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Time2Feat: Learning Interpretable Representations for Multivariate Time Series Clustering., , , and . Proc. VLDB Endow., 16 (2): 193-201 (2022)Landmark Explanation: An Explainer for Entity Matching Models., , , and . CIKM, page 4680-4684. ACM, (2021)Evaluating the integration of datasets., , , and . SAC, page 347-356. ACM, (2022)An Intrinsically Interpretable Entity Matching System., , , , and . EDBT, page 645-657. OpenProceedings.org, (2023)Unsupervised Evaluation of Data Integration Processes., , , and . iiWAS, page 77-81. ACM, (2020)Automated Machine Learning for Entity Matching Tasks., , , , and . EDBT, page 325-330. OpenProceedings.org, (2021)Avoiding the Pitfalls on Stock Market: Challenges and Solutions in Developing Quantitative Strategies., , , , and . Ital-IA, volume 3486 of CEUR Workshop Proceedings, page 489-494. CEUR-WS.org, (2023)Transforming ML Predictive Pipelines into SQL with MASQ., , , , and . SIGMOD Conference, page 2696-2700. ACM, (2021)Landmark Explanation: a Tool for Entity Matching., , , and . SEBD, volume 3194 of CEUR Workshop Proceedings, page 69-76. CEUR-WS.org, (2022)Interpretable Entity Matching with WYM., , , , , and . SEBD, volume 3478 of CEUR Workshop Proceedings, page 101-109. CEUR-WS.org, (2023)