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2024

  • NEW: A. Bianchi, A. Chai, V. Corvinelli, P. Godfrey, J. Szlichta, C. Zuzarte. Db2une: Tuning Under Pressure via Deep Learning. PVLDB, 17(12): 3855-3868, 2024.
  • R. Karegar, M. Mirsafian, P. Godfrey, L. Golab, M. Kargar, D. Srivastava, J. Szlichta. Discovering Approximate Implicit Domain Orders through Order Dependencies. VLDB J., 1-26 pages, 2024.
  • R. Hamidi, H. Fani, E. Bagheri, M. Kargar, D. Srivastava, J. Szlichta. Variational Neural Architecture for Skill-based Team Formation. ACM TOIS, 42(1): 7:1-7:28 (2024), 2024.
  • A. Yu, P. Godfrey, L. Golab, D. Srivastava, J. Szlichta. CAMO: Explaining Consensus Across MOdels. IEEE ICDE, 1-4, 2024.
  • J. Rorseth, P. Godfrey, L. Golab, D. Srivastava, J. Szlichta. RAGE Against the Machine: Retrieval-Augmented LLM Explanations. IEEE ICDE, 1-4, 2023.
  • K. Golzadeh, L. Golab, J. Szlichta. Explaining Expert Search Systems with ExES. IEEE ICDE, 1-4, 2024.
  • A. Yu, P. Godfrey, L. Golab, D. Srivastava, J. Szlichta. Explaining Consensus Patterns Across Multiple Models. IEEE ICDE, 1-2, 2024.
  • J. Rorseth, P. Godfrey, L. Golab, D. Srivastava, J. Szlichta. Towards Explainability in Retrieval-Augmented LLMs. IEEE ICDE, 1-2, 2024.
  • A. Esmaelizadeh, J. Rorseth, Andy Yu, P. Godfrey, L. Golab, D. Srivastava, J. Szlichta, K. Taghva. On Integrating the Data-Science and Machine-Learning Pipelines for Responsible AI. Guide-AI @ ACM SIGMOD, 50-53 pages, 2024.
  • ML4DM: The fourth workshop on the emerging applications of machine learning in modern data management. ACM CASCON, 1-4, 2024.

2023

  • H. Nguyen, R. Hamidi, F. Al-Obeidat, E. Bagheri, M. Kargar, D. Srivastava, J. Szlichta, F. Zarrinkalam. Learning Heterogenous Subgraph Representations for Team Discovery. Information Retrieval Journal, Springer, 26(1): 8, 2023.
  • C. Henderson, V. Corvinelli, P. Godfrey, P. Mierzejewski, J. Szlichta, C. Zuzarte. BLUTune: Tuning Up IBM Db2 with ML. IEEE ICDE, 3615-3618, 2023.
  • J. Rorseth, P. Godfrey, L. Golab, M. Kargar, D. Srivastava, J. Szlichta. CREDENCE: Counterfactual Explanations for Document Ranking. IEEE ICDE, 3631-3634, 2023.
  • A. Bianchi, R. Karegar, P. Godfrey, L. Golab, M. Kargar, D. Srivastava, J. Szlichta. iORDER: Mining Implicit Domain Orders. IEEE ICDE, 3623-3626, 2023.
  • A. Chai, A. Vezvaei, L. Golab, M. Kargar, D. Srivastava, J. Szlichta and M. Zihayat. EAGER: Explainable Question Answering Using Knowledge Graphs. GRADES-NDA @ ACM SIGMOD, 4:1-4:5, 2023.
  • A. Kamali, C. Zuzarte, V. Kantere, J. Szlichta, Y. Chen, X. Yu, N. Wang. ML4DM: Emerging applications of machine learning in modern data management (third edition). ACM CASCON @ IBM TechXchange, 3 pages, 2023.
  • J. Szlichta, C. Zuzarte, A. Kamali, V. Kantere, X. Yu. Machine Learning Based Modern Data Systems. ACM CASCON @ IBM TechXchange, abstract paper (speaker series), 2023. 

