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134
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ECML
2006
Springer
15 years 6 months ago
Transductive Gaussian Process Regression with Automatic Model Selection
Abstract. In contrast to the standard inductive inference setting of predictive machine learning, in real world learning problems often the test instances are already available at ...
Quoc V. Le, Alexander J. Smola, Thomas Gärtne...
125
Voted
COLT
1991
Springer
15 years 6 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
97
Voted
ECTEL
2009
Springer
15 years 9 months ago
Personalisation of Learning in Virtual Learning Environments
Personalization of learning has become a prominent issue in the educational field, at various levels. This article elaborates a different view on personalisation than what usually ...
Dominique Verpoorten, Christian Glahn, Milos Kravc...
123
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ICML
2005
IEEE
16 years 3 months ago
Active learning for Hidden Markov Models: objective functions and algorithms
Hidden Markov Models (HMMs) model sequential data in many fields such as text/speech processing and biosignal analysis. Active learning algorithms learn faster and/or better by cl...
Brigham Anderson, Andrew Moore
129
Voted
IJCNN
2006
IEEE
15 years 8 months ago
Alleviating Catastrophic Forgetting via Multi-Objective Learning
— Handling catastrophic forgetting is an interesting and challenging topic in modeling the memory mechanisms of the human brain using machine learning models. From a more general...
Yaochu Jin, Bernhard Sendhoff