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CVPR
2011
IEEE
14 years 9 months ago
On Deep Generative Models with Applications to Recognition
The most popular way to use probabilistic models in vision is first to extract some descriptors of small image patches or object parts using well-engineered features, and then to...
Marc', Aurelio Ranzato, Joshua Susskind, Volodymyr...
CIKM
2008
Springer
15 years 3 months ago
Modeling hidden topics on document manifold
Topic modeling has been a key problem for document analysis. One of the canonical approaches for topic modeling is Probabilistic Latent Semantic Indexing, which maximizes the join...
Deng Cai, Qiaozhu Mei, Jiawei Han, Chengxiang Zhai
ANLP
1997
137views more  ANLP 1997»
15 years 2 months ago
Probabilistic and Rule-Based Tagger of an Inflective Language- a Comparison
We present results of probabilistic tagging of Czech texts in order to show how these techniques work for one of the highly morphologically ambiguous inflective languages. After d...
Jan Hajic, Barbora Hladká
DOCENG
2005
ACM
15 years 3 months ago
Injecting information into atomic units of text
This paper presents a new approach to text processing, based on textemes. These are atomic text units generalising the concepts of character and glyph by merging them in a common ...
Yannis Haralambous, Gábor Bella
ICML
2001
IEEE
16 years 2 months ago
Learning Probabilistic Models of Relational Structure
Most real-world data is stored in relational form. In contrast, most statistical learning methods work with "flat" data representations, forcing us to convert our data i...
Lise Getoor, Nir Friedman, Daphne Koller, Benjamin...