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COLT
1999
Springer
15 years 6 months ago
Regret Bounds for Prediction Problems
We present a unified framework for reasoning about worst-case regret bounds for learning algorithms. This framework is based on the theory of duality of convex functions. It brin...
Geoffrey J. Gordon
126
Voted
WEBNET
2000
15 years 3 months ago
How the Wild Wide Web was Won: Online Web Developer Training
: As the Web grows in importance in institutional settings, so does the need for training. Universities are looking at the daunting task of putting more information and services on...
John Sharkey, Kitzzy Aviles, Barbara Ferguson
128
Voted
BMCBI
2006
137views more  BMCBI 2006»
15 years 2 months ago
A classification-based framework for predicting and analyzing gene regulatory response
Background: We have recently introduced a predictive framework for studying gene transcriptional regulation in simpler organisms using a novel supervised learning algorithm called...
Anshul Kundaje, Manuel Middendorf, Mihir Shah, Chr...
BMCBI
2011
14 years 9 months ago
Using Stochastic Causal Trees to Augment Bayesian Networks for Modeling eQTL Datasets
Background: The combination of genotypic and genome-wide expression data arising from segregating populations offers an unprecedented opportunity to model and dissect complex phen...
Kyle C. Chipman, Ambuj K. Singh
JMLR
2011
148views more  JMLR 2011»
14 years 9 months ago
Multitask Sparsity via Maximum Entropy Discrimination
A multitask learning framework is developed for discriminative classification and regression where multiple large-margin linear classifiers are estimated for different predictio...
Tony Jebara