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» Efficient Piecewise Learning for Conditional Random Fields
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CVPR
2010
IEEE
15 years 11 months ago
Automatic Discovery of Meaningful Object Parts with Latent CRFs
Object recognition is challenging due to high intra-class variability caused, e.g., by articulation, viewpoint changes, and partial occlusion. Successful methods need to strike a...
Paul Schnitzspan, Stefan Roth, Bernt Schiele
ACL
2006
15 years 4 months ago
Combining Statistical and Knowledge-Based Spoken Language Understanding in Conditional Models
Spoken Language Understanding (SLU) addresses the problem of extracting semantic meaning conveyed in an utterance. The traditional knowledge-based approach to this problem is very...
Ye-Yi Wang, Alex Acero, Milind Mahajan, John Lee
NIPS
2003
15 years 4 months ago
Discriminative Fields for Modeling Spatial Dependencies in Natural Images
In this paper we present Discriminative Random Fields (DRF), a discriminative framework for the classification of natural image regions by incorporating neighborhood spatial depe...
Sanjiv Kumar, Martial Hebert
ACL
2009
15 years 1 months ago
Efficient Inference of CRFs for Large-Scale Natural Language Data
This paper presents an efficient inference algorithm of conditional random fields (CRFs) for large-scale data. Our key idea is to decompose the output label state into an active s...
Minwoo Jeong, Chin-Yew Lin, Gary Geunbae Lee
ACL
2012
13 years 5 months ago
Learning to Find Translations and Transliterations on the Web
In this paper, we present a new method for learning to finding translations and transliterations on the Web for a given term. The approach involves using a small set of terms and ...
Joseph Z. Chang, Jason S. Chang, Jyh-Shing Roger J...