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...
Background: Nonnegative Matrix Factorization (NMF) is an unsupervised learning technique that has been applied successfully in several fields, including signal processing, face re...
We use unsupervised probabilistic machine learning ideas to try to explain the kinds of learning observed in real neurons, the goal being to connect abstract principles of self-or...
We present an approach to low-level vision that combines two main ideas: the use of convolutional networks as an image processing architecture and an unsupervised learning procedu...
Background: In metagenomic studies, a process called binning is necessary to assign contigs that belong to multiple species to their respective phylogenetic groups. Most of the cu...
Chon-Kit Kenneth Chan, Arthur L. Hsu, Saman K. Hal...