Kernel methods have been successfully applied to many machine learning problems. Nevertheless, since the performance of kernel methods depends heavily on the type of kernels being...
Tianbao Yang, Mehrdad Mahdavi, Rong Jin, Jinfeng Y...
This paper describes the development of a ground truth dataset of culturally diverse Romanized names in which approximately 70,000 names are matched against a subset of 700. We ra...
Discovering the dependencies among the variables of a domain from examples is an important problem in optimization. Many methods have been proposed for this purpose, but few large...
This paper presents a new pooling method for constructing the assessment sets used in the evaluation of retrieval systems. Our proposal is based on RankBoost, a machine learning v...
We present a real-time, Linux-based testbed called LITMUSRT , which we have developed for empirically evaluating multiprocessor real-time scheduling algorithms. We also present th...
John M. Calandrino, Hennadiy Leontyev, Aaron Block...