Publications

2023

1. IEEE BigData

   Matching Noisy Keys for Obfuscation

   Charlie Dickens, Eric Bax

   In IEEE International Conference on Big Data (Special Session on Security and Privacy) 2023

   Bib PDF

   @inproceedings{DickensBax23,
     author = {Charlie Dickens, Eric Bax},
     title = {Matching Noisy Keys for Obfuscation},
     booktitle = {IEEE International Conference on Big Data (Special Session on Security and Privacy)},
     year = {2023},
   }

2022

1. NeurIPS

   Order-Invariant Cardinality Estimators Are Differentially Private

   Charlie Dickens, Justin Thaler,  and Ting, Daniel

   In NeurIPS 2022

   Bib PDF

   @inproceedings{DickensThalerTing22,
     author = {Charlie Dickens, Justin Thaler and Ting, Daniel},
     title = {Order-Invariant Cardinality Estimators Are Differentially Private},
     booktitle = {NeurIPS},
     year = {2022},
   }

2021

1. PODS

   Subspace exploration: Bounds on Projected Frequency Estimation

   Cormode, Graham, Dickens, Charlie,  and Woodruff, David P.

   In ACM Principles of Database Systems (PODS) 2021

   Bib PDF

   @inproceedings{CormodeDickensWoodruff20,
     author = {Cormode, Graham and Dickens, Charlie and Woodruff, David P.},
     title = {Subspace exploration: Bounds on Projected Frequency Estimation},
     booktitle = {{ACM} Principles of Database Systems ({PODS})},
     publisher = {{ACM}},
     year = {2021},
   }

2. PhD

   On the Efficiency of Finding and Using Tabular Data Summaries: Scalability, Accuracy, and Hardness

   Dickens, Charlie

   2021

   Bib PDF

   @article{Dickens21thesis,
     author = {Dickens, Charlie},
     title = {On the Efficiency of Finding and Using Tabular Data Summaries: Scalability, Accuracy, and Hardness},
     year = {2021},
   }

2020

1. Preprint

   Interpretable Anomaly Detection with Mondrian Pólya Forests on Data Streams

   Dickens, Charlie, Meissner, Eric,  Moreno, Pablo G and 1 more author

   arXiv preprint arXiv:2008.01505 2020

   Bib PDF

   @article{dickens2020interpretable,
     title = {Interpretable Anomaly Detection with Mondrian P{\'o}lya Forests on Data Streams},
     author = {Dickens, Charlie and Meissner, Eric and Moreno, Pablo G and Diethe, Tom},
     journal = {arXiv preprint arXiv:2008.01505},
     year = {2020},
   }

2019

1. N1OPT

   Iterative Hessian Sketch in Input Sparsity Time

   Cormode, Graham,  and Dickens, Charlie

   In NeurIPS Workshop: Beyond First-Order Optimization Methods in Machine Learning 2019

   Bib PDF

   @inproceedings{cormode2019iterative,
     title = {Iterative Hessian Sketch in Input Sparsity Time},
     author = {Cormode, Graham and Dickens, Charlie},
     booktitle = {NeurIPS Workshop: Beyond First-Order Optimization Methods in Machine Learning},
     year = {2019},
   }

2018

1. ICML

   Leveraging Well-Conditioned Bases: Streaming and Distributed Summaries in Minkowski p-Norms

   Cormode, Graham, Dickens, Charlie,  and Woodruff, David P.

   In International Conference on Machine Learning 2018

   Bib PDF

   @inproceedings{pmlr-v80-dickens18a,
     title = {Leveraging Well-Conditioned Bases: Streaming and Distributed Summaries in {M}inkowski $p$-Norms},
     author = {Cormode, Graham and Dickens, Charlie and Woodruff, David P.},
     booktitle = {International Conference on Machine Learning},
     year = {2018},
   }