Edith Cohen

ORCID

Publication Activity (10 Years)

Years Active: 1989-2024
Publications (10 Years): 56

Top Venues

CoRR

ICML

Proc. ACM Meas. Anal. Comput. Syst.

KDD

Publications

Sara Ahmadian, Edith Cohen
Unmasking Vulnerabilities: Cardinality Sketches under Adaptive Inputs. CoRR (2024)
Edith Cohen, Haim Kaplan, Yishay Mansour, Shay Moran, Kobbi Nissim, Uri Stemmer, Eliad Tsfadia
Data Reconstruction: When You See It and When You Don't. CoRR (2024)
Edith Cohen, Xin Lyu, Jelani Nelson, Tamás Sarlós, Uri Stemmer
Lower Bounds for Differential Privacy Under Continual Observation and Online Threshold Queries. COLT (2024)
Edith Cohen, Xin Lyu, Jelani Nelson, Tamás Sarlós, Uri Stemmer
Lower Bounds for Differential Privacy Under Continual Observation and Online Threshold Queries. CoRR (2024)
Edith Cohen, Xin Lyu, Jelani Nelson, Tamás Sarlós, Uri Stemmer
Lower Bounds for Differential Privacy Under Continual Observation and Online Threshold Queries. IACR Cryptol. ePrint Arch. 2024 (2024)
Idan Attias, Edith Cohen, Moshe Shechner, Uri Stemmer
A Framework for Adversarial Streaming via Differential Privacy and Difference Estimators. ITCS (2023)
Edith Cohen
Sampling Big Ideas in Query Optimization. PODS (2023)
Edith Cohen, Xin Lyu, Jelani Nelson, Tamás Sarlós, Uri Stemmer
Optimal Differentially Private Learning of Thresholds and Quasi-Concave Optimization. STOC (2023)
Edith Cohen, Jelani Nelson, Tamás Sarlós, Uri Stemmer
Tricking the Hashing Trick: A Tight Lower Bound on the Robustness of CountSketch to Adaptive Inputs. AAAI (2023)
Edith Cohen, Xin Lyu, Jelani Nelson, Tamás Sarlós, Uri Stemmer
Generalized Private Selection and Testing with High Confidence. ITCS (2023)
Edith Cohen, Xin Lyu, Jelani Nelson, Tamás Sarlós, Uri Stemmer
Hot PATE: Private Aggregation of Distributions for Diverse Task. CoRR (2023)
Edith Cohen, Xin Lyu
The Target-Charging Technique for Privacy Accounting across Interactive Computations. CoRR (2023)
Edith Cohen, Xin Lyu
The Target-Charging Technique for Privacy Analysis across Interactive Computations. NeurIPS (2023)
Edith Cohen, Xin Lyu, Jelani Nelson, Tamás Sarlós, Uri Stemmer
Õptimal Differentially Private Learning of Thresholds and Quasi-Concave Optimization. CoRR (2022)
Edith Cohen, Xin Lyu, Jelani Nelson, Tamás Sarlós, Uri Stemmer
Generalized Private Selection and Testing with High Confidence. CoRR (2022)
Edith Cohen, Xin Lyu, Jelani Nelson, Tamás Sarlós, Moshe Shechner, Uri Stemmer
On the Robustness of CountSketch to Adaptive Inputs. CoRR (2022)
Eliad Tsfadia, Edith Cohen, Haim Kaplan, Yishay Mansour, Uri Stemmer
FriendlyCore: Practical Differentially Private Aggregation. ICML (2022)
Edith Cohen, Xin Lyu, Jelani Nelson, Tamás Sarlós, Moshe Shechner, Uri Stemmer
On the Robustness of CountSketch to Adaptive Inputs. ICML (2022)
Niklas Carlsson, Edith Cohen, Philippe Robert
POMACS V6, N1, March 2022 Editorial. Proc. ACM Meas. Anal. Comput. Syst. 6 (1) (2022)
Niklas Carlsson, Edith Cohen, Philippe Robert
POMACS V6, N2, June 2022 Editorial. Proc. ACM Meas. Anal. Comput. Syst. 6 (2) (2022)
Edith Cohen, Jelani Nelson, Tamás Sarlós, Uri Stemmer
Tricking the Hashing Trick: A Tight Lower Bound on the Robustness of CountSketch to Adaptive Inputs. CoRR (2022)
