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ICML
2004
IEEE
14 years 3 months ago
Kernel-based discriminative learning algorithms for labeling sequences, trees, and graphs
We introduce a new perceptron-based discriminative learning algorithm for labeling structured data such as sequences, trees, and graphs. Since it is fully kernelized and uses poin...
Hisashi Kashima, Yuta Tsuboi
LREC
2008
130views Education» more  LREC 2008»
13 years 11 months ago
ParsCit: an Open-source CRF Reference String Parsing Package
We describe ParsCit, a freely available, open-source implementation of a reference string parsing package. At the core of ParsCit is a trained conditional random field (CRF) model...
Isaac G. Councill, C. Lee Giles, Min-Yen Kan
ICASSP
2010
IEEE
13 years 10 months ago
Predicting interruptions in dyadic spoken interactions
Interruptions occur frequently in spontaneous conversations, and they are often associated with changes in the flow of conversation. Predicting interruption is essential in the d...
Chi-Chun Lee, Shrikanth Narayanan
IJCV
2008
266views more  IJCV 2008»
13 years 10 months ago
Learning to Recognize Objects with Little Supervision
This paper shows (i) improvements over state-of-the-art local feature recognition systems, (ii) how to formulate principled models for automatic local feature selection in object c...
Peter Carbonetto, Gyuri Dorkó, Cordelia Sch...
JMLR
2010
153views more  JMLR 2010»
13 years 4 months ago
Generalized Expectation Criteria for Semi-Supervised Learning with Weakly Labeled Data
In this paper, we present an overview of generalized expectation criteria (GE), a simple, robust, scalable method for semi-supervised training using weakly-labeled data. GE fits m...
Gideon S. Mann, Andrew McCallum