We present a novel deterministic dependency parsing algorithm that attempts to create the easiest arcs in the dependency structure first in a non-directional manner. Traditional d...
—Methods for learning decision rules are being successfully applied to many problem domains, especially where understanding and interpretation of the learned model is necessary. ...
We examine the implications of a new hazard-free combinational logic synthesis method [8], which generates multiplexor trees from binary decision diagrams (BDDs) -- representation...
Kenneth Y. Yun, Bill Lin, David L. Dill, Srinivas ...
To solve a decision problem under uncertainty via stochastic programming means to choose or to build a suitable stochastic programming model taking into account the nature of the r...
We present a molecular computing algorithm for evolving DNA-encoded genetic programs in a test tube. The use of synthetic DNA molecules combined with biochemical techniques for va...