Abstract. In the artificial neural networks (ANNs), feature selection is a wellresearched problem, which can improve the network performance and speed up the training of the networ...
Similarity search usually encounters a serious problem in the high dimensional space, known as the “curse of dimensionality”. In order to speed up the retrieval efficiency, p...
We propose a fast batch learning method for linearchain Conditional Random Fields (CRFs) based on Newton-CG methods. Newton-CG methods are a variant of Newton method for high-dime...
Yuta Tsuboi, Yuya Unno, Hisashi Kashima, Naoaki Ok...
Kernel summations are a ubiquitous key computational bottleneck in many data analysis methods. In this paper, we attempt to marry, for the first time, the best relevant technique...
Dongryeol Lee, Richard W. Vuduc, Alexander G. Gray
Branch-and-bound algorithms are general methods applicable to various combinatorial optimization problems and parallelization is one of the most hopeful methods to improve these a...