Idan Attias, Edith Cohen, Moshe Shechner, Uri Stemmer
A Framework for Adversarial Streaming via Differential Privacy and Difference Estimators. CoRR (2021)
Eliad Tsfadia, Edith Cohen, Haim Kaplan, Yishay Mansour, Uri Stemmer
FriendlyCore: Practical Differentially Private Aggregation. CoRR (2021)
Edith Cohen
Editorial. ACM Trans. Algorithms 17 (3) (2021)
Niklas Carlsson, Edith Cohen, Philippe Robert
POMACS V5, N3, December 2021 Editorial. Proc. ACM Meas. Anal. Comput. Syst. 5 (3) (2021)
Edith Cohen, Haim Kaplan, Yishay Mansour, Uri Stemmer, Eliad Tsfadia
Differentially-Private Clustering of Easy Instances. CoRR (2021)
Edith Cohen, Ofir Geri, Tamás Sarlós, Uri Stemmer
Differentially Private Weighted Sampling. AISTATS (2021)
Edith Cohen, Haim Kaplan, Yishay Mansour, Uri Stemmer, Eliad Tsfadia
Differentially-Private Clustering of Easy Instances. ICML (2021)
Edith Cohen, Rasmus Pagh, David P. Woodruff
-Sampling Without Replacement. CoRR (2020)
Edith Cohen, Rasmus Pagh, David P. Woodruff
-Sampling Without Replacement. NeurIPS (2020)
Eliav Buchnik, Edith Cohen
Graph Learning with Loss-Guided Training. CoRR (2020)
Edith Cohen, Ofir Geri, Rasmus Pagh
Composable Sketches for Functions of Frequencies: Beyond the Worst Case. CoRR (2020)
Eliav Buchnik, Edith Cohen
Graph Learning with Loss-Guided Training. GRADES-NDA@SIGMOD (2020)
Gal Sadeh, Edith Cohen, Haim Kaplan
Sample Complexity Bounds for Influence Maximization. ITCS (2020)
Edith Cohen, Ofir Geri, Tamás Sarlós, Uri Stemmer
Differentially Private Weighted Sampling. CoRR (2020)
Edith Cohen, Ofir Geri, Rasmus Pagh
Composable Sketches for Functions of Frequencies: Beyond the Worst Case. ICML (2020)
Eliav Buchnik, Edith Cohen, Avinatan Hassidim, Yossi Matias
Self-similar Epochs: Value in arrangement. ICML (2019)
Edith Cohen, Ofir Geri
Sampling Sketches for Concave Sublinear Functions of Frequencies. NeurIPS (2019)
Edith Cohen, Ofir Geri
Sampling Sketches for Concave Sublinear Functions of Frequencies. CoRR (2019)
Gal Sadeh, Edith Cohen, Haim Kaplan
Influence Maximization with Few Simulations. CoRR (2019)
Eliav Buchnik, Edith Cohen
Bootstrapped Graph Diffusions: Exposing the Power of Nonlinearity. SIGMETRICS (Abstracts) (2018)
Eliav Buchnik, Edith Cohen
Bootstrapped Graph Diffusions: Exposing the Power of Nonlinearity. Proc. ACM Meas. Anal. Comput. Syst. 2 (1) (2018)
Eliav Buchnik, Edith Cohen, Avinatan Hassidim, Yossi Matias
LSH Microbatches for Stochastic Gradients: Value in Rearrangement. CoRR (2018)
Edith Cohen, Shiri Chechik, Haim Kaplan
Clustering Small Samples With Quality Guarantees: Adaptivity With One2all PPS. AAAI (2018)
Edith Cohen
Stream Sampling Framework and Application for Frequency Cap Statistics. ACM Trans. Algorithms 14 (4) (2018)
Shir Landau Feibish, Yehuda Afek, Anat Bremler-Barr, Edith Cohen, Michal Shagam
Mitigating DNS random subdomain DDoS attacks by distinct heavy hitters sketches. HotWeb (2017)
Eliav Buchnik, Edith Cohen
Bootstrapped Graph Diffusions: Exposing the Power of Nonlinearity. CoRR (2017)
Edith Cohen, Shiri Chechik, Haim Kaplan
Clustering over Multi-Objective Samples: The one2all Sample. CoRR (2017)
Edith Cohen
HyperLogLog Hyperextended: Sketches for Concave Sublinear Frequency Statistics. KDD (2017)
