Rachel Cummings

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	Tutte	Dal 2019
Citazioni	8184	7733
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i10-index	35	34

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Katrina LigettHebrew UniversityEmail verificata su mail.huji.ac.il
Wanrong ZhangHarvard UniversityEmail verificata su fas.harvard.edu
Aaron RothProfessor of Computer Science, University of PennsylvaniaEmail verificata su cis.upenn.edu
Zhiwei Steven WuCarnegie Mellon UniversityEmail verificata su andrew.cmu.edu
Elissa M. RedmilesClare Luce Boothe Assistant Professor, Georgetown UniversityEmail verificata su georgetown.edu
Gabriel KaptchukAssistant Professor, University of MarylandEmail verificata su umd.edu
Wei Chen （陈卫）Microsoft ResearchEmail verificata su microsoft.com
Wei WeiResearch Scientist at GoogleEmail verificata su cs.cmu.edu
Zhenming LiuCollege of William and MaryEmail verificata su cs.wm.edu
Yifei YuanupennEmail verificata su cis.upenn.edu
Yajun WangMicrosoft CorporationEmail verificata su microsoft.com
David Rincón RiveraDept. of Network Engineering, Universitat Politècnica de Catalunya (UPC - BarcelonaTech)Email verificata su upc.edu
Jamie MorgensternUniversity of WashingtonEmail verificata su cs.washington.edu
Dhamma KimparaPhD Student, University of Colorado BoulderEmail verificata su colorado.edu
Sara KrehbielAssistant Professor of Mathematics and Computer Science, Santa Clara UniversityEmail verificata su scu.edu
Uthaipon TantipongpipatTwitterEmail verificata su twitter.com
T. Tony KeChinese University of Hong KongEmail verificata su cuhk.edu.hk
Xiaorui SunUniversity of Illinois at ChicagoEmail verificata su uic.edu
Chris WaitesStanford UniversityEmail verificata su stanford.edu
David DotyAssociate Professor of Computer Science, University of California, DavisEmail verificata su ucdavis.edu

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Rachel Cummings

Columbia University

Email verificata su columbia.edu - Home page

Data privacy Machine learning Algorithmic economics Privacy Policy


Titolo Ordina per citazioni Ordina per anno Ordina per titolo	Citata da Citata da	Anno
Advances and open problems in federated learning P Kairouz, HB McMahan, B Avent, A Bellet, M Bennis, AN Bhagoji, ...	6135	2021
Influence Maximization in Social Networks When Negative Opinions May Emerge and Propagate. W Chen, A Collins, R Cummings, T Ke, Z Liu, D Rincon, X Sun, Y Wang, ... SIAM International Conference on Data Mining (SDM), 379-390, 2011	463	2011
Mariana Raykova, Dawn Song, Weikang Song, Sebastian U P Kairouz, HB McMahan, B Avent, A Bellet, M Bennis, AN Bhagoji, ... Stich, Ziteng Sun, Ananda Theertha Suresh, Florian Tramèr, Praneeth …, 2021	192	2021
On the compatibility of privacy and fairness R Cummings, V Gupta, D Kimpara, J Morgenstern Adjunct publication of the 27th conference on user modeling, adaptation and …, 2019	177	2019
" I need a better description": An Investigation Into User Expectations For Differential Privacy R Cummings, G Kaptchuk, EM Redmiles Proceedings of the 2021 ACM SIGSAC Conference on Computer and Communications …, 2021	93	2021
Truthful linear regression R Cummings, S Ioannidis, K Ligett Conference on Learning Theory (COLT), 448-483, 2015	75	2015
Adaptive learning with robust generalization guarantees R Cummings, K Ligett, K Nissim, A Roth, ZS Wu Conference on Learning Theory (COLT), 772-814, 2016	68	2016
Advances and open problems in federated learning. arXiv 2019 P Kairouz, HB McMahan, B Avent, A Bellet, M Bennis, AN Bhagoji, ... arXiv preprint arXiv:1912.04977, 2019	66	2019
Accuracy for sale: Aggregating data with a variance constraint R Cummings, K Ligett, A Roth, ZS Wu, J Ziani Conference on Innovations in Theoretical Computer Science (ITCS), 317-324, 2015	59	2015
Speed faults in computation by chemical reaction networks HL Chen, R Cummings, D Doty, D Soloveichik International Symposium on Distributed Computing (DISC), 16-30, 2014	56	2014
Privacy and truthful equilibrium selection for aggregative games R Cummings, M Kearns, A Roth, ZS Wu Conference Web and Internet Economics (WINE), 286-299, 2015	52	2015
Differential privacy for growing databases R Cummings, S Krehbiel, KA Lai, U Tantipongpipat Advances in Neural Information Processing Systems 31, 2018	51	2018
Differentially private synthetic mixed-type data generation for unsupervised learning UT Tantipongpipat, C Waites, D Boob, AA Siva, R Cummings Intelligent Decision Technologies 15 (4), 779-807, 2021	49	2021
The role of differential privacy in gdpr compliance R Cummings, D Desai FAT’18: Proceedings of the Conference on Fairness, Accountability, and …, 2018	47	2018
Probability 1 computation with chemical reaction networks R Cummings, D Doty, D Soloveichik International Conference on DNA Computing and Molecular Programming (DNA), 37-52, 2014	46	2014
Differentially private change-point detection R Cummings, S Krehbiel, Y Mei, R Tuo, W Zhang Advances in neural information processing systems 31, 2018	44	2018
Attribute privacy: Framework and mechanisms W Zhang, O Ohrimenko, R Cummings Proceedings of the 2022 ACM Conference on Fairness, Accountability, and …, 2022	40	2022
Online learning and profit maximization from revealed preferences K Amin, R Cummings, L Dworkin, M Kearns, A Roth Conference on Artificial Intelligence (AAAI), 770-776, 2015	35	2015
Challenges towards the next frontier in privacy R Cummings, D Desfontaines, D Evans, R Geambasu, M Jagielski, ... arXiv preprint arXiv:2304.06929 1, 2023	34	2023
Individual sensitivity preprocessing for data privacy R Cummings, D Durfee Proceedings of the Fourteenth Annual ACM-SIAM Symposium on Discrete …, 2020	33	2020

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