Graham Cormode

I am a researcher at AT&T Labs--Research. My interests are in network management, mining massive datasets and data streams, and in theoretical matching problems. From 2004--06, I worked at Bell Laboratories in the Internet Management Research Department.

Between 2002 and 2004, I was a postdoctoral fellow at DIMACS, the Center for Discrete Mathematics and Computer Science. I completed my PhD at the Department of Computer Science at the University of Warwick, UK in 2002. I spent a year of my PhD studying in Cleveland, Ohio at Case Western Reserve University with the Electrical Engineering and Computer Science Department , and Summer 2000 as an intern at AT&T Shannon research labs.

For more information, see a (reasonably up to date) CV.

Conference Publications

[1] G. Cormode, C. M. Procopiuc, E. Shen, D. Srivastava, and T. Yu. Empirical privacy and empirical utility of anonymized data. In Privacy-Preserving Data Publication and Analysis (PrivDB), 2013.
[2] G. Cormode, K. Mirylenka, T. Palpanas, and D. Srivastava. Finding interesting correlations with conditional heavy hitters. In International Conference on Data Engineering (ICDE), 2013.
[3] G. Cormode, C. M. Procopiuc, D. Srivastava, and G. Yaroslavtsev. Accurate and efficient private release of datacubes and contingency tables. In International Conference on Data Engineering (ICDE), 2013.
[4] G. Cormode and D. Firmani. On unifying the space of l0-sampling algorithms. In SIAM Meeting on Algorithm Engineering and Experiments, 2013.
[5] G. Cormode, J. Thaler, and K. Yi. Verifying computations with streaming interactive proofs. In International Conference on Very Large Data Bases (VLDB), Sept. 2012.
[6] A. Goyal, H. Daumé III, and G. Cormode. Sketch algorithms for estimating point queries in NLP. In EMNLP-CoNLL, pages 1093-1103, 2012.
[7] P. Agarwal, G. Cormode, Z. Huang, J. Phillips, Z. Wei, and K. Yi. Mergeable summaries. In ACM Principles of Database Systems (PODS), 2012.
[8] E. Cohen, G. Cormode, and N. Duffield. Don't let the negatives bring you down: Sampling from streams of signed updates. In ACM Conference on Measurement and Modeling of Computer Systems (SIGMETRICS), 2012.
[9] G. Cormode and K. Yi. Tracking distributed aggregates over time-based sliding windows. In Scientific and Statistical Database Management (SSDBM), 2012.
[10] G. Cormode, S. Muthukrishnan, and J. Yan. Scienceography: the study of how science is written. In Proceedings of the International Conference on Fun with Algorithms (FUN), 2012.
[11] G. Cormode, M. Procopiuc, D. Srivastava, and T. Tran. Differentially private publication of sparse data. In International Conference on Database Theory (ICDT), 2012.
[12] G. Cormode, M. Procopiuc, E. Shen, D. Srivastava, and T. Yu. Differentially private spatial decompositions. In International Conference on Data Engineering (ICDE), 2012.
[13] M. Lu, S. Bangalore, G. Cormode, M. Hadjieleftheriou, and D. Srivastava. A dataset search engine for the research document corpus. In International Conference on Data Engineering (ICDE), 2012.
[14] G. Cormode, E. Shen, D. Srivastava, and T. Yu. Aggregate query answering on possibilistic data with cardinality constraints. In International Conference on Data Engineering (ICDE), 2012.
[15] G. Cormode, M. Mitzenmacher, and J. Thaler. Practical verified computation with streaming interactive proofs. In Innovations in Theoretical Computer Science (ITCS), 2012.
[16] P. Agarwal, G. Cormode, Z. Huang, J. Phillips, Z. Wei, and K. Yi. Mergeable coresets. In Third Workshop on Massive Data Algorithmics (MASSIVE), 2011.
[17] G. Cormode. Personal privacy vs population privacy: Learning to attack anonymization. In ACM SIGKDD Conference, 2011.
