We develop methods for analyzing and constructing combined modulation/error-correctiong codes (ECC codes), in particular codes that employ some form of reversed concatenation and w...
Jorge Campello de Souza, Brian H. Marcus, Richard ...
We consider the exploration/exploitation problem in reinforcement learning (RL). The Bayesian approach to model-based RL offers an elegant solution to this problem, by considering...
We investigate the design of algorithms resilient to memory faults, i.e., algorithms that, despite the corruption of some memory values during their execution, are able to produce...
Property testing is concerned with deciding whether an object (e.g. a graph or a function) has a certain property or is “far” (for some definition of far) from every object w...
We propose a framework for defining agent-based models (ABMs) and two algorithms for the automatic parallelization of agent-based models, a general version P-ABMG for all ABMs def...