In this paper, a new recursive algorithm is proposed for optimal estimation of similarity measure used in a content-based retrieval system. This is performed through a relevance f...
— A key step in many statistical learning methods used in machine learning involves solving a convex optimization problem containing one or more hyper-parameters that must be sel...
Kristin P. Bennett, Jing Hu, Xiaoyun Ji, Gautam Ku...
This paper proposes a new algorithm which promotes well distributed non-dominated fronts in the parameters space when a single-objective function is optimized. This algorithm is b...
In this work, we extend a common framework for seeded
image segmentation that includes the graph cuts, ran-
dom walker, and shortest path optimization algorithms.
Viewing an ima...
Camille Couprie, Leo Grady, Laurent Najman, Hugues...
In this paper, we present a novel and efficient approach for automatic design of Artificial Neural Networks (ANNs) by evolving to the optimal network configuration(s) within an ar...
E. Alper Yildirim, Ince Turker, Moncef Gabbouj, Se...