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TCS
2008
15 years 24 days ago
Kernel methods for learning languages
This paper studies a novel paradigm for learning formal languages from positive and negative examples which consists of mapping strings to an appropriate highdimensional feature s...
Leonid Kontorovich, Corinna Cortes, Mehryar Mohri
SDM
2011
SIAM
370views Data Mining» more  SDM 2011»
14 years 3 months ago
Sparse Latent Semantic Analysis
Latent semantic analysis (LSA), as one of the most popular unsupervised dimension reduction tools, has a wide range of applications in text mining and information retrieval. The k...
Xi Chen, Yanjun Qi, Bing Bai, Qihang Lin, Jaime G....
119
Voted
ECCV
2004
Springer
15 years 6 months ago
Principal Geodesic Analysis on Symmetric Spaces: Statistics of Diffusion Tensors
Diffusion tensor magnetic resonance imaging (DT-MRI) is emerging as an important tool in medical image analysis of the brain. However, relatively little work has been done on produ...
P. Thomas Fletcher, Sarang C. Joshi
111
Voted
QI
2009
Springer
190views Physics» more  QI 2009»
15 years 7 months ago
Characterizing Pure High-Order Entanglements in Lexical Semantic Spaces via Information Geometry
An emerging topic in Quantuam Interaction is the use of lexical semantic spaces, as Hilbert spaces, to capture the meaning of words. There has been some initial evidence that the p...
Yuexian Hou, Dawei Song
CVPR
2008
IEEE
16 years 2 months ago
Scene classification with low-dimensional semantic spaces and weak supervision
A novel approach to scene categorization is proposed. Similar to previous works of [11, 15, 3, 12], we introduce an intermediate space, based on a low dimensional semantic "t...
Nikhil Rasiwasia, Nuno Vasconcelos