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Detecting intrusive transactions in databases using partially-ordered sequential rule mining and fractional-distance based anomaly detection.

, , , and . Int. J. Intell. Eng. Informatics, 8 (2): 138-171 (2020)

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AQuA: A Benchmarking Tool for Label Quality Assessment., , , , , and . CoRR, (2023)JoLT: Jointly Learned Representations of Language and Time-Series for Clinical Time-Series Interpretation (Student Abstract)., , , , and . AAAI, page 23447-23448. AAAI Press, (2024)Modeling Involuntary Dynamic Behaviors to Support Intelligent Tutoring (Student Abstract)., , , and . AAAI, page 13799-13800. AAAI Press, (2020)Are You Paying Attention? Detecting Distracted Driving in Real-Time., , , , and . BigMM, page 171-180. IEEE, (2019)The Word is Mightier than the Label: Learning without Pointillistic Labels using Data Programming., and . CoRR, (2021)Discriminating Cognitive Disequilibrium and Flow in Problem Solving: A Semi-Supervised Approach Using Involuntary Dynamic Behavioral Signals., , and . AAAI, page 420-427. AAAI Press, (2020)What's Most Broken? A Tool to Assist Data-Driven Iterative Improvement of an Intelligent Tutoring System., , and . AAAI, page 9941-9942. AAAI Press, (2019)Toward Learning at Scale in Developing Countries: Lessons from the Global Learning XPRIZE Field Study., , , and . L@S, page 175-183. ACM, (2020)Weak Supervision for Affordable Modeling of Electrocardiogram Data., , and . AMIA, AMIA, (2021)What's Most Broken? Design and Evaluation of a Tool to Guide Improvement of an Intelligent Tutor., , and . AIED (1), volume 11625 of Lecture Notes in Computer Science, page 283-295. Springer, (2019)