This paper formalizes Feature Selection as a Reinforcement Learning problem, leading to a provably optimal though intractable selection policy. As a second contribution, this pape...
Most frameworks for utility elicitation assume a predefined set of features over which user preferences are expressed. We consider utility elicitation in the presence of subjecti...
- This paper presents a learning approach using cerebellar model articulation controller (CMAC) to accommodate faults for a class of multivariable nonlinear systems. A CMAC is prop...
Chih-Min Lin, Chang-Chih Chung, Yu-Ju Liu, Daniel ...
For many educational applications such as learning tools for argumentation, structured diagrams are a suitable form of external representation. However, student-created graphs pos...
Niels Pinkwart, Kevin D. Ashley, Vincent Aleven, C...
Semi-supervised clustering algorithms aim to improve clustering results using limited supervision. The supervision is generally given as pairwise constraints; such constraints are...
Brian Kulis, Sugato Basu, Inderjit S. Dhillon, Ray...