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» Conditional Random Fields for Object Recognition
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EMNLP
2007
14 years 11 months ago
Semi-Supervised Structured Output Learning Based on a Hybrid Generative and Discriminative Approach
This paper proposes a framework for semi-supervised structured output learning (SOL), specifically for sequence labeling, based on a hybrid generative and discriminative approach...
Jun Suzuki, Akinori Fujino, Hideki Isozaki
ECCV
2006
Springer
15 years 11 months ago
Learning and Incorporating Top-Down Cues in Image Segmentation
Abstract. Bottom-up approaches, which rely mainly on continuity principles, are often insufficient to form accurate segments in natural images. In order to improve performance, rec...
Xuming He, Richard S. Zemel, Debajyoti Ray
ICML
2005
IEEE
15 years 10 months ago
Predicting protein folds with structural repeats using a chain graph model
Protein fold recognition is a key step towards inferring the tertiary structures from amino-acid sequences. Complex folds such as those consisting of interacting structural repeat...
Yan Liu, Eric P. Xing, Jaime G. Carbonell
ICML
2003
IEEE
15 years 10 months ago
Hidden Markov Support Vector Machines
This paper presents a novel discriminative learning technique for label sequences based on a combination of the two most successful learning algorithms, Support Vector Machines an...
Yasemin Altun, Ioannis Tsochantaridis, Thomas Hofm...
ICASSP
2011
IEEE
14 years 1 months ago
Simultaneous dialog act segmentation and classification from human-human spoken conversations
An accurate identification dialog acts (DAs), which represent the illocutionary aspect of communication, is essential to support the understanding of human conversations. This re...
Silvia Quarteroni, Alexei V. Ivanov, Giuseppe Ricc...