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NIPS
2007
15 years 8 months ago
Active Preference Learning with Discrete Choice Data
We propose an active learning algorithm that learns a continuous valuation model from discrete preferences. The algorithm automatically decides what items are best presented to an...
Eric Brochu, Nando de Freitas, Abhijeet Ghosh
FLAIRS
1998
15 years 8 months ago
Lazy Transformation-Based Learning
Weintroduce a significant improvementfor a relatively newmachine learning methodcalled Transformation-Based Learning. By applying a MonteCarlo strategy to randomly sample from the...
Ken Samuel
ICASSP
2010
IEEE
15 years 6 months ago
Learning from high-dimensional noisy data via projections onto multi-dimensional ellipsoids
In this paper, we examine the problem of learning from noisecontaminated data in high-dimensional space. A new learning approach based on projections onto multi-dimensional ellips...
Liuling Gong, Dan Schonfeld
ECTEL
2009
Springer
15 years 4 months ago
Experience Structuring Factors Affecting Learning in Family Visits to Museums
Abstract. This paper describes the design and evaluation of an adaptive museum guide for families. In the Kurio system, a mixture of embedded and tangible technology imbues the mus...
Marek Hatala, Karen Tanenbaum, Ron Wakkary, Kevin ...
ICPR
2008
IEEE
16 years 7 months ago
Exploiting qualitative domain knowledge for learning Bayesian network parameters with incomplete data
When a large amount of data are missing, or when multiple hidden nodes exist, learning parameters in Bayesian networks (BNs) becomes extremely difficult. This paper presents a lea...
Qiang Ji, Wenhui Liao