We present two new algorithms for finding optimal strategies for discounted, infinite-horizon, Deterministic Markov Decision Processes (DMDP). The first one is an adaptation of...
This article proposes a stochastic version of the matching pursuit algorithm for Bayesian variable selection in linear regression. In the Bayesian formulation, the prior distributi...
There are many local and greedy algorithms for energy minimization over Markov Random Field (MRF) such as iterated condition mode (ICM) and various gradient descent methods. Local ...
DHT networks based on consistent hashing functions have an inherent load uneven distribution problem. The objective of DHT load balancing is to balance the workload of the network...
This paper investigates the problem of incremental joins of multiple ranked data sets when the join condition is a list of arbitrary user-defined predicates on the input tuples. ...
Apostol Natsev, Yuan-Chi Chang, John R. Smith, Chu...