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...
The proposed feature selection method aims to find a minimum subset of the most informative variables for classification/regression by efficiently approximating the Markov Blanket ...
We consider a number of range reporting problems in two and three dimensions and prove lower bounds on the amount of space used by any cache-oblivious data structure for these pro...
In this paper we consider the problem of managing and exploiting schedules in an uncertain and distributed environment. We assume a team of collaborative agents, each responsible ...
Stephen F. Smith, Anthony Gallagher, Terry L. Zimm...
In modern embedded systems including communication and multimedia applications, large fraction of power is consumed during memory access and data transfer. Thus, buses should be d...