In this paper we introduce the concept and method for adaptively tuning the model complexity in an online manner as more examples become available. Challenging classification pro...
Inductive inference can be considered as one of the fundamental paradigms of algorithmic learning theory. We survey results recently obtained and show their impact to potential ap...
In this paper, we present a novel multi-agent learning paradigm called team-partitioned, opaque-transition reinforcement learning (TPOT-RL). TPOT-RL introduces the concept of usin...
The concept of information landscapes has been a constant theme in the development of interactive multimedia packages. For the interface and access to this information to be effec...
John G. Hedberg, Barry Harper, Christine Brown, Ro...
A conversational method of teaching whereby the students engage each other as a key part of the learning experience achieves a higher percentage of high grades (and presumably bet...