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ML
2000
ACM
149views Machine Learning» more  ML 2000»
14 years 9 months ago
BoosTexter: A Boosting-based System for Text Categorization
This work focuses on algorithms which learn from examples to perform multiclass text and speech categorization tasks. Our approach is based on a new and improved family of boosting...
Robert E. Schapire, Yoram Singer
ICCBR
1999
Springer
15 years 2 months ago
When Experience Is Wrong: Examining CBR for Changing Tasks and Environments
Case-based problem-solving systems reason and learn from experiences, building up case libraries of problems and solutions to guide future reasoning. The expected bene ts of this l...
David B. Leake, David C. Wilson
TROB
2010
159views more  TROB 2010»
14 years 4 months ago
Task-Specific Generalization of Discrete and Periodic Dynamic Movement Primitives
Abstract--Acquisition of new sensorimotor knowledge by imitation is a promising paradigm for robot learning. To be effective, action learning should not be limited to direct replic...
Ales Ude, Andrej Gams, Tamim Asfour, Jun Morimoto
ICALP
2011
Springer
14 years 1 months ago
New Algorithms for Learning in Presence of Errors
We give new algorithms for a variety of randomly-generated instances of computational problems using a linearization technique that reduces to solving a system of linear equations...
Sanjeev Arora, Rong Ge
BMCBI
2006
111views more  BMCBI 2006»
14 years 9 months ago
PepDist: A New Framework for Protein-Peptide Binding Prediction based on Learning Peptide Distance Functions
Background: Many different aspects of cellular signalling, trafficking and targeting mechanisms are mediated by interactions between proteins and peptides. Representative examples...
Tomer Hertz, Chen Yanover