Given a dataset, each element of which labeled by one of k labels, we construct by a very fast algorithm, a k-category proximal support vector machine (PSVM) classifier. Proximal s...
Here we advocate an approach to learning hardware based on induction of finite state machines from temporal logic constraints. The method involves training on examples, constraint...
Marek A. Perkowski, Alan Mishchenko, Anatoli N. Ch...
In this paper we introduce the Generalized Bayesian Committee Machine (GBCM) for applications with large data sets. In particular, the GBCM can be used in the context of kernel ba...
We consider the problem of the binary classification on imbalanced data, in which nearly all the instances are labelled as one class, while far fewer instances are labelled as the...
Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. ...
The efficient mapping of program parallelism to multi-core processors is highly dependent on the underlying architecture. This paper proposes a portable and automatic compiler-bas...