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CHI
2010
ACM
16 years 1 months ago
Examining multiple potential models in end-user interactive concept learning
End-user interactive concept learning is a technique for interacting with large unstructured datasets, requiring insights from both human-computer interaction and machine learning...
Saleema Amershi, James Fogarty, Ashish Kapoor, Des...
ICTAI
2007
IEEE
16 years 14 days ago
Multi-agent Reinforcement Learning Using Strategies and Voting
Multiagent learning attracts much attention in the past few years as it poses very challenging problems. Reinforcement Learning is an appealing solution to the problems that arise...
Ioannis Partalas, Ioannis Feneris, Ioannis P. Vlah...
AICT
2006
IEEE
16 years 7 days ago
Privacy and data protection in technology-enhanced professional learning
Privacy provision and data protection are basic requirements for professional learning, especially when personalized systems are used that adapt to sensitive learner personal data...
Tomaz Klobucar
IJCNN
2006
IEEE
16 years 5 days ago
Alleviating Catastrophic Forgetting via Multi-Objective Learning
— Handling catastrophic forgetting is an interesting and challenging topic in modeling the memory mechanisms of the human brain using machine learning models. From a more general...
Yaochu Jin, Bernhard Sendhoff
HICSS
2005
IEEE
115views Biometrics» more  HICSS 2005»
15 years 11 months ago
Strategies Employed By Participants In Virtual Learning Communities
This paper examines the learning behavior of online students in an asynchronous learning environment. We employ the theoretical lens of an online community of inquiry, to understa...
James Waters, Susan Gasson