Set-valued estimation offers a way to account for imprecise knowledge of the prior distribution of a Bayesian statistical inference problem. The set-valued Kalman filter, which p...
Bloom filters make use of a "probabilistic" hash-coding method to reduce the amount of space required to store a hash set. A Bloom filter offers a trade-off between its ...
Mark C. Little, Santosh K. Shrivastava, Neil A. Sp...
— We study the problem of optimal estimation using quantized innovations, with application to distributed estimation over sensor networks. We show that the state probability dens...
Knowledge discovery systems are constrained by three main limited resources: time, memory and sample size. Sample size is traditionally the dominant limitation, but in many present...
Time information is critical for a variety of applications in distributed environments that facilitate pervasive computing and communication. This work describes and evaluates a no...