Dynamic optimization presents opportunities for finding run-time bottlenecks and deploying optimizations in statically compiled programs. In this paper, we discuss our current impl...
Howard Chen, Jiwei Lu, Wei-Chung Hsu, Pen-Chung Ye...
ABSTRACT. Estimating a non-uniformly sampled function from a set of learning points is a classical regression problem. Kernel methods have been widely used in this context, but eve...
Bandit based methods for tree search have recently gained popularity when applied to huge trees, e.g. in the game of go [6]. Their efficient exploration of the tree enables to ret...
The multi-objective covariance matrix adaptation evolution strategy (MO-CMA-ES) combines a mutation operator that adapts its search distribution to the underlying optimization prob...
— Adaptive modulation and antenna diversity are two important enabling techniques for future wireless network to meet demand for high data rate transmission. We study a Markov de...