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» Good Learning and Implicit Model Enumeration
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ICSTM
2000
164views Management» more  ICSTM 2000»
13 years 7 months ago
Building Sustainable Interest in Modelling in the Classroom
System Dynamics has had a tough time breaking into High Schools. Like all good ideas the most difficult part is convincing those who would most benefit that this new approach is i...
Gordon Kubanek
JMLR
2008
131views more  JMLR 2008»
13 years 6 months ago
On Relevant Dimensions in Kernel Feature Spaces
We show that the relevant information of a supervised learning problem is contained up to negligible error in a finite number of leading kernel PCA components if the kernel matche...
Mikio L. Braun, Joachim M. Buhmann, Klaus-Robert M...
ICDM
2010
IEEE
172views Data Mining» more  ICDM 2010»
13 years 4 months ago
Learning Attribute-to-Feature Mappings for Cold-Start Recommendations
Cold-start scenarios in recommender systems are situations in which no prior events, like ratings or clicks, are known for certain users or items. To compute predictions in such ca...
Zeno Gantner, Lucas Drumond, Christoph Freudenthal...
SIGIR
2012
ACM
11 years 8 months ago
TFMAP: optimizing MAP for top-n context-aware recommendation
In this paper, we tackle the problem of top-N context-aware recommendation for implicit feedback scenarios. We frame this challenge as a ranking problem in collaborative filterin...
Yue Shi, Alexandros Karatzoglou, Linas Baltrunas, ...
AAAI
1998
13 years 7 months ago
Fast Probabilistic Modeling for Combinatorial Optimization
Probabilistic models have recently been utilized for the optimization of large combinatorial search problems. However, complex probabilistic models that attempt to capture interpa...
Shumeet Baluja, Scott Davies