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Interpreting deep learning models for entity resolution: an experience report using LIME.

, , , , and . aiDM@SIGMOD, page 8:1-8:4. ACM, (2019)

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Engineering Color Barcode Algorithms for Mobile Applications., , and . SEA, volume 8504 of Lecture Notes in Computer Science, page 211-222. Springer, (2014)Self-supervised learning for medieval handwriting identification: A case study from the Vatican Apostolic Library., , , , , and . Inf. Process. Manag., 59 (3): 102875 (2022)In Codice Ratio: A crowd-enabled solution for low resource machine transcription of the Vatican Registers., , , and . Inf. Process. Manag., 58 (5): 102606 (2021)Fast Enumeration of Large k-Plexes., , , , and . KDD, page 115-124. ACM, (2017)Resolving duplicates in Large Multiple-Choice Questions Repositories., , , , , and . IRCDL, volume 3643 of CEUR Workshop Proceedings, page 34-40. CEUR-WS.org, (2024)Managing Large Multiple-choice Test Items Repositories., , , , and . IV, page 275-279. IEEE, (2022)Effective Explanations for Entity Resolution Models., , , , , and . ICDE, page 2709-2721. IEEE, (2022)Crowdsourcing for Building Knowledge Graphs at Scale from the Vatican Archives., , , , and . SEBD, volume 2646 of CEUR Workshop Proceedings, page 242-249. CEUR-WS.org, (2020)Real-time analysis of critical nodes in network cores., , and . IWCMC, page 42-46. IEEE, (2012)On Unifying the Space of ℓ0-Sampling Algorithms., and . ALENEX, page 163-172. SIAM, (2013)