Graham Cormode

ORCID

Publication Activity (10 Years)

Years Active: 2000-2024
Publications (10 Years): 114

Top Venues

University of Warwick, Coventry, UK (PHD)

Education History

University of Warwick, Coventry, UK

PHD

Publications

Graham Cormode
Technical Perspective on 'Better Differentially Private Approximate Histograms and Heavy Hitters using the Misra-Gries Sketch'. SIGMOD Rec. 53 (1) (2024)
Wei-Ning Chen, Graham Cormode, Akash Bharadwaj, Peter Romov, Ayfer Özgür
Federated Experiment Design under Distributed Differential Privacy. AISTATS (2024)
Samuel Maddock, Graham Cormode, Carsten Maple
FLAIM: AIM-based Synthetic Data Generation in the Federated Setting. KDD (2024)
Harsh Kasyap, Ugur-Ilker Atmaca, Carsten Maple, Graham Cormode, Jiancong He
Private and Secure Fuzzy Name Matching. CoRR (2024)
Graham Cormode, Marcel Dall'Agnol, Tom Gur, Chris Hickey
Streaming Zero-Knowledge Proofs. CCC (2024)
Akash Bharadwaj, Graham Cormode
Federated computation: a survey of concepts and challenges. Distributed Parallel Databases 42 (3) (2024)
Graham Cormode, Igor L. Markov, Harish Srinivas
Private and Efficient Federated Numerical Aggregation. EDBT (2024)
Wei-Ning Chen, Ayfer Özgür, Graham Cormode, Akash Bharadwaj
The communication cost of security and privacy in federated frequency estimation. AISTATS (2023)
Samuel Maddock, Graham Cormode, Carsten Maple
FLAIM: AIM-based Synthetic Data Generation in the Federated Setting. CoRR (2023)
Kuntai Cai, Xiaokui Xiao, Graham Cormode
PrivLava: Synthesizing Relational Data with Foreign Keys under Differential Privacy. Proc. ACM Manag. Data 1 (2) (2023)
Graham Cormode
Applications of Sketching and Pathways to Impact. PODS (2023)
Jonathan Hehir, Daniel Ting, Graham Cormode
Sketch-Flip-Merge: Mergeable Sketches for Private Distinct Counting. CoRR (2023)
Kuntai Cai, Xiaokui Xiao, Graham Cormode
PrivLava: Synthesizing Relational Data with Foreign Keys under Differential Privacy. CoRR (2023)
Graham Cormode, Igor L. Markov
Federated Calibration and Evaluation of Binary Classifiers. Proc. VLDB Endow. 16 (11) (2023)
Sayan Ghosh, Karthik Prasad, Xiaoliang Dai, Peizhao Zhang, Bichen Wu, Graham Cormode, Peter Vajda
Pruning Compact ConvNets for Efficient Inference. CoRR (2023)
Jonathan Hehir, Daniel Ting, Graham Cormode
Sketch-Flip-Merge: Mergeable Sketches for Private Distinct Counting. ICML (2023)
Graham Cormode, Marcel Dall'Agnol, Tom Gur, Chris Hickey
Streaming Zero-Knowledge Proofs. CoRR (2023)
Graham Cormode, Zohar S. Karnin, Edo Liberty, Justin Thaler, Pavel Veselý
Relative Error Streaming Quantiles. J. ACM 70 (5) (2023)
Wei-Ning Chen, Graham Cormode, Akash Bharadwaj, Peter Romov, Ayfer Özgür
Federated Experiment Design under Distributed Differential Privacy. CoRR (2023)
Graham Cormode
Technical Perspective on 'R2T: Instance-optimal Truncation for Differentially Private Query Evaluation with Foreign Keys. SIGMOD Rec. 52 (1) (2023)
Ari Biswas, Graham Cormode
Interactive Proofs For Differentially Private Counting. CCS (2023)
Karthik Prasad, Sayan Ghosh, Graham Cormode, Ilya Mironov, Ashkan Yousefpour, Pierre Stock
Reconciling Security and Communication Efficiency in Federated Learning. IEEE Data Eng. Bull. 46 (1) (2023)
