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» Online learning to diversify from implicit feedback
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JUCS
2006
185views more  JUCS 2006»
13 years 6 months ago
The Berlin Brain-Computer Interface: Machine Learning Based Detection of User Specific Brain States
We outline the Berlin Brain-Computer Interface (BBCI), a system which enables us to translate brain signals from movements or movement intentions into control commands. The main co...
Benjamin Blankertz, Guido Dornhege, Steven Lemm, M...
IUI
2003
ACM
13 years 12 months ago
On-line personalization of a touch screen based keyboard
The user expectations for usability and personalization along with decreasing size of handheld devices challenge traditional keypad layout design. We have developed a method for o...
Johan Himberg, Jonna Häkkilä, Petri Kang...
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...
LION
2007
Springer
192views Optimization» more  LION 2007»
14 years 26 days ago
Learning While Optimizing an Unknown Fitness Surface
This paper is about Reinforcement Learning (RL) applied to online parameter tuning in Stochastic Local Search (SLS) methods. In particular a novel application of RL is considered i...
Roberto Battiti, Mauro Brunato, Paolo Campigotto
IPM
2008
139views more  IPM 2008»
13 years 6 months ago
Complex adaptive filtering user profile using graphical models
This article explores how to develop complex data driven user models that go beyond the bag of words model and topical relevance. We propose to learn from rich user specific info...
Yi Zhang 0001