733 citations
- Cornell UniversityUS11 papers
- Jacobs InstituteUS3 papers
- Cornell Lab of Ornithology1 paper
- École Polytechnique Fédérale de LausanneCH1 paper
- International University of the CaribbeanJM1 paper
- Max Planck Institute for InformaticsDE1 paper
- Menlo SchoolUS1 paper
- Meta (United States)US1 paper
- Stanford UniversityUS1 paper
- The Ohio State UniversityUS1 paper
- Twitter (United States)US1 paper
- Università della Svizzera italianaCH1 paper
11 papers
When Do People Trust Their Social Groups?
Xiao Ma, Justin Cheng, Shankar Iyer +1
Trust facilitates cooperation and supports positive outcomes in social groups, including member satisfaction, information sharing, and task performance. Extensive prior research ha…
The Profiling Potential of Computer Vision and the Challenge of Computational Empiricism
Jake Goldenfein
Computer vision and other biometrics data science applications have commenced a new project of profiling people. Rather than using 'transaction generated information', these system…
"Birds in the Clouds": Adventures in Data Engineering
N. Cherel, J. Reesman, A. Sahuguet +2
Leveraging their eBird crowdsourcing project, the Cornell Lab of Ornithology generates sophisticated Spatio-Temporal Exploratory Model (STEM) maps of bird migrations. Such maps are…
Machine Learning Models that Remember Too Much
Congzheng Song, Thomas Ristenpart, Vitaly Shmatikov
Machine learning (ML) is becoming a commodity. Numerous ML frameworks and services are available to data holders who are not ML experts but want to train predictive models on their…
Plausible Deniability for Privacy-Preserving Data Synthesis
Vincent Bindschaedler, Reza Shokri, Carl A. Gunter
Releasing full data records is one of the most challenging problems in data privacy. On the one hand, many of the popular techniques such as data de-identification are problematic…
Path Planning with Divergence-Based Distance Functions
Renjie Chen, Craig Gotsman, Kai Hormann
Distance functions between points in a domain are sometimes used to automatically plan a gradient-descent path towards a given target point in the domain, avoiding obstacles that m…