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ADMA
2006
Springer
110views Data Mining» more  ADMA 2006»
14 years 17 days ago
Learning with Local Drift Detection
Abstract. Most of the work in Machine Learning assume that examples are generated at random according to some stationary probability distribution. In this work we study the problem...
João Gama, Gladys Castillo
APWEB
2005
Springer
14 years 2 months ago
An Incremental Subspace Learning Algorithm to Categorize Large Scale Text Data
The dramatic growth in the number and size of on-line information sources has fueled increasing research interest in the incremental subspace learning problem. In this paper, we pr...
Jun Yan, QianSheng Cheng, Qiang Yang, Benyu Zhang
ITICSE
2010
ACM
14 years 13 days ago
Helping students build a mental model of computation
Introductory computer science classes are known for having a high attrition rate. Some authors believe this is due to students’ difficulties in establishing a mental model of co...
Steve Kollmansberger
AI
2002
Springer
13 years 8 months ago
Improving heuristic mini-max search by supervised learning
This article surveys three techniques for enhancing heuristic game-tree search pioneered in the author's Othello program Logistello, which dominated the computer Othello scen...
Michael Buro
EMNLP
2007
13 years 10 months ago
Structural Correspondence Learning for Dependency Parsing
Following (Blitzer et al., 2006), we present an application of structural correspondence learning to non-projective dependency parsing (McDonald et al., 2005). To induce the corre...
Nobuyuki Shimizu, Hiroshi Nakagawa