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» TildeCRF: Conditional Random Fields for Logical Sequences
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JMLR
2008
230views more  JMLR 2008»
13 years 7 months ago
Exponentiated Gradient Algorithms for Conditional Random Fields and Max-Margin Markov Networks
Log-linear and maximum-margin models are two commonly-used methods in supervised machine learning, and are frequently used in structured prediction problems. Efficient learning of...
Michael Collins, Amir Globerson, Terry Koo, Xavier...
AVSS
2006
IEEE
14 years 1 months ago
A Random Field Model for Improved Feature Extraction and Tracking
This paper presents a novel method for illuminationinvariant and contrast preserving feature extraction, aimed at improving performance of tracking under complex light condition. ...
Xiaotong Yuan, Stan Z. Li
SETA
2004
Springer
126views Mathematics» more  SETA 2004»
14 years 27 days ago
Algebraic Feedback Shift Registers Based on Function Fields
We study algebraic feedback shift registers (AFSRs) based on quotients of polynomial rings in several variables over a finite field. These registers are natural generalizations o...
Andrew Klapper
CVPR
2003
IEEE
14 years 9 months ago
Video Segmentation Based on Graphical Models
This paper proposes a unified framework for spatiotemporal segmentation of video sequences. A Bayesian network is presented to model the interactions among the motion vector field...
Kia-Fock Loe, Tele Tan, Yang Wang 0002
SIAMIS
2010
378views more  SIAMIS 2010»
13 years 2 months ago
Global Interactions in Random Field Models: A Potential Function Ensuring Connectedness
Markov random field (MRF) models, including conditional random field models, are popular in computer vision. However, in order to be computationally tractable, they are limited to ...
Sebastian Nowozin, Christoph H. Lampert