[18] E. Cohen, G. Cormode, and N. Duffield. Structure-aware sampling: Flexible and accurate summarization. In International Conference on Very Large Data Bases (VLDB), 2011.
[19] G. Cormode and K. Yi. Tracking distributed aggregates over time-based sliding windows (brief announcement). In ACM Principles of Distributed Computing (PODC), 2011.
[20] E. Cohen, G. Cormode, and N. Duffield. Structure-aware sampling on data streams. In ACM Conference on Measurement and Modeling of Computer Systems (SIGMETRICS), 2011.
[21] G. Cormode, H. Karloff, and T. Wirth. Set cover algorithms for very large datasets. In ACM Conference on Information and Knowledge Management (CIKM), 2010.
[22] G. Cormode, S. Muthukrishnan, K. Yi, and Q. Zhang. Optimal sampling from distributed streams. In ACM Principles of Database Systems (PODS), 2010.
[23] S. Bhagat, G. Cormode, B. Krishnamurthy, and D. Srivastava. Privacy in dynamic social networks. In World Wide Web Conference (WWW), 2010.
[24] G. Cormode, M. Mitzenmacher, and J. Thaler. Streaming graph computations with a helpful advisor. In European Symposium on Algorithms, 2010.
[25] A. Chakrabarti, G. Cormode, R. Kondapally, and A. McGregor. Information cost tradeoffs for augmented index and streaming language recognition. In IEEE Foundations of Computer Science (FOCS), 2010.
[26] G. Cormode, N. Li, T. Li, and D. Srivastava. Minimizing minimality and maximizing utility: Analyzing method-based attacks on anonymized data. In International Conference on Very Large Data Bases (VLDB), 2010.
[27] S. Bhagat, G. Cormode, B. Krishnamurthy, and D. Srivastava. Prediction promotes privacy in dynamic social networks. In Workshop on Online Social Networks (WOSN), 2010.
[28] S. Bhagat, G. Cormode, B. Krishnamurthy, and D. Srivastava. Class-based graph anonymization for social network data. In International Conference on Very Large Data Bases (VLDB), 2009.
[29] G. Cormode, A. Deligiannakis, M. Garofalakis, and A. McGregor. Probabilistic histograms for probabilistic data. In International Conference on Very Large Data Bases (VLDB), 2009.
[30] A. Chakrabarti, G. Cormode, and A. McGregor. Annotations in data streams. In International Colloquium on Automata, Languages and Programming (ICALP), 2009.
[31] G. Cormode, L. Golab, F. Korn, A. McGregor, D. Srivastava, and X. Zhang. Estimating the confidence of conditional functional dependencies. In ACM SIGMOD International Conference on Management of Data (SIGMOD), 2009.
[32] R. Berinde, G. Cormode, P. Indyk, and M. Strauss. Space-optimal heavy hitters with strong error bounds. In ACM Principles of Database Systems (PODS), 2009.
[33] G. Cormode, S. Tirthapura, and B. Xu. Time-decayed correlated aggregates over data streams. In SIAM Conference on Data Mining (SDM), 2009.
[34] G. Cormode and M. Garofalakis. Histograms and wavelets on probabilistic data. In International Conference on Data Engineering (ICDE), 2009. Best paper award.
[35] G. Cormode, F. Li, and K. Yi. Semantics of ranking queries for probabilistic data and expected ranks. In International Conference on Data Engineering (ICDE), 2009.
[36] G. Cormode, V. Shkapenyuk, D. Srivastava, and B. Xu. Forward decay: A practical time decay model for streaming systems. In International Conference on Data Engineering (ICDE), 2009.
[37] G. Cormode and M. Hadjieleftheriou. Finding frequent items in data streams. In International Conference on Very Large Data Bases (VLDB), 2008. Best paper award.
[38] G. Cormode, D. Srivastava, T. Yu, and Q. Zhang. Anonymizing bipartite graph data using safe groupings. In International Conference on Very Large Data Bases (VLDB), 2008.
