Approximate Denial Constraints
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Ihab F. Ilyas | Benny Kimelfeld | Alireza Heidari | Ester Livshits | I. Ilyas | B. Kimelfeld | Ester Livshits | Alireza Heidari
[1] Paola Vera-Licona,et al. The minimal hitting set generation problem: algorithms and computation , 2016, SIAM J. Discret. Math..
[2] Santo Fortunato,et al. Community detection in graphs , 2009, ArXiv.
[3] Marc Boullé,et al. Universal Approximation of Edge Density in Large Graphs , 2015, ArXiv.
[4] Felix Naumann,et al. Discovery of Approximate (and Exact) Denial Constraints , 2019, Proc. VLDB Endow..
[5] Felix Naumann,et al. Functional Dependency Discovery: An Experimental Evaluation of Seven Algorithms , 2015, Proc. VLDB Endow..
[6] Chengfei Liu,et al. Discover Dependencies from Data—A Review , 2012, IEEE Transactions on Knowledge and Data Engineering.
[7] H. White,et al. “Structural Equivalence of Individuals in Social Networks” , 2022, The SAGE Encyclopedia of Research Design.
[8] Jan Chomicki,et al. Minimal-change integrity maintenance using tuple deletions , 2002, Inf. Comput..
[9] Hannu Toivonen,et al. TANE: An Efficient Algorithm for Discovering Functional and Approximate Dependencies , 1999, Comput. J..
[10] Pietro Sala,et al. Mining approximate temporal functional dependencies with pure temporal grouping in clinical databases , 2015, Comput. Biol. Medicine.
[11] Santosh S. Vempala,et al. Algorithms for implicit hitting set problems , 2011, SODA '11.
[12] Renée J. Miller,et al. Discovering data quality rules , 2008, Proc. VLDB Endow..
[13] Lhouari Nourine,et al. Partial Enumeration of Minimal Transversals of a Hypergraph , 2015, CLA.
[14] Uriel Feige,et al. On sums of independent random variables with unbounded variance, and estimating the average degree in a graph , 2004, STOC '04.
[15] Rui Abreu,et al. A Low-Cost Approximate Minimal Hitting Set Algorithm and its Application to Model-Based Diagnosis , 2009, SARA.
[16] Kathryn B. Laskey,et al. Stochastic blockmodels: First steps , 1983 .
[17] Benny Kimelfeld,et al. Computing Optimal Repairs for Functional Dependencies , 2017, PODS.
[18] Laks V. S. Lakshmanan,et al. Discovering Conditional Functional Dependencies , 2009, 2009 IEEE 25th International Conference on Data Engineering.
[19] Leopoldo E. Bertossi,et al. Complexity of Consistent Query Answering in Databases Under Cardinality-Based and Incremental Repair Semantics , 2006, ICDT.
[20] Rosine Cicchetti,et al. FUN: An Efficient Algorithm for Mining Functional and Embedded Dependencies , 2001, ICDT.
[21] Jean-Marc Petit,et al. Efficient Discovery of Functional Dependencies and Armstrong Relations , 2000, EDBT.
[22] Paolo Papotti,et al. Discovering Denial Constraints , 2013, Proc. VLDB Endow..
[23] Staal A. Vinterbo,et al. Minimal approximate hitting sets and rule templates , 2000, Int. J. Approx. Reason..
[24] Rui Abreu,et al. MHS2: A Map-Reduce Heuristic-Driven Minimal Hitting Set Search Algorithm , 2013, MUSEPAT.
[25] Felix Naumann,et al. Efficient Denial Constraint Discovery with Hydra , 2017, Proc. VLDB Endow..
[26] Eduardo Cunha de Almeida,et al. BFASTDC: A Bitwise Algorithm for Mining Denial Constraints , 2018, DEXA.
[27] Theodoros Rekatsinas,et al. HoloDetect: Few-Shot Learning for Error Detection , 2019, SIGMOD Conference.
[28] Ihab F. Ilyas,et al. Principles of Progress Indicators for Database Repairing , 2019, ArXiv.
[29] Tao Jiang,et al. Discovering Approximate Functional Dependencies from Distributed Big Data , 2016, APWeb.
[30] Phipps Arabie,et al. Constructing blockmodels: How and why , 1978 .
[31] Theodoros Rekatsinas,et al. Approximate Inference in Structured Instances with Noisy Categorical Observations , 2019, UAI.
[32] Floris Geerts,et al. Revisiting Conditional Functional Dependency Discovery: Splitting the "C" from the "FD" , 2018, ECML/PKDD.
[33] Peter A. Flach,et al. Database Dependency Discovery: A Machine Learning Approach , 1999, AI Commun..
[34] Heikki Mannila,et al. Approximate Dependency Inference from Relations , 1992, ICDT.
[35] Edward L. Robertson,et al. FastFDs: A Heuristic-Driven, Depth-First Algorithm for Mining Functional Dependencies from Relation Instances - Extended Abstract , 2001, DaWaK.
[36] Nabil H. Mustafa,et al. Practical and efficient algorithms for the geometric hitting set problem , 2018, Discret. Appl. Math..
[37] Charu C. Aggarwal,et al. Graph Clustering , 2010, Encyclopedia of Machine Learning and Data Mining.
[38] Guy Van den Broeck,et al. The most probable database problem , 2014 .
[39] Reuven Bar-Yehuda,et al. A Linear-Time Approximation Algorithm for the Weighted Vertex Cover Problem , 1981, J. Algorithms.
[40] Takeaki Uno,et al. Efficient algorithms for dualizing large-scale hypergraphs , 2011, Discret. Appl. Math..
[41] Dana Ron,et al. On Estimating the Average Degree of a Graph , 2004, Electron. Colloquium Comput. Complex..