In multi-task learning our goal is to design regression or classification models for each of the tasks and appropriately share information between tasks. A Dirichlet process (DP) ...
In this paper, we review the paradigm of inductive process modeling, which uses background knowledge about possible component processes to construct quantitative models of dynamic...
Will Bridewell, Narges Bani Asadi, Pat Langley, Lj...
A computational composite is a material in which computations contribute to the properties of the material through their capability to control transitions between states in the oth...
Time synchronization is a crucial component of a large class of sensor network applications, traditionally implemented as a standalone middleware service that provides a virtual gl...
Building fully synchronous VLSI circuits is becoming less viable as circuit geometries evolve. However, before the adoption of purely asynchronous strategies in VLSI design, globa...
Julian J. H. Pontes, Rafael Soares, Ewerson Carval...