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» Using Random Forests in the Structured Language Model
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ICCV
2007
IEEE
14 years 10 months ago
Steerable Random Fields
In contrast to traditional Markov random field (MRF) models, we develop a Steerable Random Field (SRF) in which the field potentials are defined in terms of filter responses that ...
Stefan Roth, Michael J. Black
JMIV
2002
122views more  JMIV 2002»
13 years 8 months ago
Markov Random Field Modeling in Median Pyramidal Transform Domain for Denoising Applications
We consider a median pyramidal transform for denoising applications. Traditional techniques of pyramidal denoising are similar to those in wavelet-based methods. In order to remove...
Ilya Gluhovsky, Vladimir P. Melnik, Ilya Shmulevic...
EMNLP
2011
12 years 8 months ago
Structured Relation Discovery using Generative Models
We explore unsupervised approaches to relation extraction between two named entities; for instance, the semantic bornIn relation between a person and location entity. Concretely, ...
Limin Yao, Aria Haghighi, Sebastian Riedel, Andrew...
IJRR
2007
186views more  IJRR 2007»
13 years 8 months ago
Extracting Places and Activities from GPS Traces Using Hierarchical Conditional Random Fields
Learning patterns of human behavior from sensor data is extremely important for high-level activity inference. We show how to extract a person’s activities and significant plac...
Lin Liao, Dieter Fox, Henry A. Kautz
NIPS
2001
13 years 10 months ago
Natural Language Grammar Induction Using a Constituent-Context Model
This paper presents a novel approach to the unsupervised learning of syntactic analyses of natural language text. Most previous work has focused on maximizing likelihood according...
Dan Klein, Christopher D. Manning