Edith Cohen
Greedy Maximization Framework for Graph-based Influence Functions. CoRR (2016)
Edith Cohen
Estimating Frequency Statistics through Distinct Count Measurements. CoRR (2016)
Edith Cohen, Graham Cormode, Nick G. Duffield, Carsten Lund
On the Tradeoff between Stability and Fit. ACM Trans. Algorithms 13 (1) (2016)
Yehuda Afek, Anat Bremler-Barr, Edith Cohen, Shir Landau Feibish, Michal Shagam
Efficient Distinct Heavy Hitters for DNS DDoS Attack Detection. CoRR (2016)
Edith Cohen
Semi-Supervised Learning for Asymmetric Graphs through Reach and Distance Diffusion. CoRR (2016)
Eliav Buchnik, Edith Cohen
Reverse Ranking by Graph Structure: Model and Scalable Algorithms. SIGMETRICS (2016)
Edith Cohen
Greedy Maximization Framework for Graph-Based Influence Functions. HotWeb (2016)
Shiri Chechik, Edith Cohen, Haim Kaplan
Average Distance Queries through Weighted Samples in Graphs and Metric Spaces: High Scalability with Tight Statistical Guarantees. CoRR (2015)
Edith Cohen
Stream Sampling for Frequency Cap Statistics. KDD (2015)
Shiri Chechik, Edith Cohen, Haim Kaplan
Average Distance Queries through Weighted Samples in Graphs and Metric Spaces: High Scalability with Tight Statistical Guarantees. APPROX-RANDOM (2015)
Eliav Buchnik, Edith Cohen
Reverse Ranking by Graph Structure: Model and Scalable Algorithms. CoRR (2015)
Edith Cohen
All-Distances Sketches, Revisited: HIP Estimators for Massive Graphs Analysis. IEEE Trans. Knowl. Data Eng. 27 (9) (2015)
Edith Cohen
Multi-objective Weighted Sampling. HotWeb (2015)
Edith Cohen
Multi-Objective Weighted Sampling. CoRR (2015)
Edith Cohen
Stream Sampling for Frequency Cap Statistics. CoRR (2015)
Edith Cohen
All-distances sketches, revisited: HIP estimators for massive graphs analysis. PODS (2014)
Edith Cohen, Daniel Delling, Thomas Pajor, Renato F. Werneck
Sketch-based Influence Maximization and Computation: Scaling up with Guarantees. CIKM (2014)
Edith Cohen, Avinatan Hassidim, Haim Kaplan, Yishay Mansour, Danny Raz, Yoav Tzur
Probe scheduling for efficient detection of silent failures. Perform. Evaluation 79 (2014)
Edith Cohen, Daniel Delling, Thomas Pajor, Renato F. Werneck
Timed Influence: Computation and Maximization. CoRR (2014)
Edith Cohen, Nick G. Duffield, Haim Kaplan, Carsten Lund, Mikkel Thorup
Algorithms and estimators for summarization of unaggregated data streams. J. Comput. Syst. Sci. 80 (7) (2014)
Edith Cohen
Variance Competitiveness for Monotone Estimation: Tightening the Bounds. CoRR (2014)
Edith Cohen, Daniel Delling, Thomas Pajor, Renato F. Werneck
Computing classic closeness centrality, at scale. COSN (2014)
Qin Lv, Pei Cao, Edith Cohen, Kai Li, Scott Shenker
Author retrospective for search and replication in unstructured peer-to-peer networks. ICS 25th Anniversary (2014)
Edith Cohen, Daniel Delling, Thomas Pajor, Renato F. Werneck
Computing Classic Closeness Centrality, at Scale. CoRR (2014)
Edith Cohen
Estimation for monotone sampling: competitiveness and customization. PODC (2014)
Edith Cohen
Distance queries from sampled data: accurate and efficient. KDD (2014)
Edith Cohen, Daniel Delling, Thomas Pajor, Renato F. Werneck
Sketch-based Influence Maximization and Computation: Scaling up with Guarantees. CoRR (2014)