2022

  • C. Henderson, S. Bryson, V. Corvinelli, P. Godfrey, P. Mierzejewski, J. Szlichta, C. Zuzarte. BLUTune: Query-informed Multi-stage IBM Db2 Tuning via ML. ACM CIKM, 3162-3171, 2022.
  • R. Karegar, M. Mirsafian, P. Godfrey, L. Golab, M. Kargar, D. Srivastava, J. Szlichta. Discovering Implicit Domain Orders through Order Dependencies. IEEE ICDE, 1098-1110, 2022.
  • P. Li, J. Szlichta, M. Böhlen, D. Srivastava. ABC of Order Dependencies. VLDB J., 31(15): 825-849, 2022.
  • M. Kargar, L. Golab, D. Srivastava, J. Szlichta, M. Zihayat. Effective Keyword Search over Weighted Graph Social Networks. IEEE TKDE 34(2): 601-616, 2022.
  • Zheng Zheng, Longtao Zheng, Morteza Alipour Langouri, Fei Chiang, Lukasz Golab, Jaroslaw Szlichta: Discovery and Contextual Data Cleaning with Ontology Functional Dependencies. ACM JDIQ, 14(3) 20:1-20:26, 2022.
  • P. Li, J. Jessica, N. Tania, M. Böhlen, D. Srivastava, J. Szlichta. Mining Band Order Dependencies. IEEE ICDE, 3162-3165, 2022.
  • A. Vezvaei, L. Golab, M. Kargar, D. Srivastava, J. Szlichta, M. Zihayat. Fine-Tuning Dependencies with Parameters. EDBT, 393-397, 2022.
  • R. Hamidi, E. Bagheri, M. Kargar, D. Srivastava, J. Szlichta. Subgraph Representation Learning for Team Mining. ACM WebSci, 148-153, 2022.
  • A. Kamali, C. Zuzarte, J. Szlichta, S. Quader, V. Kantere, Y. Chen. Emerging applications of machine learning in modern data management. ACM CASCON, 3 pages, 2022.
  • M. Kargar, J. Szlichta, M. Zihayat. Keyword Search Over Enterprise Data Using Advanced Machine Learning. CORS/INFORMS, abstract submission, 2022.

2021

  • A. Mihaylov, V. Corvinelli, P. Godfrey, P. Mierzejewski, J. Szlichta, C. Zuzarte. Scalable Learning to Troubleshoot Query Performance Problems. ACM CIKM, 4016-4025, 2021.
  • R. Hamidi, A. Mitha, H. Fani, M. Kargar, J. Szlichta, E. Bagheri. PyTFL: A Python-based Neural Team Formation Toolkit. ACM CIKM, 4716-4720, 2021.
  • J. Nemec, H. Davoudi, L. Golab, M. Kargar, Y. Lytvyn, P. Mierzejewski, J. Szlichta, M. Zihayat. RW-Team: Robust Team Formation using Random Walk. ACM CIKM, 4759-4763, 2021.
  • B. Askari, J. Szlichta, A. Salehi-Abari. Variational Autoencoders for Top-K Recommendation with Implicit Feedback. ACM SIGIR, 2061-2065, 2021.
  • R. Hamidi, E. Bagheri, M. Kargar, D. Srivastava, J. Szlichta. Retrieving Skill-Based Teams from Collaboration Network. ACM SIGIR, 2015-2019, 2021.
  • R. Karegar, L. Godfrey, L. Golab, M. Kargar, J. Szlichta, D. Srivastava. Efficient Discovery of Approximate Order Dependencies. EDBT, 427-432, 2021.
  • M. Kargar, L. Golab, D. Srivastava, J. Szlichta, M. Zihayat. Effective Keyword Search in Weighted Graphs (Extended Abstract). IEEE ICDE, 2350-2351, 2021.
  • S. Bryson, C. Henderson, V. Corvinelli, P. Godfrey, P. Mierzejewski, J. Szlichta, C. Zuzarte. Database Management Systems Tuning through AI. Canadian AI, industry track, 1-4, 2021.
  • M. Kargar, J. Szlichta, M. Zihayat. Environmentally Friendly Tour Recommendations using Sustainable Transporters. CORS/INFORMS, abstract submission, 2021.

