The min-sum k-clustering problem is to partition a metric space (P, d) into k clusters C1, . . . , Ck ⊆ P such that k i=1 p,q∈Ci d(p, q) is minimized. We show the first effi...
When an image is viewed at varying resolutions, it is known to create discrete perceptual jumps or transitions amid the continuous intensity changes. In this paper, we study a per...
Service composition is becoming the dominant paradigm for developing Web service applications. It is important to ensure that a service composition complies with the requirements f...
Jian Yu, Tan Phan Manh, Jun Han, Yan Jin, Yanbo Ha...
We provide a provably efficient algorithm for learning Markov Decision Processes (MDPs) with continuous state and action spaces in the online setting. Specifically, we take a mo...
We prove an upper bound on the convergence rate of Markov Chain Monte Carlo (MCMC) algorithms for the important special case when the state space can be aggregated into a smaller ...