Giovanni Felici and Cited - Free people check

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A-priori upper bounds for the set covering problem - IDEAS ...

ideas.repec.org

by G Felici · · Cited by 4 — Giovanni Felici & Sokol Ndreca & Aldo Procacci & Benedetto Scoppola, "A-priori upper bounds for the set covering problem," Annals of Operations ... › spr › annopr

DNA barcoding of recently diverged species - PubMed

pubmed.ncbi.nlm.nih.gov

by R van Velzen · · Cited by 179 — Authors. Robin van Velzen , Emanuel Weitschek, Giovanni Felici, Freek T Bakker. Affiliation. 1 Biosystematics Group, Wageningen University, Wageningen, ... › ...

LAF: Logic Alignment Free and its application to bacterial ...

biodatamining.biomedcentral.com

by E Weitschek · · Cited by 17 — LAF: Logic Alignment Free and its application to bacterial genomes classification. Emanuel Weitschek,; Fabio Cunial &; Giovanni Felici. › articles

Data Mining and Knowledge Discovery SpringerLink

link.springer.com

by C Orsenigo · Cited by 4 — Evangelos Triantaphyllou; Giovanni Felici. Provides a unique perspective into the core of data mining and knowledge discovery (DM and KD), combining many ... › book

All web results to the name "Giovanni Felici"

DNA Barcoding of Recently Diverged Species - PLOS

journals.plos.org

by R van Velzen · · Cited by 179 — Giovanni Felici,. Affiliation Istituto di Analisi dei Sistemi e Informatica Antonio Ruberti, Consiglio Nazionale delle Ricerche, Rome, Italy. › plosone › article › journal.po...

Filtering with alignment free distances for high throughput ...

journal.embnet.org

by MC De Cola · · Cited by 2 — Filtering with alignment free distances for high throughput DNA reads assembly. Maria C De Cola, Giovanni Felici, Daniele Santoni, Emanuel Weitschek ... › index.php › article › view

How to extract meaningful data from machine learning classifiers

www.inderscienceonline.com

by G Ateniese · · Cited by 305 — Giovanni Felici. Institute for Systems Analysis and Computer Science "Antonio Ruberti", CNR, Italy, Via dei Taurini 19, Rome, Italy. › IJSN

MIP-BOOST: Efficient and Effective L 0 Feature Selection for ...

pennstate.pure.elsevier.com

by A Kenney · · Cited by 7 — MIP-BOOST: Efficient and Effective L 0 Feature Selection for Linear Regression. Ana Kenney, Francesca Chiaromonte, Giovanni Felici. › publications