Other Reports

[1] G. Cormode. Technical perspective on `R2T: Instance-optimal Truncation for Differentially Private Query Evaluation with Foreign Keys'. In SIGMOD Record, volume 52(1), page 114. ACM, Mar. 2023.
[2] G. Cormode. Gems of pods: Applications of sketching and pathways to impact. In ACM Principles of Database Systems (PODS). ACM, 2023.
[3] G. Cormode. Technical perspective: A framework for adversarially robust streaming algorithms. In SIGMOD Record, volume 50(1). ACM, Mar. 2021. Introduction to research highlights paper by Ben-Eliezer, Jayaram, Woodruff, and Yogev.
[4] G. Cormode. The true cost of popularity. In Communications of the ACM (CACM). ACM, July 2019. Introduction to research highlights paper by Larsen, Nelson, Nguyen and Thorup.
[5] G. Cormode. Technical perspective: εktelo: A framework for defining differentially-private computations. In SIGMOD Record, volume 48(1). ACM, Mar. 2019. Introduction to research highlights paper by Zhang, McKenna, Kotsogiannis, Bissias, Hay, Machanavajjhala and Gerome Miklau.
[6] G. Cormode, H. Jowhari, M. Monemizadeh, and S. Muthukrishnan. The sparse awakens: Streaming algorithms for matching size estimation in sparse graphs. Technical report, ArXiV, 2016.
[7] G. Cormode and M. Garofalakis. Join sizes, frequency moments, and applications. In M. Garofalakis, J. Gehrke, and R. Rastogi, editors, Data Stream Management: Processing High-Speed Data Streams. Springer, 2016.
[8] G. Cormode and P. Indyk. Stable distributions in streaming computations. In M. Garofalakis, J. Gehrke, and R. Rastogi, editors, Data Stream Management: Processing High-Speed Data Streams. Springer, 2016.
[9] G. Cormode. Encyclopedia entry on 'count-min sketch'. In M.-Y. Kao, editor, Encyclopedia of Algorithms. Springer, 2015.
[10] G. Cormode. Encyclopedia entry on 'ams sketch'. In M.-Y. Kao, editor, Encyclopedia of Algorithms. Springer, 2015.
[11] G. Cormode. Encyclopedia entry on 'misra-gries summary'. In M.-Y. Kao, editor, Encyclopedia of Algorithms. Springer, 2015.
[12] G. Cormode. Continuous distributed monitoring: A short survey. In Paper accompanying invited talk at Algorithms and Models for Distributed Event Processing (AlMoDEP). ACM, Sept. 2011.
[13] G. Cormode. Sketch techniques for massive data. In G. Cormode, M. Garofalakis, P. Haas, and C. Jermaine, editors, Synposes for Massive Data: Samples, Histograms, Wavelets and Sketches, Foundations and Trends in Databases. NOW publishers, 2011.
[14] S. Bhagat, G. Cormode, and S. Muthukrishnan. Node classification in social networks. In C. C. Aggarwal, editor, Social Network Data Analytics. Springer, 2011.
[15] G. Cormode, J. Thaler, and K. Yi. Verifying computations with streaming interactive proofs. Technical Report TR10-159, Electronic Colloquium on Computational Complexity (ECCC), 2010.
[16] G. Cormode. Individual privacy vs population privacy: Learning to attack anonymization. Technical Report arXiv:1011.2511, arXiv, 2010.
[17] G. Cormode. Encyclopedia entry on 'Count-Min Sketch'. In L. Liu and M. T. Ozsu, editors, Encyclopedia of Database Systems, pages 511-516. Springer, 2009.
[18] G. Cormode and M. Garofalakis. Histograms and wavelets on probabilistic data. Technical Report arXiv:0806.1071, arXiv, 2008.
[19] G. Cormode, F. Korn, and S. Tirthapura. Time decaying aggregates in out-of-order streams. Technical Report 2007-10, Center for Discrete Mathematics and Computer Science (DIMACS), 2007.
[20] G. Cormode. Computational fundamentals of analyzing and mining data streams. In Workshop on Data Stream Analysis. 2007.
[21] G. Cormode and S. Muthukrishnan. Combinatorial algorithms for compressed sensing. In Proceedings of Conference on Information Sciences and Systems (CISS). IEEE, 2006. Invited submission.
[22] G. Cormode. Some key concepts in data mining - clustering. In Discrete Methods in Epidemiology, volume 70 of DIMACS, pages 2-9. AMS, 2006.
[23] G. Cormode and M. Garofalakis. Efficient strategies for continuous distributed tracking tasks. In IEEE Data Engineering Bulletin, pages 33-39. IEEE, March 2005.
[24] G. Cormode and S. Muthukrishnan. Combinatorial algorithms for compressed sensing. Technical Report 2005-40, Center for Discrete Mathematics and Computer Science (DIMACS), 2005.
[25] G. Cormode and S. Muthukrishnan. Towards an algorithmic theory of compressed sensing. Technical Report 2005-25, Center for Discrete Mathematics and Computer Science (DIMACS), 2005.
[26] G. Cormode, S. Muthukrishnan, and I. Rozenbaum. Summarizing and mining inverse distributions on data streams via dynamic inverse sampling. Technical Report 2005-11, Center for Discrete Mathematics and Computer Science (DIMACS), 2005.
[27] G. Cormode. The hardness of the lemmings game, or, “Oh no, more NP-Completeness proofs”. Technical Report 2004-11, Center for Discrete Mathematics and Computer Science (DIMACS), 2004.
[28] J. Abello and G. Cormode. Report on DIMACS working group meeting: Data mining and epidemiology, March 18-19, 2004. Technical Report 2004-37, Center for Discrete Mathematics and Computer Science (DIMACS), 2004.
[29] G. Cormode, A. Czumaj, and S. Muthukrishnan. How to increase the acceptance ratios of top conferences. Technical Report 2004-12, Center for Discrete Mathematics and Computer Science (DIMACS), 2004.
[30] G. Cormode and S. Muthukrishnan. Radial histograms for spatial streams. Technical Report 2003-11, Center for Discrete Mathematics and Computer Science (DIMACS), 2003.
[31] G. Cormode and S. Muthukrishnan. Estimating dominance norms of multiple data streams. Technical Report 2002-35, Center for Discrete Mathematics and Computer Science (DIMACS), 2002.
[32] G. Cormode and S. Muthukrishnan. The string edit distance matching problem with moves. Technical Report 2001-26, Center for Discrete Mathematics and Computer Science (DIMACS), 2001.
[33] G. Cormode. Topic dependencies for electronic books. (unpublished manuscript), 1999.
[34] G. Cormode. Springs and sound layouts. (unpublished manuscript), 1998.

This file was generated by bibtex2html 1.92.