2020

  • S. Bryson, H. Davoudi, L. Golab, M. Kargar, Y. Lytvyn, P. Mierzejewski, J. Szlichta, M. Zihayat. Robust Keyword Search in Large Attributed Graphs. Information Retrieval Journal, Springer, 23(5): 502-524 (2020).
  • A. Khan, L. Golab, M. Kargar, J. Szlichta, M. Zihayat. Compact Group Discovery in Attributed Graphs and Social Networks. Information Processing and Management, Elsevier, 57 (2):102054-72, 2020.
  • P. Li, J. Szlichta, M. Böhlen and D. Srivastava. Discovering Band Order Dependencies. IEEE ICDE, 1878-1881.
  • R. Hamidi, H. Fani, M. Kargar, J. Szlichta, Ebrahim Bagheri. Learning to Form Skill-based Teams of Experts. ACM CIKM, 2049-2052, 2020.
  • J. Szlichta, P. Godfrey, L. Golab, M. Kargar, D. Srivastava. Erratum for Discovering Order Dependencies through Order Compatibility. EDBT, 659-663, 2020.

2019

  • G. Damasio, V. Corvinelli, P. Godfrey, P. Mierzejewski, A. Mihaylov,  J. Szlichta, C. Zuzarte. Guided Automated Learning for query workload re-Optimization. PVLDB 12(12): 2010-2021, 2019.
  •  G. Damasio, S. Bryson, V. Corvinelli, P. Godfrey, P. Mierzejewski, J. Szlichta, C. Zuzarte. GALO: Guided Automated Learning for re-Optimization. PVLDB, 12(12): 1778-1781, 2019.
  • M. Zihayat, M. Kargar, J. Szlichta. A Survey of High Utility Pattern Mining Algorithms for Big Data. High-Utility Pattern Mining: Theory, Algorithms and Applications, Springer, 75-96, 2019.
  • H. Davoudi, P. Godfrey, L. Golab, M. Kargar and D. Srivastava,  J. Szlichta . Bringing Order to Data. AMW, 5.1-5, 2019.
  • M. Kargar, M. Zihayat, J. Szlichta. Mining and Exploration of Attributed Graphs: Theory and Applications. ACM CASCON x EVOKE (organized by IBM), 397-398, 2019.

2018

  • J. Szlichta, P. Godfrey, L. Golab, M. Kargar and D. Srivastava. Effective and Complete Discovery of Bidirectional Order Dependencies via Set-based Axioms. VLDB Journal 27(4): 573-591, 2018.
  • A. Mihaylov, P. Godfrey, L. Golab, M. Kargar, D. Srivastava and J. Szlichta. FastOD: Bringing Order to Data. IEEE ICDE, 1561-1564, 2018.
  • Z. Zheng, M. Alipour Langouri, Z. Qu, I. Currie, F. Chiang, L. Golab and J. Szlichta. FastOFD: Contextual Data Cleaning with Ontology Functional Dependencies. EDBT, 694-697, 2018.
  • M. Alipour-Langouri, Z. Zheng, F. Chiang, L. Golab and J. Szlichta. Contextual Data Cleaning. IEEE ICDE workshop on Context in Analytics, 21-24, 2018.
  • M. Zihayat, A. An, L. Golab, M. Kargar and J. Szlichta. Effective Team Formation in Expert Networks. AMW, 4.1-4, 2018.
  • J. Szlichta: Order Dependencies. Encyclopedia of Database Systems, Springer, Editors: L. Liu (Georgia Tech) and T. Özsu (University of Waterloo), 2631-2632, 2018.

