Abstract. Most of the work in Machine Learning assume that examples are generated at random according to some stationary probability distribution. In this work we study the problem...
Much recent research has been devoted to learning algorithms for deep architectures such as Deep Belief Networks and stacks of auto-encoder variants, with impressive results obtai...
Dumitru Erhan, Yoshua Bengio, Aaron C. Courville, ...
Genetic algorithms are often applied to combinatorial optimization problems, the most popular one probably being the traveling salesperson problem. In contrast to permutations use...
Abstract. The Parallel Disks Model (PDM) has been proposed to alleviate the I/O bottleneck that arises in the processing of massive data sets. Sorting has been extensively studied ...
Recent research on compact genetic algorithms (cGAs) has proposed a number of evolutionary search methods with reduced memory requirements. In cGAs, the evolution of populations is...