We study the problem of estimating selectivity of approximate substring queries. Its importance in databases is ever increasing as more and more data are input by users and are in...
Standard Reinforcement Learning (RL) aims to optimize decision-making rules in terms of the expected return. However, especially for risk-management purposes, other criteria such ...
In this paper, we propose a new scheduling method for asynchronous circuits in bundled-data implementation. The method is based on integer linear programming (ILP) which explores ...
Scalability and extended lifetime are two critical design goals of any large scale wireless sensor network. A two-tiered network model has been proposed recently for this purpose....
This paper is concerned with the design and analysis of adaptive wavelet methods for systems of operator equations. Its main accomplishment is to extend the range of applicability...