BlogCatalog / Cambridge University Press / Neural Networks / Quk eT Ae / eT A (4) eT Ae / Intel / /
Country
Korea / /
Currency
pence / / /
Facility
College Football / ARPACK library / /
IndustryTerm
electronic media / equivalent network / web analysis / graph mining / matrix product / iterative algorithm / online parameters tuning / established algorithms / large networks / efficient graph algorithms / labeled social networks / community detection algorithms / state-of-theart algorithm / social media / greedy algorithms / markov chain / greedy algorithm / closed form solution / power law / larger and larger networks / social networks / computing / real world networks / information processing systems / efficient algorithms / /
Organization
Cambridge University / Spanish Centre for the Development of Industrial Technology / National Academy of Sciences / International World Wide Web Conference Committee / SEMI / Zachary’s Karate Club / European Union / /
Person
Daniele Quercia / Robin Devooght Amin Mantrach / Martin Saveski / Marco Saerens / SEMI-SUPERVISED LEARNING / Hugues Bersini Alejandro Jaimes / Roosevelt / /
Position
natural random walker / random walker / author / /
PublishedMedium
New Journal of Physics / Proceedings of the National Academy of Sciences / Journal of Physics A / la Recherche / /
Technology
four tested algorithms / efficient graph algorithms / RAM / Av / ModMax algorithm / efficient algorithms / machine learning / introduced algorithm / 5.1 Derived Algorithm / testing community detection algorithms / proposed algorithm / RW ModMax algorithm / state-of-theart algorithm / greedy algorithm / 6.7 Running Time Analysis The RW ModMax algorithm / iterative algorithm / presented algorithms / be extracted using an iterative algorithm / /
Random Walks Based Modularity: Application to Semi-Supervised Learning Robin Devooght Amin Mantrach