[39] G. Cormode, F. Korn, and S. Tirthapura. Time-decaying aggregates in out-of-order streams. In ACM Principles of Database Systems (PODS), 2008.
[40] G. Cormode and A. McGregor. Approximation algorithms for clustering uncertain data. In ACM Principles of Database Systems (PODS), 2008.
[41] G. Cormode, F. Korn, S. Muthukrishnan, and D. Srivastava. Summarizing two-dimensional data with skyline-based statistical descriptors. In Scientific and Statistical Database Management (SSDBM), 2008.
[42] A. Chakrabarti, G. Cormode, and A. McGregor. Robust lower bounds for communication and stream computation. In ACM Symposium on Theory of Computing (STOC), 2008.
[43] G. Cormode, F. Korn, S. Muthukrishnan, and Y. Wu. On signatures for communication graphs. In International Conference on Data Engineering (ICDE), 2008.
[44] G. Cormode, F. Korn, and S. Tirthapura. Exponentially decayed aggregates on data streams. In International Conference on Data Engineering (ICDE), 2008.
[45] G. Cormode, S. Muthukrishnan, and K. Yi. Algorithms for distributed, functional monitoring. In ACM-SIAM Symposium on Discrete Algorithms (SODA), 2008.
[46] S. Bhagat, G. Cormode, and I. Rozenbaum. Applying link-based classification to label blogs. In Joint WEBKDD and SNA-KDD Workshop, 2007.
[47] S. Ganguly and G. Cormode. On estimating frequency moments of data streams. In Proceedings of RANDOM, 2007.
[48] G. Cormode, S. Tirthapura, and B. Xu. Time-decaying sketches for sensor data aggregation. In ACM Principles of Distributed Computing (PODC), 2007.
[49] G. Cormode and M. Garofalakis. Sketching probabilistic data streams. In ACM SIGMOD International Conference on Management of Data (SIGMOD), 2007.
[50] S. Bhagat, G. Cormode, S. Muthukrishnan, I. Rozenbaum, and H. Xue. No blog is an island analyzing connections across information networks. In International Conference on Weblogs and Social Media, 2007.
[51] G. Cormode, S. Muthukrishnan, and W. Zhuang. Conquering the divide: Continuous clustering of distributed data streams. In International Conference on Data Engineering (ICDE), 2007.
[52] A. Chakrabarti, G. Cormode, and A. McGregor. A near-optimal algorithm for computing the entropy of a stream. In ACM-SIAM Symposium on Discrete Algorithms (SODA), 2007.
[53] G. Cormode and S. Muthukrishnan. Combinatorial algorithms for compressed sensing. In SIROCCO, 2006.
[54] G. Cormode, F. Korn, S. Muthukrishnan, and D. Srivastava. Space- and time-efficient deterministic algorithms for biased quantiles over data streams. In ACM Principles of Database Systems (PODS), 2006.
[55] G. Cormode, R. Keralapura, and J. Ramimirtham. Communication-efficient distributed monitoring of thresholded counts. In ACM SIGMOD International Conference on Management of Data (SIGMOD), 2006.
[56] G. Cormode, M. Garofalakis, and D. Sacharidis. Fast approximate wavelet tracking on streams. In Extending Database Technology, pages 4-22, 2006.
[57] G. Cormode, S. Muthukrishnan, and W. Zhuang. What's different: Distributed, continuous monitoring of duplicate-resilient aggregates on data streams. In International Conference on Data Engineering (ICDE), pages 20-31, 2006.
[58] G. Cormode, S. Muthukrishnan, and I. Rozenbaum. Summarizing and mining inverse distributions on data streams via dynamic inverse sampling. In International Conference on Very Large Data Bases (VLDB), pages 25-36, 2005.
[59] G. Cormode and M. Garofalakis. Sketching streams through the net: Distributed approximate query tracking. In International Conference on Very Large Data Bases (VLDB), pages 13-24, 2005.
[60] G. Cormode and S. Muthukrishnan. Space efficient mining of multigraph streams. In ACM Principles of Database Systems (PODS), pages 271-282, 2005.
