Gradient-based methods for solving non-negative matrix tri-factorization problem : Code and data

Povh, Janez (avtor), Hribar, Rok (avtor)

Code and data used in paper "Gradient-based methods for solving non-negative matrix tri-factorization problem". GitLab: symmetric NMTF, Project ID: 1360, 3 branches, total 5.4 GB files. History: 06 Jul, 2020 3 commits. ZIP in this repository contains code and small amount of data used in code examples. Full data is available from GitLab.

• Jezik: Angleški jezik
• Ključne besede: non-negative matrix factorization, p-matching problem, data co-clustering, patients sub-typing, drug repurposing, high-performance computing
• Organizacija: FS - Fakulteta za strojništvo
• Leto izida: 2020
• PID: 20.500.12556/RUL-117359

Avtorske pravice

No license. All rights reserved.

Opomba

With regard to the type and amount of data one requires, three options are available: 1. code and small amount of data used in code examples (~1M): git clone --single-branch https://repo.ijs.si/hribarr/symmetric-nmtf.git; 2. code and real-world data used in the paper (~210M): git clone --single-branch https://repo.ijs.si/hribarr/symmetric-nmtf.git -b real-data; 3. code, real-world data and synthetic data used in the paper (~14G): git clone --single-branch https://repo.ijs.si/hribarr/symmetric-nmtf.git -b full-data.

• Datum objave v RUL: 08.07.2020

Sekundarni jezik

• Jezik: Slovenski jezik
• Ključne besede: nenegativna matrična faktorizacija, problem p-prirejanja, so-gručenje podatkov, serotipizacija pacientov, nova uporabnost zdravil, super-računalništvo

Projekti

• Financer: ARRS - Agencija za raziskovalno dejavnost Republike Slovenije
• Številka projekta: J1-8155
• Naslov: ZLIVANJE BIOMEDICINSKIH PODATKOV Z UPORABO NENEGATIVNE MATRIČNE TRI-FAKTORIZACIJE