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KDD
1995
ACM
148views Data Mining» more  KDD 1995»
15 years 8 months ago
Learning Arbiter and Combiner Trees from Partitioned Data for Scaling Machine Learning
Knowledge discovery in databases has become an increasingly important research topic with the advent of wide area network computing. One of the crucial problems we study in this p...
Philip K. Chan, Salvatore J. Stolfo
EDM
2009
110views Data Mining» more  EDM 2009»
15 years 2 months ago
Using Learning Decomposition and Bootstrapping with Randomization to Compare the Impact of Different Educational Interventions o
A basic question of instructional interventions is how effective it is in promoting student learning. This paper presents a study to determine the relative efficacy of different in...
Mingyu Feng, Joseph Beck, Neil T. Heffernan
ICML
2010
IEEE
15 years 6 months ago
Boosting for Regression Transfer
The goal of transfer learning is to improve the learning of a new target concept given knowledge of related source concept(s). We introduce the first boosting-based algorithms for...
David Pardoe, Peter Stone
AAAI
1994
15 years 6 months ago
Hierarchical Chunking in Classifier Systems
Two standard schemes for learning in classifier systems have been proposed in the literature: the bucket brigade algorithm (BBA) and the profit sharing plan (PSP). The BBA is a lo...
Gerhard Weiß
BMCBI
2008
174views more  BMCBI 2008»
15 years 5 months ago
Evolutionary approaches for the reverse-engineering of gene regulatory networks: A study on a biologically realistic dataset
Background: Inferring gene regulatory networks from data requires the development of algorithms devoted to structure extraction. When only static data are available, gene interact...
Cédric Auliac, Vincent Frouin, Xavier Gidro...