Daniel Ting

According to our database, Daniel Ting authored at least 28 papers between 2008 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Sketch-Flip-Merge: Mergeable Sketches for Private Distinct Counting.

Jonathan Hehir, Daniel Ting, Graham Cormode

Proceedings of the International Conference on Machine Learning, 2023

2022

Breaking Cuckoo Hash: Black Box Attacks.

Pedro Reviriego, Daniel Ting

IEEE Trans. Dependable Secur. Comput., 2022

(Nearly) All Cardinality Estimators Are Differentially Private.

Charlie Dickens, Justin Thaler, Daniel Ting

CoRR, 2022

Adaptive Threshold Sampling.

Daniel Ting

Proceedings of the SIGMOD '22: International Conference on Management of Data, Philadelphia, PA, USA, June 12, 2022

Statistical Schema Learning with Occam's Razor.

Justin Talbot, Daniel Ting

Proceedings of the SIGMOD '22: International Conference on Management of Data, Philadelphia, PA, USA, June 12, 2022

Order-Invariant Cardinality Estimators Are Differentially Private.

Charlie Dickens, Justin Thaler, Daniel Ting

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

More Accurate Streaming Cardinality Estimation With Vectorized Counters.

Valerio Bruschi, Pedro Reviriego, Salvatore Pontarelli, Daniel Ting, Giuseppe Bianchi

IEEE Netw. Lett., 2021

Simple, Optimal Algorithms for Random Sampling Without Replacement.

Daniel Ting

CoRR, 2021

Conditional Cuckoo Filters.

Daniel Ting, Rick Cole

Proceedings of the SIGMOD '21: International Conference on Management of Data, 2021

2020

Security of HyperLogLog (HLL) Cardinality Estimation: Vulnerabilities and Protection.

Pedro Reviriego, Daniel Ting

IEEE Commun. Lett., 2020

Fast Updates for Line-Rate HyperLogLog-Based Cardinality Estimation.

Pedro Reviriego, Valerio Bruschi, Salvatore Pontarelli, Daniel Ting, Giuseppe Bianchi

IEEE Commun. Lett., 2020

HyperLogLog (HLL) Security: Inflating Cardinality Estimates.

Pedro Reviriego, Pablo Adell, Daniel Ting

CoRR, 2020

Manifold Learning via Manifold Deflation.

Daniel Ting, Michael I. Jordan

CoRR, 2020

Data Sketching for Real Time Analytics: Theory and Practice.

Daniel Ting, Jonathan Malkin, Lee Rhodes

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

2019

Learning to optimize federated queries.

Liqi Xu, Richard L. Cole, Daniel Ting

Proceedings of the Second International Workshop on Exploiting Artificial Intelligence Techniques for Data Management, 2019

Approximate Distinct Counts for Billions of Datasets.

Daniel Ting

Proceedings of the 2019 International Conference on Management of Data, 2019

2018

Data Sketches for Disaggregated Subset Sum and Frequent Item Estimation.

Daniel Ting

Proceedings of the 2018 International Conference on Management of Data, 2018

Optimal Subsampling with Influence Functions.

Daniel Ting, Eric Brochu

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Count-Min: Optimal Estimation and Tight Error Bounds using Empirical Error Distributions.

Daniel Ting

Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

2017

Optimal Sub-sampling with Influence Functions.

Daniel Ting, Eric Brochu

CoRR, 2017

Adaptive Threshold Sampling and Estimation.

Daniel Ting

CoRR, 2017

2016

Towards Optimal Cardinality Estimation of Unions and Intersections with Sketches.

Daniel Ting

Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

2014

Streamed approximate counting of distinct elements: beating optimal batch methods.

Daniel Ting

Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2014

2013

Mixture models of endhost network traffic.

John Mark Agosta, Jaideep Chandrashekar, Mark Crovella, Nina Taft, Daniel Ting

Proceedings of the IEEE INFOCOM 2013, Turin, Italy, April 14-19, 2013, 2013

2010

Neighbor-Dependent Ramachandran Probability Distributions of Amino Acids Developed from a Hierarchical Dirichlet Process Model.

Daniel Ting, Guoli Wang, Maxim V. Shapovalov, Rajib Mitra, Michael I. Jordan, Roland L. Dunbrack Jr.

PLoS Comput. Biol., 2010

Online Semi-Supervised Learning on Quantized Graphs.

Michal Valko, Branislav Kveton, Ling Huang, Daniel Ting

Proceedings of the UAI 2010, 2010

An Analysis of the Convergence of Graph Laplacians.

Daniel Ting, Ling Huang, Michael I. Jordan

Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

2008

Random orthogonal matrix masking methodology for microdata release.

Daniel Ting, Stephen E. Fienberg, Mario Trottini

Int. J. Inf. Comput. Secur., 2008