Abstract. Multiple-instance learning (MIL) allows for training classifiers from ambiguously labeled data. In computer vision, this learning paradigm has been recently used in many ...
In recent years, matrix approximation for missing value prediction has emerged as an important problem in a variety of domains such as recommendation systems, e-commerce and onlin...
In this paper, we propose a technique to flexibly implement genetic algorithms for various problems on FPGAs. For the purpose, we propose a basic architecture for GA which consist...
—Thus far, sparse representations have been exploited largely in the context of robustly estimating functions in a noisy environment from a few measurements. In this context, the...
Parallel algorithm designers need computational models that take first order system costs into account, but are also simple enough to use in practice. This paper introduces the L...