Saeed Mahloujifar, Alexandre Sablayrolles, Graham Cormode, Somesh Jha
Optimal Membership Inference Bounds for Adaptive Composition of Sampled Gaussian Mechanisms. CoRR (2022)
Sayan Biswas, Graham Cormode, Carsten Maple
Impact of Sampling on Locally Differentially Private Data Collection. CoRR (2022)
Michael Shekelyan, Graham Cormode, Peter Triantafillou, Ali Mohammadi Shanghooshabad, Qingzhi Ma
Weighted Random Sampling over Joins. CoRR (2022)
Mary Scott, Graham Cormode, Carsten Maple
Aggregation and Transformation of Vector-Valued Messages in the Shuffle Model of Differential Privacy. CoRR (2022)
Ziyue Huang, Yuan Qiu, Ke Yi, Graham Cormode
Frequency Estimation Under Multiparty Differential Privacy: One-shot and Streaming. Proc. VLDB Endow. 15 (10) (2022)
Samuel Maddock, Graham Cormode, Tianhao Wang, Carsten Maple, Somesh Jha
Federated Boosted Decision Trees with Differential Privacy. CCS (2022)
Ari Biswas, Graham Cormode
Verifiable Differential Privacy For When The Curious Become Dishonest. CoRR (2022)
Mary Scott, Graham Cormode, Carsten Maple
Aggregation and Transformation of Vector-Valued Messages in the Shuffle Model of Differential Privacy. IEEE Trans. Inf. Forensics Secur. 17 (2022)
Riccardo Tommasini, Senjuti Basu Roy, Xuan Wang, Hongwei Wang, Heng Ji, Jiawei Han, Preslav Nakov, Giovanni Da San Martino, Firoj Alam, Markus Schedl, Elisabeth Lex, Akash Bharadwaj, Graham Cormode, Milan Dojchinovski, Jan Forberg, Johannes Frey, Pieter Bonte, Marco Balduini, Matteo Belcao, Emanuele Della Valle, Junliang Yu, Hongzhi Yin, Tong Chen, Haochen Liu, Yiqi Wang, Wenqi Fan, Xiaorui Liu, Jamell Dacon, Lingjuan Lye, Jiliang Tang, Aristides Gionis, Stefan Neumann, Bruno Ordozgoiti, Simon Razniewski, Hiba Arnaout, Shrestha Ghosh, Fabian M. Suchanek, Lingfei Wu, Yu Chen, Yunyao Li, Bang Liu, Filip Ilievski, Daniel Garijo, Hans Chalupsky, Pedro A. Szekely, Ilias Kanellos, Dimitris Sacharidis, Thanasis Vergoulis, Nurendra Choudhary, Nikhil Rao, Karthik Subbian, Srinivasan H. Sengamedu, Chandan K. Reddy, Friedhelm Victor, Bernhard Haslhofer, George Katsogiannis-Meimarakis, Georgia Koutrika, Shengmin Jin, Danai Koutra, Reza Zafarani, Yulia Tsvetkov, Vidhisha Balachandran, Sachin Kumar, Xiangyu Zhao, Bo Chen, Huifeng Guo, Yejing Wang, Ruiming Tang, Yang Zhang, Wenjie Wang, Peng Wu, Fuli Feng, Xiangnan He
Accepted Tutorials at The Web Conference 2022. WWW (Companion Volume) (2022)
Akash Bharadwaj, Graham Cormode
An Introduction to Federated Computation. SIGMOD Conference (2022)
Graham Cormode, Akash Bharadwaj
Sample-and-threshold differential privacy: Histograms and applications. AISTATS (2022)
Karthik Prasad, Sayan Ghosh, Graham Cormode, Ilya Mironov, Ashkan Yousefpour, Pierre Stock
Reconciling Security and Communication Efficiency in Federated Learning. CoRR (2022)
Samuel Maddock, Graham Cormode, Tianhao Wang, Carsten Maple, Somesh Jha
Federated Boosted Decision Trees with Differential Privacy. CoRR (2022)
Graham Cormode, Igor L. Markov
Federated Calibration and Evaluation of Binary Classifiers. CoRR (2022)
Wei-Ning Chen, Ayfer Özgür, Graham Cormode, Akash Bharadwaj
The communication cost of security and privacy in federated frequency estimation. CoRR (2022)
