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176
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CVPR
2007
IEEE
16 years 8 months ago
Learning Gaussian Conditional Random Fields for Low-Level Vision
Markov Random Field (MRF) models are a popular tool for vision and image processing. Gaussian MRF models are particularly convenient to work with because they can be implemented u...
Marshall F. Tappen, Ce Liu, Edward H. Adelson, Wil...
GECCO
2003
Springer
100views Optimization» more  GECCO 2003»
15 years 11 months ago
Dense and Switched Modular Primitives for Bond Graph Model Design
This paper suggests dense and switched modular primitives for a bond-graph-based GP design framework that automatically synthesizes designs for multi-domain, lumped parameter dynam...
Kisung Seo, Zhun Fan, Jianjun Hu, Erik D. Goodman,...
ICDAR
2009
IEEE
15 years 4 months ago
Using Kernel Density Classifier with Topic Model and Cost Sensitive Learning for Automatic Text Categorization
This paper proposes a novel framework for automatic text categorization problem based on the kernel density classifier. The overall goal is to tackle two main issues in automatic ...
Dwi Sianto Mansjur, Ted S. Wada, Biing-Hwang Juang
INFOCOM
2000
IEEE
15 years 10 months ago
A Predictability Analysis of Network Traffic
This paper assesses the predictability of network traffic by considering two metrics: (1) how far into the future a traffic rate process can be predicted with bounded error; (2) w...
Aimin Sang, San-qi Li
160
Voted
ICASSP
2011
IEEE
14 years 10 months ago
Sentence simplification for spoken language understanding
In this paper, we present a sentence simplification method and demonstrate its use to improve intent determination and slot filling tasks in spoken language understanding (SLU) ...
Gökhan Tür, Dilek Hakkani-Tür, Larr...