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ICALT
2006
IEEE
16 years 16 days ago
Learning about and through Empirical Modelling
Empirical Modelling is a body of principles and tools that has been developed for the construction of interactive environments. Our previous research has indicated respects in whi...
Russell Boyatt, Antony Harfield, Meurig Beynon
ICCBR
2005
Springer
16 years 8 hour ago
Learning Semantic Annotations for Textual Cases
Abstract. In this paper, we propose an approach to attach semantic annotations to textual cases for their representation. To achieve this goal, a framework that combines machine le...
Eni Mustafaraj, Martin Hoof, Bernd Freisleben
COLT
2007
Springer
16 years 20 days ago
Minimax Bounds for Active Learning
This paper analyzes the potential advantages and theoretical challenges of “active learning” algorithms. Active learning involves sequential sampling procedures that use infor...
Rui Castro, Robert D. Nowak
ALT
2010
Springer
15 years 8 months ago
Online Multiple Kernel Learning: Algorithms and Mistake Bounds
Online learning and kernel learning are two active research topics in machine learning. Although each of them has been studied extensively, there is a limited effort in addressing ...
Rong Jin, Steven C. H. Hoi, Tianbao Yang
AAAI
2008
15 years 8 months ago
Active Learning for Pipeline Models
For many machine learning solutions to complex applications, there are significant performance advantages to decomposing the overall task into several simpler sequential stages, c...
Dan Roth, Kevin Small