Abstract. In recent years, there has been a growing interest in addressing dynamic optimization problems (DOPs) using evolutionary algorithms (EAs). Several approaches have been de...
We present a new method for classification with structured
latent variables. Our model is formulated using the
max-margin formalism in the discriminative learning literature.
We...
Given a sequence S of n symbols over some alphabet Σ, we develop a new compression method that is (i) very simple to implement; (ii) provides O(1) time random access to any symbol...
In this work we provide empirical evidence that shows how a variable-length genetic algorithm (GA) can naturally evolve shorter average size populations. This reduction in chromos...
There is a growing body of work on sorting and selection in models other than the unit-cost comparison model. This work treats a natural stochastic variant of the problem where the...