[61] G. Cormode, M. Garofalakis, S. Muthukrishnan, and R. Rastogi. Holistic aggregates in a networked world: Distributed tracking of approximate quantiles. In ACM SIGMOD International Conference on Management of Data (SIGMOD), pages 25-36, 2005.
[62] G. Cormode and S. Muthukrishnan. Summarizing and mining skewed data streams. In SIAM Conference on Data Mining (SDM), 2005.
[63] G. Cormode, F. Korn, S. Muthukrishnan, and D. Srivastava. Effective computation of biased quantiles over data streams. In International Conference on Data Engineering (ICDE), pages 20-31, 2005.
[64] G. Cormode and S. Muthukrishnan. Substring compression problems. In ACM-SIAM Symposium on Discrete Algorithms (SODA), pages 321-330, 2005.
[65] G. Cormode, F. Korn, S. Muthukrishnan, and D. Srivastava. Diamond in the rough: Finding hierarchical heavy hitters in multi-dimensional data. In ACM SIGMOD International Conference on Management of Data (SIGMOD), pages 155-166, 2004.
[66] G. Cormode, F. Korn, S. Muthukrishnan, T. Johnson, O. Spatscheck, and D. Srivastava. Holistic UDAFs at streaming speeds. In ACM SIGMOD International Conference on Management of Data (SIGMOD), pages 35-46, 2004.
[67] G. Cormode. The hardness of the lemmings game, or Oh no, more NP-completeness proofs. In Proceedings of Third International Conference on Fun with Algorithms, pages 65-76, 2004.
[68] G. Cormode, A. Czumaj, and S. Muthukrishnan. How to increase the acceptance ratios of top conferences. In Proceedings of Third International Conference on Fun with Algorithms, pages 262-273, 2004.
[69] G. Cormode and S. Muthukrishnan. What's new: Finding significant differences in network data streams. In Proceedings of IEEE Infocom, pages 1534-1545, 2004.
[70] G. Cormode and S. Muthukrishnan. An improved data stream summary: The count-min sketch and its applications. In Proceedings of Latin American Theoretical Informatics (LATIN), pages 29-38, 2004.
[71] G. Cormode. Stable distributions for stream computations: it's as easy as 0,1,2. In Workshop on Management and Processing of Massive Data Streams at FCRC, 2003.
[72] G. Cormode and S. Muthukrishnan. What's hot and what's not: Tracking most frequent items dynamically. In ACM Principles of Database Systems (PODS), pages 296-306, 2003.
[73] G. Cormode, F. Korn, S. Muthukrishnan, and D. Srivastava. Finding hierarchical heavy hitters in data streams. In International Conference on Very Large Data Bases (VLDB), pages 464-475, 2003.
[74] G. Cormode and S. Muthukrishnan. Estimating dominance norms of multiple data streams. In European Symposium on Algorithms, volume 2838 of LNCS, 2003.
[75] G. Cormode, M. Datar, P. Indyk, and S. Muthukrishnan. Comparing data streams using Hamming norms. In International Conference on Very Large Data Bases (VLDB), pages 335-345, 2002.
[76] G. Cormode, P. Indyk, N. Koudas, and S. Muthukrishnan. Fast mining of tabular data via approximate distance computations. In International Conference on Data Engineering (ICDE), pages 605-616, 2002.
[77] G. Cormode and S. Muthukrishnan. The string edit distance matching problem with moves. In ACM-SIAM Symposium on Discrete Algorithms (SODA), pages 667-676, 2002.
[78] G. Cormode, S. Muthukrishnan, and S. C. Sahinalp. Permutation editing and matching via embeddings. In International Colloquium on Automata, Languages and Programming (ICALP), volume 2076, pages 481-492, 2001.
[79] G. Cormode, M. Paterson, S. C. Sahinalp, and U. Vishkin. Communication complexity of document exchange. In ACM-SIAM Symposium on Discrete Algorithms (SODA), pages 197-206, 2000.
[80] G. Ozsoyoglu, N. H. Balkir, G. Cormode, and Z. M. Ozsoyoglu. Electronic books in digital libraries. In Proceedings of IEEE Advances in Digital Libraries (ADL), pages 5-14, 2000.

