Aim of this work is to apply a novel comprehensive machine learning tool for data mining to preprocessing and interpretation of gene expression data. Furthermore, some visualizatio...
Roberto Amato, Angelo Ciaramella, N. Deniskina, Ca...
The success of tensor-based subspace learning depends heavily on reducing correlations along the column vectors of the mode-k flattened matrix. In this work, we study the problem ...
Shuicheng Yan, Dong Xu, Stephen Lin, Thomas S. Hua...
An optimizing compiler has a hard time to generate a code which will perform at top speed for an arbitrary data set size. In general, the low level optimization process must take i...
The signature of neuronal assemblies is the higher-order correlation structure of the spiking activity of the participating neurons. Due to the rapid progress in recording technol...
In this paper, we propose a fast, memory-efficient, and scalable clustering algorithm for analyzing transactional data. Our approach has three unique features. First, we use the c...