Edith Cohen, Graham Cormode, Nick G. Duffield, Carsten Lund
On the Tradeoff between Stability and Fit CoRR (2013)
Edith Cohen
Scalable Neighborhood Sketching and Distance Distribution Estimation in Graph Datasets: Revisited, Unified, and Improved. CoRR (2013)
Edith Cohen, Daniel Delling, Fabian Fuchs, Andrew V. Goldberg, Moisés Goldszmidt, Renato F. Werneck
Scalable similarity estimation in social networks: closeness, node labels, and random edge lengths. COSN (2013)
Edith Cohen, Avinatan Hassidim, Haim Kaplan, Yishay Mansour, Danny Raz, Yoav Tzur
Probe Scheduling for Efficient Detection of Silent Failures CoRR (2013)
Edith Cohen, Haim Kaplan
What You Can Do with Coordinated Samples. APPROX-RANDOM (2013)
Edith Cohen, Haim Kaplan, Yishay Mansour
Scheduling Subset Tests: One-Time, Continuous, and How They Relate. APPROX-RANDOM (2013)
Edith Cohen, Amos Fiat, Haim Kaplan, Liam Roditty
A Labeling Approach to Incremental Cycle Detection. CoRR (2013)
Edith Cohen, Haim Kaplan
How to Estimate Change from Samples CoRR (2012)
Edith Cohen, Haim Kaplan
A Case for Customizing Estimators: Coordinated Samples CoRR (2012)
Edith Cohen, Michal Feldman, Amos Fiat, Haim Kaplan, Svetlana Olonetsky
Envy-Free Makespan Approximation. SIAM J. Comput. 41 (1) (2012)
Edith Cohen, Graham Cormode, Nick G. Duffield
Don't let the negatives bring you down: sampling from streams of signed updates. SIGMETRICS (2012)
Edith Cohen, Haim Kaplan
What you can do with Coordinated Samples CoRR (2012)
Edith Cohen, Graham Cormode, Nick G. Duffield
Structure-Aware Sampling: Flexible and Accurate Summarization CoRR (2011)
Edith Cohen, Nick G. Duffield, Haim Kaplan, Carsten Lund, Mikkel Thorup
Efficient Stream Sampling for Variance-Optimal Estimation of Subset Sums. SIAM J. Comput. 40 (5) (2011)
Edith Cohen, Graham Cormode, Nick G. Duffield
Structure-aware sampling on data streams. SIGMETRICS (2011)
Edith Cohen, Michal Feldman, Amos Fiat, Haim Kaplan, Svetlana Olonetsky
Truth, Envy, and Truthful Market Clearing Bundle Pricing. WINE (2011)
Edith Cohen, Haim Kaplan
Get the Most out of Your Sample: Optimal Unbiased Estimators using Partial Information CoRR (2011)
Edith Cohen, Graham Cormode, Nick G. Duffield
Structure-Aware Sampling: Flexible and Accurate Summarization. Proc. VLDB Endow. 4 (11) (2011)
Edith Cohen, Haim Kaplan
Get the most out of your sample: optimal unbiased estimators using partial information. PODS (2011)
Edith Cohen, Michal Feldman, Amos Fiat, Haim Kaplan, Svetlana Olonetsky
On the Interplay between Incentive Compatibility and Envy Freeness CoRR (2010)
Edith Cohen, Haim Kaplan, Tova Milo
Labeling Dynamic XML Trees. SIAM J. Comput. 39 (5) (2010)
Edith Cohen, Michal Feldman, Amos Fiat, Haim Kaplan, Svetlana Olonetsky
Envy-free makespan approximation: extended abstract. EC (2010)
Edith Cohen, Michal Feldman, Amos Fiat, Haim Kaplan, Svetlana Olonetsky
Truth and Envy in Capacitated Allocation Games CoRR (2010)
Edith Cohen, Nick G. Duffield, Haim Kaplan, Carsten Lund, Mikkel Thorup
Stream sampling for variance-optimal estimation of subset sums. SODA (2009)

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Publication Activity (10 Years)

Top Topics

Top Venues

Edith Cohen