… Valentini. Effectiveness of error correcting output codes in multiclass learning problems. In …
Valentini. Upper bounds on the training error of ECOC-SVM ensembles. Technical Report TR-…

Bias-variance analysis provides a tool to study learning algorithms and can be used to properly
design ensemble methods well tuned to the properties of a specific base learner. Indeed …

Recently, bias-variance decomposition of error has been used as a tool to study the behavior
of learning algorithms and to develop new ensemble methods well suited to the bias-…

Background A major bottleneck in our understanding of the molecular underpinnings of life
is the assignment of function to proteins. While molecular experiments provide the most …

Two major constraints demand more consideration for energy efficiency in cluster computing:
(a) operational costs, and (b) system reliability. Increasing energy efficiency in cluster …

Background The Critical Assessment of Functional Annotation (CAFA) is an ongoing, global,
community-driven effort to evaluate and improve the computational annotation of protein …

The interpretation of non-coding variants still constitutes a major challenge in the application
of whole-genome sequencing in Mendelian disease, especially for single-nucleotide and …

Background Stratification of patients with post-acute sequelae of SARS-CoV-2 infection (PASC,
or long COVID) would allow precision clinical management strategies. However, long …

Levulinic acid (LA) is one of the top bio-based platform molecules that can be converted into
many valuable chemicals. It can be produced by acid catalysis from renewable resources, …

Gene function prediction is a complex computational problem, characterized by several
items: the number of functional classes is large, and a gene may belong to multiple classes; …