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» Towards a Better Understanding of Incremental Learning
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ITS
2004
Springer
138views Multimedia» more  ITS 2004»
13 years 10 months ago
A Metacognitive ACT-R Model of Students' Learning Strategies in Intelligent Tutoring Systems
Research has shown that students’ problem-solving actions vary in type and duration. Among other causes, this behavior is a result of strategies that are driven by different goal...
Ido Roll, Ryan Shaun Baker, Vincent Aleven, Kennet...
UAI
2008
13 years 6 months ago
Toward Experiential Utility Elicitation for Interface Customization
User preferences for automated assistance often vary widely, depending on the situation, and quality or presentation of help. Developing effective models to learn individual prefe...
Bowen Hui, Craig Boutilier
IROS
2007
IEEE
143views Robotics» more  IROS 2007»
13 years 11 months ago
Metrics for quantifying system performance in intelligent, fault-tolerant multi-robot teams
— Any system that has the capability to diagnose and recover from faults is considered to be a fault-tolerant system. Additionally, the quality of the incorporated fault-toleranc...
Balajee Kannan, Lynne E. Parker
AAAI
2007
13 years 7 months ago
A Connectionist Cognitive Model for Temporal Synchronisation and Learning
The importance of the efforts towards integrating the symbolic and connectionist paradigms of artificial intelligence has been widely recognised. Integration may lead to more e...
Luís C. Lamb, Rafael V. Borges, Artur S. d'...
BMCBI
2008
165views more  BMCBI 2008»
13 years 5 months ago
Peak intensity prediction in MALDI-TOF mass spectrometry: A machine learning study to support quantitative proteomics
Background: Mass spectrometry is a key technique in proteomics and can be used to analyze complex samples quickly. One key problem with the mass spectrometric analysis of peptides...
Wiebke Timm, Alexandra Scherbart, Sebastian Bö...