Michael Shekelyan, Graham Cormode, Qingzhi Ma, Ali Mohammadi Shanghooshabad, Peter Triantafillou
Streaming Weighted Sampling over Join Queries. EDBT (2022)
Graham Cormode, Zohar Karnin, Edo Liberty, Justin Thaler, Pavel Veselý
Relative Error Streaming Quantiles. SIGMOD Rec. 51 (1) (2022)
Lauren Watson, Chuan Guo, Graham Cormode, Alexandre Sablayrolles
On the Importance of Difficulty Calibration in Membership Inference Attacks. ICLR (2022)
Graham Cormode
Technical Perspective: A Framework for Adversarially Robust Streaming Algorithms. SIGMOD Rec. 50 (1) (2021)
Graham Cormode, Igor L. Markov
Bit-efficient Numerical Aggregation and Stronger Privacy for Trust in Federated Analytics. CoRR (2021)
Graham Cormode, Abhinav Mishra, Joseph Ross, Pavel Veselý
Theory meets Practice at the Median: A Worst Case Comparison of Relative Error Quantile Algorithms. KDD (2021)
Graham Cormode, Samuel Maddock, Carsten Maple
Frequency Estimation under Local Differential Privacy. Proc. VLDB Endow. 14 (11) (2021)
Mary Scott, Graham Cormode, Carsten Maple
Applying the Shuffle Model of Differential Privacy to Vector Aggregation. BICOD (2021)
Graham Cormode, Samuel Maddock, Carsten Maple
Frequency Estimation under Local Differential Privacy [Experiments, Analysis and Benchmarks]. CoRR (2021)
Ziyue Huang, Yuan Qiu, Ke Yi, Graham Cormode
Frequency Estimation Under Multiparty Differential Privacy: One-shot and Streaming. CoRR (2021)
Teddy Cunningham, Graham Cormode, Hakan Ferhatosmanoglu, Divesh Srivastava
Real-World Trajectory Sharing with Local Differential Privacy. CoRR (2021)
Graham Cormode, Minos N. Garofalakis, Michael Shekelyan
Data-Independent Space Partitionings for Summaries. PODS (2021)
Teddy Cunningham, Graham Cormode, Hakan Ferhatosmanoglu
Privacy-Preserving Synthetic Location Data in the Real World. SSTD (2021)
Kook Jin Ahn, Graham Cormode, Sudipto Guha, Andrew McGregor, Anthony Wirth
Correlation Clustering in Data Streams. Algorithmica 83 (7) (2021)
Ashkan Yousefpour, Igor Shilov, Alexandre Sablayrolles, Davide Testuggine, Karthik Prasad, Mani Malek, John Nguyen, Sayan Gosh, Akash Bharadwaj, Jessica Zhao, Graham Cormode, Ilya Mironov
Opacus: User-Friendly Differential Privacy Library in PyTorch. CoRR (2021)
Teddy Cunningham, Graham Cormode, Hakan Ferhatosmanoglu, Divesh Srivastava
Real-World Trajectory Sharing with Local Differential Privacy. Proc. VLDB Endow. 14 (11) (2021)
Michael Shekelyan, Graham Cormode
Sequential Random Sampling Revisited: Hidden Shuffle Method. AISTATS (2021)
Mary Scott, Graham Cormode, Carsten Maple
Applying the Shuffle Model of Differential Privacy to Vector Aggregation. CoRR (2021)
Teddy Cunningham, Graham Cormode, Hakan Ferhatosmanoglu
Privacy-Preserving Synthetic Location Data in the Real World. CoRR (2021)
Graham Cormode, Pavel Veselý
Streaming Algorithms for Bin Packing and Vector Scheduling. Theory Comput. Syst. 65 (6) (2021)
Graham Cormode, Abhinav Mishra, Joseph Ross, Pavel Veselý
Theory meets Practice: worst case behavior of quantile algorithms. CoRR (2021)
Graham Cormode
Current Trends in Data Summaries. SIGMOD Rec. 50 (4) (2021)
Graham Cormode, Tejas Kulkarni, Divesh Srivastava
Constrained Private Mechanisms for Count Data. IEEE Trans. Knowl. Data Eng. 33 (2) (2021)
