This paper proposes the use of constructive ordinals as mistake bounds in the on-line learning model. This approach elegantly generalizes the applicability of the on-line mistake ...
Metric and kernel learning arise in several machine learning applications. However, most existing metric learning algorithms are limited to learning metrics over low-dimensional d...
Prateek Jain, Brian Kulis, Jason V. Davis, Inderji...
To enable optimizations in memory access behavior of high performance applications, cache monitoring is a crucial process. Simulation of cache hardware is needed in order to allow...
In this paper we present the design, implementation and evaluation of a runtime system based on collective I/O techniques for irregular applications. We present two models, namely...
In collaborative software development the utilization of Version Control Systems (VCSs) is a must. For this important task some graph-based VCSs for model artifacts already emerge...