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» On learning with dissimilarity functions
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NIPS
2007
15 years 8 months ago
Agreement-Based Learning
The learning of probabilistic models with many hidden variables and nondecomposable dependencies is an important and challenging problem. In contrast to traditional approaches bas...
Percy Liang, Dan Klein, Michael I. Jordan
KI
2008
Springer
15 years 6 months ago
A Drum Machine That Learns to Groove
Music production relies increasingly on advanced hardware and software tools that makes the creative process more flexible and versatile. The advancement of these tools helps reduc...
Axel Tidemann, Yiannis Demiris
PR
2006
93views more  PR 2006»
15 years 6 months ago
Learning the kernel parameters in kernel minimum distance classifier
Choosing appropriate values for kernel parameters is one of the key problems in many kernel-based methods because the values of these parameters have significant impact on the per...
Daoqiang Zhang, Songcan Chen, Zhi-Hua Zhou
AIEDAM
2004
96views more  AIEDAM 2004»
15 years 6 months ago
Learning while designing
: This paper reports on preliminary results of an explorative study of a protocol analysis of team learning while designing using in-situ data. Two measurement-based frameworks are...
Gourabmoy Nath, John S. Gero
ICML
2009
IEEE
16 years 7 months ago
Predictive representations for policy gradient in POMDPs
We consider the problem of estimating the policy gradient in Partially Observable Markov Decision Processes (POMDPs) with a special class of policies that are based on Predictive ...
Abdeslam Boularias, Brahim Chaib-draa