Graham Cormode, Zohar S. Karnin, Edo Liberty, Justin Thaler, Pavel Veselý
Relative Error Streaming Quantiles. PODS (2021)
Akash Bharadwaj, Graham Cormode
Sample and Threshold Differential Privacy: Histograms and applications. CoRR (2021)
Graham Cormode, Charlie Dickens, David P. Woodruff
Subspace exploration: Bounds on Projected Frequency Estimation. CoRR (2021)
Graham Cormode, Charlie Dickens, David P. Woodruff
Subspace Exploration: Bounds on Projected Frequency Estimation. PODS (2021)
Peter Kairouz, H. Brendan McMahan, Brendan Avent, Aurélien Bellet, Mehdi Bennis, Arjun Nitin Bhagoji, Kallista A. Bonawitz, Zachary Charles, Graham Cormode, Rachel Cummings, Rafael G. L. D'Oliveira, Hubert Eichner, Salim El Rouayheb, David Evans, Josh Gardner, Zachary Garrett, Adrià Gascón, Badih Ghazi, Phillip B. Gibbons, Marco Gruteser, Zaïd Harchaoui, Chaoyang He, Lie He, Zhouyuan Huo, Ben Hutchinson, Justin Hsu, Martin Jaggi, Tara Javidi, Gauri Joshi, Mikhail Khodak, Jakub Konecný, Aleksandra Korolova, Farinaz Koushanfar, Sanmi Koyejo, Tancrède Lepoint, Yang Liu, Prateek Mittal, Mehryar Mohri, Richard Nock, Ayfer Özgür, Rasmus Pagh, Hang Qi, Daniel Ramage, Ramesh Raskar, Mariana Raykova, Dawn Song, Weikang Song, Sebastian U. Stich, Ziteng Sun, Ananda Theertha Suresh, Florian Tramèr, Praneeth Vepakomma, Jianyu Wang, Li Xiong, Zheng Xu, Qiang Yang, Felix X. Yu, Han Yu, Sen Zhao
Advances and Open Problems in Federated Learning. Found. Trends Mach. Learn. 14 (1-2) (2021)
Lauren Watson, Chuan Guo, Graham Cormode, Alexandre Sablayrolles
On the Importance of Difficulty Calibration in Membership Inference Attacks. CoRR (2021)
Graham Cormode, Zohar S. Karnin, Edo Liberty, Justin Thaler, Pavel Veselý
Relative Error Streaming Quantiles. CoRR (2020)
Graham Cormode, Pavel Veselý
A Tight Lower Bound for Comparison-Based Quantile Summaries. PODS (2020)
Graham Cormode, Hossein Jowhari
Samplers and Their Applications: A Survey. ACM Comput. Surv. 52 (1) (2019)
Graham Cormode, Pavel Veselý
Streaming Algorithms for Bin Packing and Vector Scheduling. WAOA (2019)
Graham Cormode, Jacques Dark, Christian Konrad
Independent Sets in Vertex-Arrival Streams. ICALP (2019)
Rajesh Chitnis, Graham Cormode
Towards a Theory of Parameterized Streaming Algorithms. IPEC (2019)
Graham Cormode, Pavel Veselý
Tight Lower Bound for Comparison-Based Quantile Summaries. CoRR (2019)
Rajesh Chitnis, Graham Cormode
Towards a Theory of Parameterized Streaming Algorithms. CoRR (2019)
Graham Cormode
Technical Perspective: #8712;KTELO. SIGMOD Rec. 48 (1) (2019)
Graham Cormode, Charlie Dickens
Iterative Hessian Sketch in Input Sparsity Time. CoRR (2019)
Graham Cormode, Chris Hickey
Efficient Interactive Proofs for Linear Algebra. ISAAC (2019)
Peter Kairouz, H. Brendan McMahan, Brendan Avent, Aurélien Bellet, Mehdi Bennis, Arjun Nitin Bhagoji, Kallista A. Bonawitz, Zachary Charles, Graham Cormode, Rachel Cummings, Rafael G. L. D'Oliveira, Salim El Rouayheb, David Evans, Josh Gardner, Zachary Garrett, Adrià Gascón, Badih Ghazi, Phillip B. Gibbons, Marco Gruteser, Zaïd Harchaoui, Chaoyang He, Lie He, Zhouyuan Huo, Ben Hutchinson, Justin Hsu, Martin Jaggi, Tara Javidi, Gauri Joshi, Mikhail Khodak, Jakub Konecný, Aleksandra Korolova, Farinaz Koushanfar, Sanmi Koyejo, Tancrède Lepoint, Yang Liu, Prateek Mittal, Mehryar Mohri, Richard Nock, Ayfer Özgür, Rasmus Pagh, Mariana Raykova, Hang Qi, Daniel Ramage, Ramesh Raskar, Dawn Song, Weikang Song, Sebastian U. Stich, Ziteng Sun, Ananda Theertha Suresh, Florian Tramèr, Praneeth Vepakomma, Jianyu Wang, Li Xiong, Zheng Xu, Qiang Yang, Felix X. Yu, Han Yu, Sen Zhao
