We study the convergence of Markov Decision Processes made of a large number of objects to optimization problems on ordinary differential equations (ODE). We show that the optimal...
Abstract—Precision analysis and optimization is very important when transforming a floating-point algorithm into fixedpoint hardware implementations. The core analysis techniqu...
Jason Cong, Karthik Gururaj, Bin Liu, Chunyue Liu,...
Abstract. In this paper, we study the problem of controlling the expected exit time from a region for a class of stochastic hybrid systems. That is, we find the least costly feedb...
This paper exploits the tradeoff between data quality and energy consumption to extend the lifetime of wireless sensor networks. To obtain an aggregate form of sensor data with pre...
A central challenge in computer science and knowledge representation is the integration of conceptual frameworks for continuous and discrete change, as exemplified by the theory ...