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Q-graph: preserving query locality in multi-query graph processing.

, , , , and . GRADES/NDA@SIGMOD/PODS, page 6:1-6:10. ACM, (2018)

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StreamLearner: Distributed Incremental Machine Learning on Event Streams: Grand Challenge., , and . DEBS, page 298-303. ACM, (2017)GraphCEP: real-time data analytics using parallel complex event and graph processing., , , and . DEBS, page 309-316. ACM, (2016)Q-graph: preserving query locality in multi-query graph processing., , , , and . GRADES/NDA@SIGMOD/PODS, page 6:1-6:10. ACM, (2018)Rollback-recovery without checkpoints in distributed event processing systems., , , , and . DEBS, page 27-38. ACM, (2013)Meeting predictable buffer limits in the parallel execution of event processing operators., , and . BigData, page 402-411. IEEE Computer Society, (2014)Scalable Deep Learning on Distributed Infrastructures: Challenges, Techniques and Tools., and . CoRR, (2019)SPECTRE: supporting consumption policies in window-based parallel complex event processing., , , , , and . Middleware, page 161-173. ACM, (2017)Scalable Deep Learning on Distributed Infrastructures: Challenges, Techniques, and Tools., and . ACM Comput. Surv., 53 (1): 3:1-3:37 (2020)Distributed complex event processing for mobile large-scale video applications., , and . Middleware (Posters & Demos), page 5-6. ACM, (2014)P4CEP: Towards In-Network Complex Event Processing., , , , , and . NetCompute@SIGCOMM, page 33-38. ACM, (2018)