Gabriel Ghinita
Artificial Intelligence · 2007–2014
A researcher in the Science corpus: 5 papers; trusts 41 researchers and is trusted by 8 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 51 citations into it; #14,664 of 35,345 by trust here, #12,974 by citations
- Sociology and Political Science — 24 citations into it; #16,464 of 22,756 by trust here, #15,556 by citations
- Privacy & Security — 15 citations into it
- Computer Science Applications — 12 citations into it; #807 of 1,855 by trust here, #524 by citations
- Computer Networks and Communications — 10 citations into it
- Signal Processing — 8 citations into it
- Computer Vision and Pattern Recognition — 7 citations into it
- Information Systems — 5 citations into it
Whom Gabriel Ghinita trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Pierangela Samarati
- Latanya Sweeney
- Mohamed F. Mokbel
- Chi-Yin Chow
- Bugra Gedik
- Kristen LeFevre
- Yufei Tao
- Roberto J. Bayardo Jr.
- Rakesh Agrawal
- Panos Kalnis
Who trusts Gabriel Ghinita overall
- Yu Zheng
- Manolis Terrovitis
- Panos Kalnis
- Alina Campan
- Xiaofang Zhou
- Reza Shokri
- Femi G. Olumofin
- Mohamed F. Mokbel
- Nikos Mamoulis
- Arvind Narayanan
Papers from Gabriel Ghinita's perspective
Ordered by how strongly the researchers Gabriel Ghinita trusts endorse each paper. Same corpus, a different order for every researcher.
- k-Anonymity: A Model for Protecting Privacy
- Protecting Respondents' Identities in Microdata Release
- On the complexity of optimal K-anonymity (ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems)
- Incognito: efficient full-domain K-anonymity (ACM SIGMOD Conference)
- Privacy Preserving Data Mining
- L-diversity: privacy beyond k-anonymity
- Calibrating Noise to Sensitivity in Private Data Analysis
- Security-control methods for statistical databases: a comparative study
- ImageNet classification with deep convolutional neural networks
- Data privacy through optimal k-anonymization (IEEE International Conference on Data Engineering)
Their papers
- PRIVE: anonymous location-based queries in distributed mobile systems (2007) — 460 citations
- A Framework for Protecting Worker Location Privacy in Spatial Crowdsourcing (2014) — 370 citations
- Private queries in location based services: anonymizers are not necessary (2008) — 893 citations
- Preventing Location-Based Identity Inference in Anonymous Spatial Queries (2007) — 754 citations
- Fast Data Anonymization with Low Information Loss (2007) — 358 citations