Advances and Open Problems in Federated Learning. CoRR (2019)
Graham Cormode, Pavel Veselý
Streaming Algorithms for Bin Packing and Vector Scheduling. CoRR (2019)
Amit Chakrabarti, Graham Cormode, Andrew McGregor, Justin Thaler, Suresh Venkatasubramanian
Verifiable Stream Computation and Arthur-Merlin Communication. SIAM J. Comput. 48 (4) (2019)
Graham Cormode, Tejas Kulkarni, Divesh Srivastava
Answering Range Queries Under Local Differential Privacy. Proc. VLDB Endow. 12 (10) (2019)
Graham Cormode
Technical perspective: The true cost of popularity. Commun. ACM 62 (8) (2019)
Yu Zhang, Srikanta Tirthapura, Graham Cormode
Learning Graphical Models from a Distributed Stream. ICDE (2018)
Graham Cormode, Jacques Dark
Fast Sketch-based Recovery of Correlation Outliers. ICDT (2018)
Graham Cormode, Tejas Kulkarni, Divesh Srivastava
Constrained Private Mechanisms for Count Data. ICDE (2018)
Graham Cormode, Charlie Dickens, David P. Woodruff
Leveraging Well-Conditioned Bases: Streaming \& Distributed Summaries in Minkowski p-Norms. CoRR (2018)
Graham Cormode, Somesh Jha, Tejas Kulkarni, Ninghui Li, Divesh Srivastava, Tianhao Wang
Privacy at Scale: Local Differential Privacy in Practice. SIGMOD Conference (2018)
Graham Cormode, Chris Hickey
You Can Check Others' Work More Quickly Than Doing It Yourself. ICDE (2018)
Chris Hickey, Graham Cormode
Cheap Checking for Cloud Computing: Statistical Analysis via Annotated Data Streams. AISTATS (2018)
Graham Cormode, Charlie Dickens, David P. Woodruff
Leveraging Well-Conditioned Bases: Streaming and Distributed Summaries in Minkowski p-Norms. ICML (2018)
Kook Jin Ahn, Graham Cormode, Sudipto Guha, Andrew McGregor, Anthony Wirth
Correlation Clustering in Data Streams. CoRR (2018)
Graham Cormode, Jacques Dark, Christian Konrad
Approximating the Caro-Wei Bound for Independent Sets in Graph Streams. ISCO (2018)
Graham Cormode, Jacques Dark, Christian Konrad
Independent Sets in Vertex-Arrival Streams. CoRR (2018)
Graham Cormode, Tejas Kulkarni, Divesh Srivastava
Marginal Release Under Local Differential Privacy. SIGMOD Conference (2018)
Graham Cormode
Data Summarization and Distributed Computation. PODC (2018)
Tejas Kulkarni, Graham Cormode, Divesh Srivastava
Answering Range Queries Under Local Differential Privacy. CoRR (2018)
Graham Cormode
Engineering Streaming Algorithms. SEA (2017)
Graham Cormode, Tejas Kulkarni, Divesh Srivastava
Constrained Differential Privacy for Count Data. CoRR (2017)
Graham Cormode, Jacques Dark
Fast Sketch-based Recovery of Correlation Outliers. CoRR (2017)
Graham Cormode, Hossein Jowhari
A second look at counting triangles in graph streams (corrected). Theor. Comput. Sci. 683 (2017)

Graham Cormode.css-eqlu8i{font-size:small;padding-left:4px;}

Publication Activity (10 Years)

Top Topics

Top Venues

Graham Cormode