activity
20102023
most citedMembership Inference Attacks and Defenses in Classification Models

63 citations · 430 across the 44 of their papers we have counts for

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Showing 2014Show all

7 papers · 1 filter

cs.SI2014★ 3 cited

Revisit Behavior in Social Media: The Phoenix-R Model and Discoveries

Flavio Figueiredo, Jussara M. Almeida, Yasuko Matsubara +2

How many listens will an artist receive on a online radio? How about plays on a YouTube video? How many of these visits are new or returning users? Modeling and mining popularity d…

cs.SI2014★ 2 cited

Efficient Network Generation Under General Preferential Attachment

James Atwood, Bruno Ribeiro, Don Towsley

Preferential attachment (PA) models of network structure are widely used due to their explanatory power and conceptual simplicity. PA models are able to account for the scale-free…

physics.soc-ph2014★ 2 cited

Modeling Website Popularity Competition in the Attention-Activity Marketplace

Bruno Ribeiro, Christos Faloutsos

How does a new startup drive the popularity of competing websites into oblivion like Facebook famously did to MySpace? This question is of great interest to academics, technologist…

physics.soc-ph2014★ 5 cited

On the duration and intensity of cumulative advantage competitions

Bo Jiang, Liyuan Sun, Daniel R. Figueiredo +2

The role of skill (fitness) and luck (randomness) as driving forces on the dynamics of resource accumulation in a myriad of systems have long puzzled scientists. Fueled by undisput…

cs.SI2014

Classifying Latent Infection States in Complex Networks

Yeon-sup Lim, Bruno Ribeiro, Don Towsley

Algorithms for identifying the infection states of nodes in a network are crucial for understanding and containing infections. Often, however, only a relatively small set of nodes…

cs.SI2014★ 25 cited

Online Dating Recommendations: Matching Markets and Learning Preferences

Kun Tu, Bruno Ribeiro, Hua Jiang +4

Recommendation systems for online dating have recently attracted much attention from the research community. In this paper we proposed a two-side matching framework for online dati…