Features identify core characteristics of software in order to produce families of programs. Through configuration, different variants of a program can be composed. Our approach...
We propose a discriminative learning approach for fusing multichannel sequential data with application to detect unsafe driving patterns from multi-channel driving recording data....
We show that the class of strongly connected graphical models with treewidth at most k can be properly efficiently PAC-learnt with respect to the Kullback-Leibler Divergence. Prev...
Aspect-Oriented Programming promises separation of concerns at the implementation level. However, aspects are not always orthogonal and aspect interaction is a fundamental problem...
Probabilistic modeling has been a dominant approach in Machine Learning research. As the field evolves, the problems of interest become increasingly challenging and complex. Makin...
Ming-Wei Chang, Lev-Arie Ratinov, Nicholas Rizzolo...