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109
Voted
LREC
2010
154views Education» more  LREC 2010»
15 years 4 months ago
Improving Proper Name Recognition by Adding Automatically Learned Pronunciation Variants to the Lexicon
This paper deals with the task of large vocabulary proper name recognition. In order to accomodate a wide diversity of possible name pronunciations (due to non-native name origins...
Bert Réveil, Jean-Pierre Martens, Henk van ...
ICCV
2011
IEEE
14 years 3 months ago
Human Action Recognition by Learning Bases of Action Attributes and Parts
In this work, we propose to use attributes and parts for recognizing human actions in still images. We define action attributes as the verbs that describe the properties of human...
Bangpeng Yao, Xiaoye Jiang, Aditya Khosla, Andy La...
140
Voted
ICML
1999
IEEE
16 years 4 months ago
Monte Carlo Hidden Markov Models: Learning Non-Parametric Models of Partially Observable Stochastic Processes
We present a learning algorithm for non-parametric hidden Markov models with continuous state and observation spaces. All necessary probability densities are approximated using sa...
Sebastian Thrun, John Langford, Dieter Fox
126
Voted
ACTAC
2006
126views more  ACTAC 2006»
15 years 3 months ago
Named Entity Recognition for Hungarian Using Various Machine Learning Algorithms
In this paper we introduce a statistical Named Entity recognizer (NER) system for the Hungarian language. We examined three methods for identifying and disambiguating proper nouns...
Richárd Farkas, György Szarvas, Andr&a...
138
Voted
KDD
2004
ACM
132views Data Mining» more  KDD 2004»
16 years 3 months ago
A probabilistic framework for semi-supervised clustering
Unsupervised clustering can be significantly improved using supervision in the form of pairwise constraints, i.e., pairs of instances labeled as belonging to same or different clu...
Sugato Basu, Mikhail Bilenko, Raymond J. Mooney