Rundong Li, Wolfgang Gatterbauer, Mirek Riedewald. Near-optimal distributed band-joins through recursive partitioning. To appear in Proc. ACM SIGMOD Int. Conf. on Managament of Data, 2020 [preprint]
Aristotelis Leventidis, Jiahui Zhang, Cody Dunne, Wolfgang Gatterbauer, HV Jagadish, Mirek Riedwald. QueryVis: Logic-based diagrams help users understand complicated SQL queries faster. To appear in Proc. ACM SIGMOD Int. Conf. on Managament of Data, 2020 [preprint]
Nikolaos Tziavelis, Wolfgang Gatterbauer, Mirek Riedewald. Optimal join algorithms meet top-k. To appear in Proc. ACM SIGMOD Int. Conf. on Managament of Data, 2020 (tutorial) [preprint]
R. Li, N. Mi, M. Riedewald, Y. Sun, Y. Yao. Abstract Cost Models for Distributed Data-Intensive Computations. Distributed and Parallel Databases, 37(3): 411-439, Springer, 2019 [preprint]
Y. Ibrahim, M. Riedewald, G. Weikum, D. Zeinalipour-Yatzi. Bridging Quantities in Tables and Text. In Proc. IEEE Int. Conf. on Data Engineering (ICDE), pages 1010-1021, 2019 (selected among Best of Conference) [preprint]
R. Li, M. Riedewald, X. Deng. Submodularity of Distributed Join Computation. In Proc. ACM SIGMOD Int. Conf. on Managament of Data, pages 1237-1252, 2018 [preprint]
X. Yang, D. Ajwani, W. Gatterbauer, P. K. Nicholson, M. Riedewald, and A. Sala. Any-k: Anytime Top-k Tree Pattern Retrieval in Labeled Graphs. In Proc. Int. Conf. on World Wide Web (WWW), pages 489-498, 2018 [extended version]
A. Abujabal, M. Yahya, M. Riedewald, and G. Weikum. Automated Template Generation for Question Answering over Knowledge Graphs. In Proc. Int. Conf. on World Wide Web (WWW), pages 1191-1200, 2017 [paper]
R. Li, N. Mi, M. Riedewald, Y. Sun, Y. Yao. A Case for Abstract Cost Models for Distributed Execution of Analytics Operators. In Proc. Int. Conf. on Big Data Analytics and Knowledge Discovery, pages 149-163, 2017 (invited to special issue of Distributed and Parallel Databases presenting the Best Papers of DaWaK) [paper]
B. Qarabaqi and M. Riedewald. Merlin: Exploratory Analysis with Imprecise Queries. IEEE Transactions on Knowledge and Data Engineering (TKDE), 28(2): 342-355, 2016 (Best papers of ICDE 2014) [preprint]
Y. Ibrahim, M. Riedewald, and G. Weikum. Making Sense of Entities and Quantities in Web Tables. In Proc. ACM Int. Conf. on Information and Knowledge Management (CIKM), pages 1703-1712, 2016 [preprint]
A. Okcan and M. Riedewald. Anti-Combining for MapReduce. In Proc. ACM SIGMOD Int. Conf. on Managament of Data, pages 839-850, 2014
B. Qarabaqi and M. Riedewald. User-Driven Refinement of Imprecise Queries. In Proc. IEEE Int. Conf. on Data Engineering (ICDE), pages 916-927, 2014 (Best Poster Award for poster presentation accompanying the full research paper, selected among Best of Conference)
P. Manolios, V. Papavasileiou, and M. Riedewald. ILP Modulo Data. In Proc. Conf. on Formal Methods in Computer-Aided Design (FMCAD), pages 171-178, 2014
G. Koutrika, L. V. S. Lakshmanan, M. Riedewald, and K. Stefanidis. Exploratory Search in Databases and the Web. EDBT/ICDT Workshops, pages 158-159, 2014
A. Okcan, M. Riedewald, B. Panda, and D. Fink. Scolopax: Exploratory Analysis of Scientific Data. In Proc. of the VLDB Endowment (PVLDB), 6(12), pages 1298-1301, 2013
B. Aghabeigi, T. Calvert, M. Seif El-Nasr, and M. Riedewald. Assistive Design and Production in Computer Games: Parametric Systems, Data Mining, Visual Analytic. In Proc. IEEE Int. Games Innovation Conference, 2012
A. Hannak, E. Anderson, L. Barrett, S. Lehman, A. Mislove, and M. Riedewald. Tweetin' in the Rain: Exploring Societal-Scale Effects of Weather on Mood. In Proc. Int. AAAI Conf. on Weblogs and Social Media (ICWSM), 2012
A. Okcan and M. Riedewald. Processing Theta-Joins using MapReduce. In Proc. ACM SIGMOD Int. Conf. on Managament of Data, pages 949-960, 2011
