Kernel machines are a popular class of machine learning algorithms that achieve state of the art accuracies on many real-life classification problems. Kernel perceptrons are among...
Recent work on the transfer of semantic information across languages has been recently applied to the development of resources annotated with Frame information for different non-En...
Roberto Basili, Diego De Cao, Danilo Croce, Bonave...
Abstract. Contract-based property checkers hold the potential for precise, scalable, and incremental reasoning. However, it is difficult to apply such checkers to large program mod...
Shuvendu K. Lahiri, Shaz Qadeer, Juan P. Galeotti,...
This paper introduces a new framework for thinking about tangible interfaces in education, with specific focus on problem domains. Manipulatives are physical objects specifically ...
We present a framework for generating procedure summaries that are precise -- applying the summary in a given context yields the same result as re-analyzing the procedure in that ...