Panos Kalnis
Artificial Intelligence · 2001–2019
A researcher in the Science corpus: 11 papers; trusts 56 researchers and is trusted by 14 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 98 citations into it; #14,215 of 35,345 by trust here, #12,244 by citations
- Computer Vision and Pattern Recognition — 37 citations into it
- Computer Networks and Communications — 31 citations into it
- Information Systems — 24 citations into it; #6,453 of 8,771 by trust here, #4,188 by citations
- Sociology and Political Science — 24 citations into it; #13,626 of 22,756 by trust here, #12,801 by citations
- Molecular Biology — 21 citations into it; #12,073 of 17,773 by trust here, #15,531 by citations
- Signal Processing — 17 citations into it; #5,855 of 7,572 by trust here, #3,673 by citations
- ML Systems & Hardware — 16 citations into it
Whom Panos Kalnis trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Pierangela Samarati
- Latanya Sweeney
- Mohamed F. Mokbel
- Chi-Yin Chow
- Kristen LeFevre
- Roberto J. Bayardo Jr.
- Yufei Tao
- Rakesh Agrawal
- Hans-Peter Kriegel
- Bugra Gedik
Who trusts Panos Kalnis overall
- Yu Zheng
- Reza Shokri
- Gabriel Ghinita
- Xiaofang Zhou
- Mohamed F. Mokbel
- Gowtham Atluri
- Hoyoung Jeung
- Man Lung Yiu
- Chi-Yin Chow
- Anuj Karpatne
Papers from Panos Kalnis's perspective
Ordered by how strongly the researchers Panos Kalnis trusts endorse each paper. Same corpus, a different order for every researcher.
- k-Anonymity: A Model for Protecting Privacy
- ImageNet classification with deep convolutional neural networks
- Protecting Respondents' Identities in Microdata Release
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- 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)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Privacy Preserving Data Mining
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
Their papers
- Privacy-preserving anonymization of set-valued data (2008) — 356 citations
- PRIVE: anonymous location-based queries in distributed mobile systems (2007) — 460 citations
- DEEP: a general computational framework for predicting enhancers (2014) — 123 citations
- Scaling Distributed Machine Learning with In-Network Aggregation (2019) — 553 citations
- GRAMI: Frequent Subgraph and Pattern Mining in a Single Large Graph (2014) — 335 citations
- Mizan: a system for dynamic load balancing in large-scale graph processing (2013) — 337 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
- On Discovering Moving Clusters in Spatio-temporal Data (2005) — 490 citations
- Efficient OLAP Operations in Spatial Data Warehouses (2001) — 384 citations