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ICML
2003
IEEE
14 years 10 months ago
Relational Instance Based Regression for Relational Reinforcement Learning
Relational reinforcement learning (RRL) is a Q-learning technique which uses first order regression techniques to generalize the Qfunction. Both the relational setting and the Q-l...
Kurt Driessens, Jan Ramon
IJCNN
2006
IEEE
14 years 3 months ago
Common Subset Selection of Inputs in Multiresponse Regression
— We propose the Multiresponse Sparse Regression algorithm, an input selection method for the purpose of estimating several response variables. It is a forward selection procedur...
Timo Similä, Jarkko Tikka
ICML
2007
IEEE
14 years 10 months ago
Focused crawling with scalable ordinal regression solvers
In this paper we propose a novel, scalable, clustering based Ordinal Regression formulation, which is an instance of a Second Order Cone Program (SOCP) with one Second Order Cone ...
Rashmin Babaria, J. Saketha Nath, S. Krishnan, K. ...
ESEM
2008
ACM
13 years 11 months ago
Empirical evaluations of regression test selection techniques: a systematic review
Regression testing is the verification that previously functioning software remains after a change. In this paper we report on a systematic review of empirical evaluations of regr...
Emelie Engström, Mats Skoglund, Per Runeson
ICASSP
2010
IEEE
13 years 10 months ago
Robust regression using sparse learning for high dimensional parameter estimation problems
Algorithms such as Least Median of Squares (LMedS) and Random Sample Consensus (RANSAC) have been very successful for low-dimensional robust regression problems. However, the comb...
Kaushik Mitra, Ashok Veeraraghavan, Rama Chellappa