Abstract. The algorithm selection problem aims to select the best algorithm for an input problem instance according to some characteristics of the instance. This paper presents a l...
We present a novel and intuitive framework for building modular vision systems for complex tasks such as surveillance applications. Inspired by graphical models, especially factor...
In this paper, a `market trading' technique is integrated with the techniques of rule discovery and refinement for data mining. A classifier system-inspired model, the market...
The conditional distribution of a discrete variable y, given another discrete variable x, is often specified by assigning one multinomial distribution to each state of x. The cost...
We present a general Bayesian framework for hyperparameter tuning in L2-regularized supervised learning models. Paradoxically, our algorithm works by first analytically integratin...