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BMCBI
2005
89views more  BMCBI 2005»
13 years 8 months ago
An empirical analysis of training protocols for probabilistic gene finders
Background: Generalized hidden Markov models (GHMMs) appear to be approaching acceptance as a de facto standard for state-of-the-art ab initio gene finding, as evidenced by the re...
William H. Majoros, Steven Salzberg
SDM
2009
SIAM
149views Data Mining» more  SDM 2009»
14 years 6 months ago
Near-optimal Supervised Feature Selection among Frequent Subgraphs.
Graph classification is an increasingly important step in numerous application domains, such as function prediction of molecules and proteins, computerised scene analysis, and an...
Alexander J. Smola, Arthur Gretton, Hans-Peter Kri...
VLSISP
2010
106views more  VLSISP 2010»
13 years 7 months ago
A Multi-Pronged Approach to Improving Semantic Extraction of News Video
In this paper we describe a multi-strategy approach to improving semantic extraction from news video. Experiments show the value of careful parameter tuning, exploiting multiple fe...
Alexander G. Hauptmann, Ming-yu Chen, Michael G. C...
BMCBI
2007
112views more  BMCBI 2007»
13 years 9 months ago
Selecting dissimilar genes for multi-class classification, an application in cancer subtyping
Background: Gene expression microarray is a powerful technology for genetic profiling diseases and their associated treatments. Such a process involves a key step of biomarker ide...
Zhipeng Cai, Randy Goebel, Mohammad R. Salavatipou...
ICDAR
2005
IEEE
14 years 2 months ago
A Hierarchical Classifier Using New Support Vector Machine
A binary hierarchical classifier is proposed to solve the multi-class classification problem. We also require rejection of non-target inputs, which thus producing a very difficult...
Yu-Chiang Frank Wang, David Casasent