Journal Publications

[1] G. Cormode, S. Muthukrishnan, K. Yi, and Q. Zhang. Continuous sampling from distributed streams. Journal of the ACM (JACM), 59(2), Apr. 2012.
[2] G. Cormode, M. Mitzenmacher, and J. Thaler. Streaming graph computations with a helpful advisor. Algorithmica, 2012.
[3] G. Cormode and S. Muthukrishnan. Approximating data with the count-min data structure. IEEE Software, 2012.
[4] G. Cormode, S. Muthukrishnan, and K. Yi. Algorithms for distributed functional monitoring. ACM Transactions on Algorithms, 7(2):1-21, 2011.
[5] G. Cormode, J. Jestes, F. Li, and K. Yi. Semantics of ranking queries for probabilistic data. IEEE Transactions on Knowledge and Data Engineering, 23(12):1903-1917, 2011.
[6] G. Cormode, B. Krishnamurthy, and W. Willinger. A manifesto for modeling and measurement in social media. First Monday, 15(9), Sept. 2010.
[7] G. Cormode and M. Garofalakis. Histograms and wavelets on probabilistic data. IEEE Transactions on Knowledge and Data Engineering, 22(8):1142-1157, Aug. 2010.
[8] A. Chakrabarti, G. Cormode, and A. McGregor. A near-optimal algorithm for computing the entropy of a stream. ACM Transactions on Algorithms, 6(3), 2010.
[9] R. Berinde, G. Cormode, P. Indyk, and M. Strauss. Space-optimal heavy hitters with strong error bounds. ACM Transactions on Database Systems, 35(4), 2010.
[10] G. Cormode, D. Srivastava, T. Yu, and Q. Zhang. Anonymizing bipartite graph data using safe groupings. The VLDB Journal, 19(1):115-139, 2010.
[11] G. Cormode and M. Hadjieleftheriou. Methods for finding frequent items in data streams. The VLDB Journal, 19(1):3-20, 2010.
[12] G. Cormode, S. Tirthapura, and B. Xu. Time-decaying sketches for robust aggregation of sensor data. SIAM Journal on Computing (SICOMP), 39(4):1309-1339, 2009.
[13] G. Cormode, S. Tirthapura, and B. Xu. Time-decayed correlated aggregates over data streams. Statistical Analysis and Data Mining, 2(5-6):294-310, 2009.
[14] K. Yi, F. Li, G. Cormode, M. Hadjieleftheriou, G. Kollios, and D. Srivastava. Small synopses for group-by query verification on outsourced data streams. ACM Transactions on Database Systems, 34(3), 2009.
[15] G. Cormode and M. Hadjieleftheriou. Finding the frequent items in streams of data. Communications of the ACM (CACM), 52(10):97-105, 2009.
[16] G. Cormode. How not to review a paper: The tools and techniques of the adversarial reviewer. SIGMOD Record, 37(4):100-104, Dec. 2008.
[17] G. Cormode and B. Krishnamurthy. Key differences between web 1.0 and web 2.0. First Monday, 13(6), June 2008.
[18] G. Cormode and M. Garofalakis. Approximate continuous querying over distributed streams. ACM Transactions on Database Systems, 33(2), June 2008.
[19] G. Cormode, F. Korn, S. Muthukrishnan, and D. Srivastava. Finding hierarchical heavy hitters in streaming data. ACM Transactions on Knowledge Discovery from Data (TKDD), 1(4), Jan. 2008.
[20] G. Cormode and S. Muthukrishnan. The string edit distance matching problem with moves. ACM Transactions on Algorithms, 3(1), 2007.
[21] G. Cormode and S. Muthukrishnan. What's new: Finding significant differences in network data streams. Transactions on Networking, 13(6):1219-1232, December 2005.
[22] G. Cormode and S. Muthukrishnan. An improved data stream summary: The count-min sketch and its applications. Journal of Algorithms, 55(1):58-75, April 2005.
[23] G. Cormode and S. Muthukrishnan. What's hot and what's not: Tracking most frequent items dynamically. ACM Transactions on Database Systems, 30(1):249-278, March 2005.
[24] G. Cormode. Representations of the research student in popular culture. Annals of Improbable Research, 10(1):26-27, 2004.
[25] G. Ozsoyoglu, N. H. Balkir, G. Cormode, and Z. M. Ozsoyoglu. Electronic books in digital libraries. IEEE Transactions on Knowledge and Data Engineering, 16(3):317-331, 2004.
[26] G. Cormode, M. Datar, P. Indyk, and S. Muthukrishnan. Comparing data streams using Hamming norms. IEEE Transactions on Knowledge and Data Engineering, 15(3):529-541, 2003.

Books and Theses

[1] G. Cormode, M. Garofalakis, P. Haas, and C. Jermaine. Synposes for Massive Data: Samples, Histograms, Wavelets and Sketches. now publishers, 2012.
[2] G. Cormode and M. Thottan, editors. Algorithms for Next Generation Networks. Springer, 2010.
[3] J. Abello and G. Cormode, editors. Discrete Methods in Epidemiology, volume 70 of DIMACS. AMS, 2006.
[4] G. Cormode. Sequence Distance Embeddings. PhD thesis, University of Warwick, 2003.

