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» Learning Models for Predicting Recognition Performance
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113
Voted
KDD
2010
ACM
287views Data Mining» more  KDD 2010»
15 years 4 months ago
Designing efficient cascaded classifiers: tradeoff between accuracy and cost
We propose a method to train a cascade of classifiers by simultaneously optimizing all its stages. The approach relies on the idea of optimizing soft cascades. In particular, inst...
Vikas C. Raykar, Balaji Krishnapuram, Shipeng Yu
119
Voted
BIBM
2008
IEEE
142views Bioinformatics» more  BIBM 2008»
15 years 9 months ago
Using Global Sequence Similarity to Enhance Biological Sequence Labeling
Identifying functionally important sites from biological sequences, formulated as a biological sequence labeling problem, has broad applications ranging from rational drug design ...
Cornelia Caragea, Jivko Sinapov, Drena Dobbs, Vasa...
122
Voted
RECOMB
2007
Springer
16 years 2 months ago
A Bayesian Model That Links Microarray mRNA Measurements to Mass Spectrometry Protein Measurements
Abstract. An important problem in biology is to understand correspondences between mRNA microarray levels and mass spectrometry peptide counts. Recently, a compendium of mRNA expre...
Anitha Kannan, Andrew Emili, Brendan J. Frey
240
Voted
AIED
2011
Springer
14 years 6 months ago
Self-assessment of Motivation: Explicit and Implicit Indicators in L2 Vocabulary Learning
Self-assessment motivation questionnaires have been used in classrooms yet many researchers find only a weak correlation between answers to these questions and learning. In this pa...
Kevin Dela Rosa, Maxine Eskenazi
118
Voted
MICCAI
2010
Springer
15 years 1 months ago
Multi-Class Sparse Bayesian Regression for Neuroimaging Data Analysis
The use of machine learning tools is gaining popularity in neuroimaging, as it provides a sensitive assessment of the information conveyed by brain images. In particular, finding ...
Vincent Michel, Evelyn Eger, Christine Keribin, Be...