2017

  • J.Szlichta, P. Godfrey, L. Golab, M. Kargar and D. Srivastava: Effective and Complete Discovery of Order Dependencies via Set-based Axiomatization. PVLDB 10(7): 721-732, 2017.
  • S. Baskaran, A. Keller, F. Chiang, L. Golab and J. Szlichta, Efficient Discovery of Ontology Functional Dependencies, ACM CIKM 2017, 1847-1856.
  • M. Zihayat, A. An, L. Golab, M. Kargar and J. Szlichta: Authority-Based Team Discovery in Social Networks. EDBT, 498-501, 2017.
  • M. Kargar, A. An, P. Godfrey, J. Szlichta and X. YuL Meaningful Keyword Search over Databases with Complex Schema. AMW, 4 pages, 2017.

2016

  • G. Damasio, P. Mierzejewski, J. Szlichta and C. Zuzarte: Query Performance Problem Determination with Knowledge Base in Semantic Web System OptImatch. EDBT 2016, 515-526.
  • M. Kargar, L. Golab and J. Szlichta: eGraphSearch: Effective Keyword Search in Graphs. ACM CIKM 2016, 2461-2464.
  • G. Damasio, P. Mierzejewski, J. Szlichta and C. Zuzarte: OptImatch: Semantic Web System for Query Problem Determination. IEEE ICDE 2016, 1334-1337.
  • M. Ferron, K. Pu and J. Szlichta: ARC: A Pipeline Approach Enabling Large-Scale Graph Visualization. ACM/IEEE ASONAM 2016, 1397-1400.
  • A. Keller, J. Szlichta: Ontology Functional Dependencies. AMW 2016, 4 pages.

2015

  • N. Prokoshyna, J. Szlichta, F. Chiang, R. J. Miller and D. Srivastava: Combining Quantitative and Logical Data Cleaning. PVLDB 9(4): 300-311, 2015.
  • M. Kargar, A. An, N. Cercone, P. Godfrey, J. Szlichta and  X. Yu: Meaningful Keyword Search in Relational Databases with Large and Complex Schema. IEEE ICDE 2015, 411-422.
  • J. Szlichta, Lukasz Golab, D. Srivastava:
    On Axiomatization and Inference Complexity over a Hierarchy of Functional Dependencies. AMW 2015, 12 pages.

2014

  • M. Volkovs, F. Chiang, J. Szlichta, R. Miller: Continuous data cleaning. IEEE ICDE 2014: 244-255.
  • J. Szlichta, P. Godfrey, J. Gryz, W. Ma, W. Qiu, Calisto Zuzarte: Business-Intelligence Queries with Order Dependencies in DB2. EDBT 2014: 750-761.
  • M. Kargar, A. An, N. Cercone, P. Godfrey, J. Szlichta, X. Yu: MeanKS: meaningful keyword search in relational databases with complex schema. ACM SIGMOD Conference 2014: 905-908.

2013

  • J. Szlichta, P. Godfrey, J. Gryz, C. Zuzarte: Expressiveness and Complexity of Order Dependencies. PVLDB 6(14): 1858-1869, 2013.
  • J. Szlichta, P. Godfrey, J. Gryz, C. Zuzarte: Axiomatic System for Order Dependencies. AMW, 4 pages, 2013.

2012

  • J. Szlichta, P. Godfrey, J. Gryz: Fundamentals of Order Dependencies. PVLDB 5(11): 1220-1231, 2012.
  • J. Szlichta, P. Godfrey, J. Gryz: Chasing Polarized Order Dependencies. AMW 2012: 168-179.

2011

  • J. Szlichta, P. Godfrey, J. Gryz, W. Ma, P. Pawluk, C. Zuzarte: Queries on dates: fast yet not blind. EDBT 2011: 497-502.