Book Chapters, Technical Reports and Unrefereed Papers

[1] 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.
[2] 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.
[3] S. Bhagat, G. Cormode, and S. Muthukrishnan. Node classification in social networks. In C. C. Aggarwal, editor, Social Network Data Analytics. Springer, 2011.
[4] G. Cormode, J. Thaler, and K. Yi. Verifying computations with streaming interactive proofs. Technical Report TR10-159, Electronic Colloquium on Computational Complexity (ECCC), 2010.
[5] G. Cormode. Individual privacy vs population privacy: Learning to attack anonymization. Technical Report arXiv:1011.2511, arXiv, 2010.
[6] 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.
[7] G. Cormode and M. Garofalakis. Histograms and wavelets on probabilistic data. Technical Report arXiv:0806.1071, arXiv, 2008.
[8] 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.
[9] G. Cormode. Computational fundamentals of analyzing and mining data streams. In Workshop on Data Stream Analysis. 2007.
[10] G. Cormode and S. Muthukrishnan. Combinatorial algorithms for compressed sensing. In Proceedings of Conference on Information Sciences and Systems (CISS). 2006. Invited submission.
[11] G. Cormode. Some key concepts in data mining - clustering. In Discrete Methods in Epidemiology, volume 70 of DIMACS, pages 2-9. AMS, 2006.
[12] 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, 2006.
[13] 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, 2006. (The book containing this chapter has yet to be published).
[14] G. Cormode and M. Garofalakis. Efficient strategies for continuous distributed tracking tasks. In IEEE Data Engineering Bulletin, pages 33-39. IEEE, March 2005.
[15] G. Cormode and S. Muthukrishnan. Combinatorial algorithms for compressed sensing. Technical Report 2005-40, Center for Discrete Mathematics and Computer Science (DIMACS), 2005.
[16] 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.
[17] 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.
[18] 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.
[19] 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.
[20] 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.
[21] G. Cormode and S. Muthukrishnan. Radial histograms for spatial streams. Technical Report 2003-11, Center for Discrete Mathematics and Computer Science (DIMACS), 2003.
[22] 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.
[23] 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.
[24] G. Cormode. Topic dependencies for electronic books. (unpublished manuscript), 1999.
[25] G. Cormode. Springs and sound layouts. (unpublished manuscript), 1998.

