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» Document Summarization Using Conditional Random Fields
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ECCV
2006
Springer
14 years 9 months ago
Learning to Combine Bottom-Up and Top-Down Segmentation
Bottom-up segmentation based only on low-level cues is a notoriously difficult problem. This difficulty has lead to recent top-down segmentation algorithms that are based on class-...
Anat Levin, Yair Weiss
AAMAS
2010
Springer
13 years 7 months ago
A probabilistic multimodal approach for predicting listener backchannels
During face-to-face interactions, listeners use backchannel feedback such as head nods as a signal to the speaker that the communication is working and that they should continue sp...
Louis-Philippe Morency, Iwan de Kok, Jonathan Grat...
ICASSP
2011
IEEE
12 years 11 months ago
Combination of stochastic understanding and machine translation systems for language portability of dialogue systems
In this paper, several approaches for language portability of dialogue systems are investigated with a focus on the spoken language understanding (SLU) component. We show that the...
Bassam Jabaian, Laurent Besacier, Fabrice Lefevre
RECOMB
2006
Springer
14 years 8 months ago
CONTRAlign: Discriminative Training for Protein Sequence Alignment
In this paper, we present CONTRAlign, an extensible and fully automatic framework for parameter learning and protein pairwise sequence alignment using pair conditional random field...
Chuong B. Do, Samuel S. Gross, Serafim Batzoglou
FOIKS
2008
Springer
14 years 4 months ago
Cost-minimising strategies for data labelling : optimal stopping and active learning
Supervised learning deals with the inference of a distribution over an output or label space $\CY$ conditioned on points in an observation space $\CX$, given a training dataset $D$...
Christos Dimitrakakis, Christian Savu-Krohn