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12 papers · 1 filter
Assumed Density Filtering Q-learning
Heejin Jeong, Clark Zhang, George J. Pappas +1
While off-policy temporal difference (TD) methods have widely been used in reinforcement learning due to their efficiency and simple implementation, their Bayesian counterparts hav…
"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…
Uniformly bounded regret in the multi-secretary problem
Alessandro Arlotto, Itai Gurvich
In the secretary problem of Cayley (1875) and Moser (1956), non-negative, independent, random variables with common distribution are sequentially presented to a decision maker…
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…