L1 regularization is effective for feature selection, but the resulting optimization is challenging due to the non-differentiability of the 1-norm. In this paper we compare state...
Feature selection is a problem of choosing a subset of relevant features. Researchers have been searching for optimal feature selection methods. `Branch and Bound' and Focus a...
Distributed W-Learning (DWL) is a reinforcement learningbased algorithm for multi-policy optimization in agent-based systems. In this poster we propose the use of DWL for decentra...
In previous work, we presented a Typed Assembly Language (TAL). TAL is sufficiently expressive to serve as a target language for compilers of high-level languages such as ML. More...
J. Gregory Morrisett, Karl Crary, Neal Glew, David...
End-user programming provides a unique opportunity to study informal computer science education and knowledge acquisition in the real world. We seek to explore the use of communit...