We describe a generative model for graph edges under specific degree distributions which admits an exact and efficient inference method for recovering the most likely structure. T...
In many real applications, especially those involving data objects with complicated semantics, it is generally desirable to discover the relation between patterns in the input spa...
Though recent analysis of traditional cooperative coevolutionary algorithms (CCEAs) casts doubt on their suitability for static optimization tasks, our experience is that the algo...
L1 regularized logistic regression is now a workhorse of machine learning: it is widely used for many classification problems, particularly ones with many features. L1 regularized...
Su-In Lee, Honglak Lee, Pieter Abbeel, Andrew Y. N...
Nonlinear model predictive control (MPC) of a simulated chaotic cutting process is presented. The nonlinear MPC combines a neural-network model and a genetic-algorithm-based optim...