Marco Gruteser
Artificial Intelligence · 2003–2019
A researcher in the Science corpus: 17 papers; trusts 50 researchers and is trusted by 34 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 422 citations into it; #9,989 of 35,345 by trust here, #2,453 by citations
- Computer Networks and Communications — 100 citations into it; #1,571 of 9,886 by trust here, #1,046 by citations
- Computer Vision and Pattern Recognition — 81 citations into it; #6,088 of 21,575 by trust here, #8,021 by citations
- Safety, Robustness & Interpretability — 76 citations into it
- Electrical and Electronic Engineering — 66 citations into it; #3,714 of 16,539 by trust here, #4,002 by citations
- Information Systems — 40 citations into it; #7,148 of 8,771 by trust here, #4,885 by citations
- Sociology and Political Science — 38 citations into it
- Statistics and Probability — 29 citations into it
Whom Marco Gruteser trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Latanya Sweeney
- Baik Hoh
- Alastair R. Beresford
- John Krumm
- Andrei Serjantov
- Sanjit Krishnan Kaul
- Nitin H. Vaidya
- Bugra Gedik
- Kaiming He
- Asim Smailagic
Who trusts Marco Gruteser overall
- Roy D. Yates
- John Krumm
- Sanjit Krishnan Kaul
- Baik Hoh
- Reza Shokri
- Cory Cornelius
- Eytan H. Modiano
- Antzela Kosta
- Isabel Wagner
- Xianwen Wu
Papers from Marco Gruteser's perspective
Ordered by how strongly the researchers Marco Gruteser trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Going deeper with convolutions
- ImageNet Large Scale Visual Recognition Challenge
- Learning Multiple Layers of Features from Tiny Images
- Long Short-Term Memory
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- Advances and Open Problems in Federated Learning (2019) — 9,019 citations
- Federated Learning with Autotuned Communication-Efficient Secure Aggregation (2019) — 84 citations
- E-eyes: device-free location-oriented activity identification using fine-grained WiFi signatures (2014) — 904 citations
- Minimizing age of information in vehicular networks (2011) — 840 citations
- Preserving privacy in gps traces via uncertainty-aware path cloaking (2007) — 388 citations
- Enhancing Security and Privacy in Traffic-Monitoring Systems (2006) — 345 citations
- ParkNet: drive-by sensing of road-side parking statistics (2010) — 488 citations
- Protecting privacy, in continuous location-tracking applications (2004) — 295 citations
- Edge Assisted Real-time Object Detection for Mobile Augmented Reality (2019) — 562 citations
- Status updates through queues (2012) — 439 citations
- Real-time status: How often should one update? (2012) — 2,261 citations
- An energy-efficient mobile recommender system (2010) — 371 citations
- Security and Privacy Vulnerabilities of In-Car Wireless Networks: A Tire Pressure Monitoring System Case Study (2010) — 451 citations
- Wireless device identification with radiometric signatures (2008) — 895 citations
- Virtual trip lines for distributed privacy-preserving traffic monitoring (2008) — 420 citations
- Protecting Location Privacy Through Path Confusion (2005) — 463 citations
- Enhancing Location Privacy in Wireless LAN Through Disposable Interface Identifiers: A Quantitative Analysis (2003) — 311 citations