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KDD
2012
ACM
205views Data Mining» more  KDD 2012»
13 years 8 months ago
Rank-loss support instance machines for MIML instance annotation
Multi-instance multi-label learning (MIML) is a framework for supervised classification where the objects to be classified are bags of instances associated with multiple labels....
Forrest Briggs, Xiaoli Z. Fern, Raviv Raich
AH
2004
Springer
15 years 11 months ago
Developing Active Learning Experiences for Adaptive Personalised eLearning
Developing adaptive, rich-media, eLearning courses tends to be a complex, highly-expensive and time-consuming task. A typical adaptive eLearning course will involve a multi-skilled...
Declan Dagger, Vincent P. Wade, Owen Conlan
KDD
1995
ACM
148views Data Mining» more  KDD 1995»
15 years 10 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
COLT
1991
Springer
15 years 9 months ago
On the Complexity of Teaching
While most theoretical work in machine learning has focused on the complexity of learning, recently there has been increasing interest in formally studying the complexity of teach...
Sally A. Goldman, Michael J. Kearns
NAACL
2001
15 years 7 months ago
Learning Optimal Dialogue Management Rules by Using Reinforcement Learning and Inductive Logic Programming
Developing dialogue systems is a complex process. In particular, designing efficient dialogue management strategies is often difficult as there are no precise guidelines to develo...
Renaud Lecoeuche