Invited Talks and Tutorials

[1] Data-driven concerns in private data release, Sept. 2012. Talk at Stevens Institute of Technology; AT&T Labs; UMass Amherst; Rutgers University-Newark; Bell Labs.
[2] Small summaries for big data, 2012. Talk at Duke ARO workshop on Big Data at Large; MSR Cambridge.
[3] Continuous distributed monitoring: A short survey, Sept. 2011. Invited talk at Algorithms and Models for Distributed Event Processing (AlMoDEP).
[4] Some sketchy results, May 2011. Talk at DIMACS Workshop on Algorithms in the Field (8F).
[5] Mergeable summaries, Apr. 2011. Talk at Harvard University; DIMACS; Johns Hopkins; University of Pennsylvania; AT&T Labs; Warwick University.
[6] Data anonymization, Mar. 2011. Guest lecture in 'Dealing with Massive Data' at Columbia University.
[7] Distributed summaries, 2011. Talk at DIMACS workshop on Parallelism: a 2020 vision.
[8] G. Cormode and D. Srivastava. Anonymized data: Generation, models, usage, Mar. 2010. Tutorial at ICDE 2010.
[9] Sipping from the firehose: Streaming interactive proofs for verifying computations, February 2010. Talk at Bristol Algorithms Days 2010; Maryland.
[10] Progress in data anonymization: from k-anonymity to the minimality attack, February 2010. Talk in Bristol.
[11] Anonymization and uncertainty in social network data, Oct. 2009. Talk at DBIR Day 2009 at NYU Poly.
[12] G. Cormode and D. Srivastava. Anonymized data: Generation, models, usage, July 2009. Tutorial at SIGMOD 2009.
[13] Processing graph streams: Upper and lower bounds, June 2009. Talk at Workshop on Algorithms and Models for Complex Networks, Bristol UK.
[14] Finding frequent items in data streams, March 2009. Talk at DIMACS Working group on Streaming, Coding and Compressive Sensing; AT&T Labs; UMass Amherst; Dartmouth College.
[15] On 'selection and sorting with limited storage', Sept. 2008. Talk at Mike66 Workshop celebrating Mike Paterson.
[16] Algorithms for distributed functional monitoring, Aug. 2008. Talk at Dagstuhl Seminar on Sublinear Algorithms.
[17] Data stream algorithms, July 2008. Tutorial at Bristol Summer School on Probabilistic Techniques in Computer Science.
[18] G. Cormode and M. Garofalakis. Streaming in a connected world: Querying and tracking distributed data streams, March 2008. Tutorial at VLDB 2006, SIGMOD 2007, EDBT 2008.
[19] Analyzing web 2.0, blogs and social networks, Dec. 2007. Talk at AT&T Labs.
[20] Computational fundamentals of analyzing and mining data streams, March 2007. Tutorial at Workshop on Data Stream Analysis, Caserta, Italy.
[21] Computing the entropy of a stream, December 2006. AT&T Labs; Bell Labs; DyDAn Center.
[22] A compact survey of compressed sensing, December 2006. Workshop on Algorithms for Data Streams, IIT Kanpur, India.
[23] Biased quantiles, June 2006. Bertinoro.
[24] Cluster and data stream analysis, March 2006. Tutorial at DIMACS Workshop on Data Mining and Epidemiology.
[25] Tracking inverse distributions of massive data streams, July 2005. Network Sampling Workshop in Paris, Bell Labs Research Seminar.
[26] Towards an algorithmic theory of compressed sensing, July 2005. Schloss Dagstuhl.
[27] Summarizing and mining skewed data streams, May 2005. NJIT.
[28] Algorithms for processing massive data at network line speed, March 2004. Talk at U. Iowa; U. Minnesota; Dartmouth; Google; AT&T; CWRU; Poly.
[29] How hard are computer games?, February 2004. Talk at DIMACS.
[30] What's hot, what's not, what's new and what's next, October 2003. Bell Labs; DIMACS Mixer at AT&T Labs.
[31] Zeroing in on the l0 metric, August 2003. DIMACS Workshop on Discrete Metric Spaces and their Algorithmic Applications at Princeton.
[32] Tracking frequent items dynamically, 2003. Institute of Advanced Studies; DIMACS; Stonybroo; U. Pennsylvania.
[33] Algorithmic embeddings for comparing large text streams, June 2002. CCR/DIMACS Workshop/Tutorial on Mining Massive Data Sets and Streams: Mathematical Methods and Algorithms for Homeland Defense.
[34] Embeddings of metrics on strings and permuations, March 2002. Workshop on Discrete Metric Spaces and their Algorithmic Applications in Haifa, Israel; BCTCS.
[35] Short string signatures, September 2000. DIMACS Workshop on Sublinear Algorithms in Princeton, NJ.
[36] Sketches: Past, present and future. Invited Panel on Sketching and Streaming at SAMSI Workshop, 2012.

See also the listings from the dblp and their co-authors list. Google scholar page. Microsoft Academic Search page.

Programme Committees and Workshops

Editorships, Current Program Committees and Workshops: Consider submitting your papers and giving me something to read!

Previous Program Committees and Workshops:

Teaching

Summer 2012: Distributed Streaming Algorithms Course at MADALGO Summer School -- follow link for slides

Spring 2011: Map Reduce Algorithms Seminar Class at Rutgers on Map Reduce and related topics.

Summer 2008: Streaming algorithms at Bristol Summer school on Probabilistic Techniques in Computer Science A short course on streaming algorithms - see above for slides, write-up, and video.

Spring 2006: Blog Data Analysis A seminar class on blog (weblog) data.

Summer 2003, Summer 2004, Summer 2006: Mentor in the DIMACS REU Program (2003) (2004)

Spring 2003: Processing Massive Data Sets. In particular, I gave 4 x 2 hour lectures on recent research on data streams, including maintaining frequent itemsets, computing distinct items and clustering on the stream. Slides available from the class page.

Winter 2000 - Winter 2001: I held seminars and revision sessions for Discrete Mathematics.

Spring 2000: At Case Western, I was a TA for ECES 454.



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