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» Exploiting Deep Structure
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118
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ICPR
2004
IEEE
16 years 3 months ago
Relaxation Labeling Processes for Protein Secondary Structure Prediction
The prediction of protein secondary structure is a classical problem in bioinformatics, and in the past few years several machine learning techniques have been proposed to t. From...
Giacomo Colle, Marcello Pelillo
117
Voted
ICML
2004
IEEE
16 years 3 months ago
A graphical model for protein secondary structure prediction
In this paper, we present a graphical model for protein secondary structure prediction. This model extends segmental semi-Markov models (SSMM) to exploit multiple sequence alignme...
Wei Chu, Zoubin Ghahramani, David L. Wild
145
Voted
CISS
2008
IEEE
15 years 9 months ago
Threshold structure of channel aware distributed scheduling in ad-hoc networks: An optimal stopping view
— As evidenced by measurement data, channel fading and co-channel interference occur on the same time scales, and it is therefore difficult to determine if packet losses are due...
Junshan Zhang
90
Voted
ICTAI
2008
IEEE
15 years 9 months ago
Finding Good Starting Points for Solving Structured and Unstructured Nonlinear Constrained Optimization Problems
In this paper, we develop heuristics for finding good starting points when solving large-scale nonlinear constrained optimization problems (COPs). We focus on nonlinear programmi...
Soomin Lee, Benjamin W. Wah
CVPR
2007
IEEE
15 years 9 months ago
High Distortion and Non-Structural Image Matching via Feature Co-occurrence
We propose a novel approach for determining if a pair of images match each other under the effect of a highdistortion transformation or non-structural relation. The co-occurrence ...
Xi Chen, Tat-Jen Cham