattern Recognition Through Quasi-Synchronization of Phase Oscillators
—The idea that synchronized oscillations are important in cognitive tasks is receiving significant attention. In this view, single neurons are no longer elementary computational...
Ekaterina Vassilieva, Guillaume Pinto, J. Acacio d...
AAAI
2008
13 years 9 months ago
Sketch Recognition Based on Manifold Learning
Current feature-based methods for sketch recognition systems rely on human-selected features. Certain machine learning techniques have been found to be good nonlinear features ext...
Heeyoul Choi, Tracy Hammond
ACL
2009
13 years 5 months ago
Paraphrase Recognition Using Machine Learning to Combine Similarity Measures
This paper presents three methods that can be used to recognize paraphrases. They all employ string similarity measures apshallow abstractions of the input sentences, and a Maximu...
Prodromos Malakasiotis
AMC
2007
138views more  AMC 2007»
13 years 7 months ago
An experimental comparison of machine learning for adaptive sketch recognition
Benefiting from advances in online sketchy shape recognition system could not be expected before the problem of its adaptability is well solved. In this paper, three methods of m...
Lisha Zhang, Zhengxing Sun