Clustering is an important technique for understanding and analysis of large multi-dimensional datasets in many scientific applications. Most of clustering research to date has be...
The K-Nearest Neighbor search (kNN) problem has been investigated extensively in the past due to its broad range of applications. In this paper we study this problem in the contex...
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 order to maintain a conflict-free environment among licensed primary users (PUs) and unlicensed secondary users (SUs) in cognitive radio networks, providing frequency and g...
This paper proposes an efficient agent for competing in Cliff Edge (CE) environments, such as sealed-bid auctions, dynamic pricing and the ultimatum game. The agent competes in on...