Guided by the goal of obtaining an optimization algorithm that is both fast and yields good generalization, we study the descent direction maximizing the decrease in generalizatio...
Nicolas Le Roux, Pierre-Antoine Manzagol, Yoshua B...
In this paper, we study the relationship between the two techniques known as ant colony optimization (aco) and stochastic gradient descent. More precisely, we show that some empir...
We describe a primal-dual framework for the design and analysis of online strongly convex optimization algorithms. Our framework yields the tightest known logarithmic regret bound...
This paper describes an approach to the use of gradient descent search in genetic programming (GP) for object classification problems. In this approach, pixel statistics are used ...