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LREC
2010
197views Education» more  LREC 2010»
13 years 10 months ago
Automatic Annotation of Co-Occurrence Relations
We introduce a method for automatically labelling edges of word co-occurrence graphs with semantic relations. Therefore we only make use of training data already contained within ...
Dirk Goldhahn, Uwe Quasthoff
NIPS
2008
13 years 10 months ago
Unlabeled data: Now it helps, now it doesn't
Empirical evidence shows that in favorable situations semi-supervised learning (SSL) algorithms can capitalize on the abundance of unlabeled training data to improve the performan...
Aarti Singh, Robert D. Nowak, Xiaojin Zhu
NIPS
2008
13 years 10 months ago
Hierarchical Semi-Markov Conditional Random Fields for Recursive Sequential Data
Inspired by the hierarchical hidden Markov models (HHMM), we present the hierarchical semi-Markov conditional random field (HSCRF), a generalisation of embedded undirected Markov ...
Tran The Truyen, Dinh Q. Phung, Hung Hai Bui, Svet...
ENTCS
2010
133views more  ENTCS 2010»
13 years 9 months ago
Towards Measurable Types for Dynamical Process Modeling Languages
Process modeling languages such as "Dynamical Grammars" are highly expressive in the processes they model using stochastic and deterministic dynamical systems, and can b...
Eric Mjolsness
IJCV
2008
151views more  IJCV 2008»
13 years 9 months ago
Describing Visual Scenes Using Transformed Objects and Parts
We develop hierarchical, probabilistic models for objects, the parts composing them, and the visual scenes surrounding them. Our approach couples topic models originally developed...
Erik B. Sudderth, Antonio Torralba, William T. Fre...