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» Machine learned regression for abductive DNA sequencing
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BMCBI
2008
143views more  BMCBI 2008»
13 years 7 months ago
Automatic detection of exonic splicing enhancers (ESEs) using SVMs
Background: Exonic splicing enhancers (ESEs) activate nearby splice sites and promote the inclusion (vs. exclusion) of exons in which they reside, while being a binding site for S...
Britta Mersch, Alexander Gepperth, Sándor S...
ICML
2003
IEEE
14 years 8 months ago
Online Ranking/Collaborative Filtering Using the Perceptron Algorithm
In this paper we present a simple to implement truly online large margin version of the Perceptron ranking (PRank) algorithm, called the OAP-BPM (Online Aggregate Prank-Bayes Poin...
Edward F. Harrington
ICML
1997
IEEE
14 years 8 months ago
Characterizing the generalization performance of model selection strategies
Abstract: We investigate the structure of model selection problems via the bias/variance decomposition. In particular, we characterize the essential structure of a model selection ...
Dale Schuurmans, Lyle H. Ungar, Dean P. Foster
COLT
1999
Springer
13 years 11 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
IJFCS
2006
130views more  IJFCS 2006»
13 years 7 months ago
Mealy multiset automata
We introduce the networks of Mealy multiset automata, and study their computational power. The networks of Mealy multiset automata are computationally complete. 1 Learning from Mo...
Gabriel Ciobanu, Viorel Mihai Gontineac