B. Chandramouli, J. Goldstein, R. Barga, M. Riedewald, and I. Santos. Accurate Latency Estimation in a Distributed Event Processing System. In Proc. IEEE Int. Conf. on Data Engineering (ICDE), pages 255-266, 2011
D. Fink, W. M. Hochachka, B. Zuckerberg, D. W. Winkler, B. Shaby, M. A. Munson, G. Hooker, M. Riedewald, D. Sheldon, and S. Kelling. Spatiotemporal Exploratory Models for Broad-Scale Survey Data. Ecological Applications, 20(8):2131-2147, 2010
B. Panda, M. Riedewald, and D. Fink. The Model Summary Problem and a Solution for Trees. In Proc. IEEE Int. Conf. on Data Engineering (ICDE), pages 449-460, 2010
S. Kelling, W. M. Hochachka, D. Fink, M. Riedewald, R. Caruana, G. Ballard, and G. Hooker. Data Intensive Science: A New Paradigm for Biodiversity Studies. BioScience, 57(7):613-620, 2009
D. Sorokina , R. Caruana, M. Riedewald, W. M. Hochachka, and S. Kelling. Detecting and Interpreting Variable Interactions in Observational Ornithology Data. In Proc. IEEE Int. Workshop on Domain Driven Data Mining (DDDM), 2009
M. Hong, M. Riedewald, C. Koch, J. Gehrke, and A. Demers. Rule-Based Multi-Query Optimization. In Proc. Int. Conf. on Extending Database Technology (EDBT), pages 120-131, 2009
A. Lachmann and M. Riedewald. Finding Relevant Patterns in Bursty Sequences. In Proc. of the VLDB Endowment (PVLDB), 1(1):78-89, 2008
F. Weigel, B. Panda, M. Riedewald, J. Gehrke, and M. Calimlim. Large-Scale Collaborative Analysis and Extraction of Web Data. In Proc. of the VLDB Endowment (PVLDB), 1(2): 1476-1479, 2008 (demo)
D. Sorokina, R. Caruana, M. Riedewald, and D. Fink. Detecting Statistical Interactions with Additive Groves of Trees. In Proc. International Conference on Machine Learning (ICML), pages 1000-1007, 2008
A. Dolgert, L. Gibbons, C. D. Jones, V. Kuznetsov, M. Riedewald, D. Riley, G. J. Sharp, and P. Wittich. Provenance in High-Energy Physics Workflows. In IEEE Computing in Science and Engineering (CiSE), 10(3):22-29, 2008
D. Sorokina, R. Caruana, and M. Riedewald: Additive Groves of Regression Trees. In Proc. European Conf. on Machine Learning (ECML), pages 323-334, 2007 (Best Student Paper)
B. Panda, M. Riedewald, J. Gehrke, and S. B. Pope: High-Speed Function Approximation. In Proc. IEEE Int. Conf. on Data Mining (ICDM), pages 613-618, 2007
W. M. Hochachka, R. Caruana, D. Fink, A. Munson, M. Riedewald, D. Sorokina, and S. Kelling. Data-Mining Discovery of Pattern and Process in Ecological Systems. In Journal of Wildlife Management, 71(7):2427--2437, 2007
M. Hong, A. Demers, J. Gehrke, C. Koch, M. Riedewald, and W. White. Massively Multi-Query Join Processing in Publish/Subscribe Systems. In Proc. ACM SIGMOD Int. Conf. on Managament of Data, pages 761-772, 2007
L. Brenna, A. Demers, J. Gehrke, M. Hong, J. Ossher, B. Panda, M. Riedewald, M. Thatte, and W. White. Cayuga: A High-Performance Event Processing Engine. In Proc. ACM SIGMOD Int. Conf. on Managament of Data, pages 1100-1102, 2007 (demo)
W. White, M. Riedewald, J. Gehrke and A. Demers. What is "Next" in Event Processing? In Proc. ACM Symp. on Principles of Database Systems (PODS), pages 263-272, 2007
A. Demers, J. Gehrke, B. Panda, M. Riedewald, V. Sharma, and W. White. Cayuga: A General Purpose Event Monitoring System. In Proc. Biennial Conf. on Innovative Data Systems Research (CIDR), pages 411-422, 2007
B. Panda, M. Riedewald, S. B. Pope, J. Gehrke, L. P. Chew. Indexing for Function Approximation. In Proc. Int. Conf. on Very Large Databases (VLDB), pages 523-534, 2006
R. Caruana, M. Elhawary, A. Munson, M. Riedewald, D. Sorokina, D. Fink, W. M. Hochachka, S. Kelling: Mining Citizen Science Data to Predict Prevalence of Wild Bird Species. In Proc. ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining, pages 909-915, 2006
