Machine learning techniques are increasingly being used to produce a wide-range of classifiers for complex real-world applications that involve nonuniform testing costs and miscl...
For a discrete-time finite-state Markov chain, we develop an adaptive importance sampling scheme to estimate the expected total cost before hitting a set of terminal states. This s...
Abstract. Location estimation and user behavior recognition are research issues that go hand in hand. In the past, these two issues have been investigated separately. In this paper...
Classically, communication systems are designed assuming perfect channel state information at the receiver and/or transmitter. However, in many practical situations, only an estim...
Location estimation is an important part of many ubiquitous computing systems. Particle filters are simulation-based probabilistic approximations which the robotics community has ...