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NIPS
1994
15 years 7 months ago
Active Learning with Statistical Models
For many types of machine learning algorithms, one can compute the statistically optimal" way to select training data. In this paper, we review how optimal data selection tec...
David A. Cohn, Zoubin Ghahramani, Michael I. Jorda...
CVPR
2010
IEEE
16 years 2 months ago
Safety in Numbers: Learning Categories from Few Examples with Multi Model Knowledge Transfer
Learning object categories from small samples is a challenging problem, where machine learning tools can in general provide very few guarantees. Exploiting prior knowledge may be ...
Tatiana Tommasi, Francesco Orabona, Barbara Caputo
SMC
2007
IEEE
125views Control Systems» more  SMC 2007»
16 years 23 days ago
A hierarchical strategy for learning of robot walking strategies in natural terrain environments
– In this paper, we present a hierarchical methodology that learns new walking gaits autonomously while operating in an uncharted environment, such as on the Mars planetary surfa...
Ayanna M. Howard, Lonnie T. Parker
CLA
2007
15 years 8 months ago
Policies Generalization in Reinforcement Learning using Galois Partitions Lattices
The generalization of policies in reinforcement learning is a main issue, both from the theoretical model point of view and for their applicability. However, generalizing from a se...
Marc Ricordeau, Michel Liquiere
EACL
2003
ACL Anthology
15 years 8 months ago
Learning to Identify Fragmented Words in Spoken Discourse
Disfluent speech adds to the difficulty of processing spoken language utterances. In this paper we concentrate on identifying one disfluency phenomenon: fragmented words. Our d...
Piroska Lendvai