N Gerner, F. Yan, A. Demers, J. Gehrke, M. Riedewald, and J. Shanmugasundaram. Automatic Client-Server Partitioning of Data-Driven Web Applications. In Proc. ACM SIGMOD Int. Conf. on Management of Data, pages 760-762, 2006 (demo)
A. Demers, J. Gehrke, M. Hong, M. Riedewald, and W. White. Towards Expressive Publish/Subscribe Systems. In Proc. Int. Conf. on Extending Database Technology (EDBT), pages 627-644, 2006
W. Y. Arms, S. Aya, M. Calimlim, J. Cordes, J. Deneva, P. Dmitriev, J. Gehrke, L. Gibbons, C. D. Jones, V. Kuznetsov, D. Lifka, M. Riedewald, D. Riley, A. Ryd, and G. J. Sharp. Three Case Studies of Large-Scale Data Flows. In Proc. IEEE Workshop on Workflow and Data Flow for Scientific Applications (SciFlow). 2006
F. Yang, J. Shanmugasundaram, M. Riedewald, J. Gehrke, and A. Demers, Hilda: A High-Level Language for Data-Driven Web Applications. In Proc. IEEE Int. Conf. on Data Engineering (ICDE), 2006
A. Das, J. Gehrke, M. Riedewald. Semantic Approximation of Data Stream Joins. In IEEE Transactions on Knowledge and Data Engineering, 17(1):44-59, 2005
A. Demers, J. Gehrke, M. Hong, and M. Riedewald. Processing High-Speed Intelligence Feeds in Real-Time. In Proc. IEEE Int. Conf. on Intelligence and Security Informatics (ISI), pages 617-618, 2005
M. Riedewald, D. Agrawal, A. El Abbadi. Dynamic Multidimensional Data Cubes for Interactive Analysis of Massive Datasets. In M. Khosrow-Pour, editor, Encyclopedia of Information Science and Technology. Idea Group Publishing, 2005
A. Das, J. Gehrke, and M. Riedewald. Approximation Techniques for Spatial Data. In Proc. ACM SIGMOD Int. Conf. on Management of Data, pages 695-706, 2004
A. Demers, J. Gehrke, M. Riedewald. Research Issues in Mining and Monitoring of Intelligence Data. To appear in H. Kargupta, A. Joshi, K. Sivakumar, and Y. Yesha, editors, Data Mining: Next Generation Challenges and Future Directions. MIT/AAAI Press, 2004
A. Demers, J. Gehrke, M. Riedewald. The Architecture of the Cornell Knowledge Broker. In Proc. Second Symposium on Intelligence and Security Informatics (ISI-2004), 2004
A. Das, J. Gehrke, M. Riedewald. Approximate Join Processing over Data Streams. In Proc. ACM SIGMOD Int. Conf. on Managament of Data, pages 40-51, 2003
M. Riedewald, D. Agrawal, A. El Abbadi, F. Korn. Accessing Scientific Data: Simpler is Better. In Proc. Int. Symp. on Spatial and Temporal Databases, pages 214-232, 2003
H.-G. Li, D. Agrawal, A. El Abbadi, M. Riedewald. Exploiting the Multi-Append-Only-Trend Property of Historical Data in Data Warehouses. In Proc. Int. Symp. on Spatial and Temporal Databases, pages 179-198, 2003
M. Riedewald, D. Agrawal, A. El Abbadi. Dynamic Multidimensional Data Cubes. In M. Rafanelli, editor, Multidimensional Databases: Problems and Solutions. Idea Group Publishing, 2003
M. Riedewald, D. Agrawal, A. El Abbadi. Efficient Integration and Aggregation of Historical Information. In Proc. ACM SIGMOD Int. Conf. on Management of Data, pages 13-24, 2002
I. Stanoi, M. Riedewald, D. Agrawal, A. El Abbadi. Discovery of Influence Sets in Frequently Updated Databases. In Proc. Int. Conf. on Very Large Databases (VLDB), pages 99-108, 2001
M. Riedewald, D. Agrawal, A. El Abbadi. Managing and Analyzing Massive Data Sets with Data Cubes. In J. Abello, P. M. Pardalos, and M. G. C. Resende, editors, Handbook of Massive Data Sets. Kluwer Academic Publishers, 2001
M. Riedewald, D. Agrawal, A. El Abbadi. Flexible Data Cubes for Online Aggregation. In Proc. Int. Conf. on Database Theory (ICDT), pages 159-173, 2001
M. Riedewald, D. Agrawal, A. El Abbadi, and R. Pajarola. Space-Efficient Data Cubes for Dynamic Environments. In Proc. Int. Conf. on Data Warehousing and Knowledge Discovery (DaWaK), pages 24-33, 2000
M. Riedewald, D. Agrawal, and A. El Abbadi. pCube: Update-Efficient Online Aggregation with Progressive Feedback and Error Bounds. In Proc. Int. Conf. on Scientific and Statistical Database Management (SSDBM), pages 95-108, 2000