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MOIRE: Mixed-Order Poisson Regression towards Fine-grained Urban Anomaly Detection at Nationwide Scale.

, , , , and . IEEE BigData, page 963-970. IEEE, (2020)

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MOIRE: Mixed-Order Poisson Regression towards Fine-grained Urban Anomaly Detection at Nationwide Scale., , , , and . IEEE BigData, page 963-970. IEEE, (2020)13.5 A 128Gb 1b/Cell 96-Word-Line-Layer 3D Flash Memory to Improve Random Read Latency with tPROG=75µs and tR=4µs., , , , , , , , , and 13 other author(s). ISSCC, page 226-228. IEEE, (2020)Tappy: Predicting Tap Accuracy of User-Interface Elements by Reverse-Engineering Webpage Structures., , , , and . CoRR, (2024)Location YardStick: Calculation of the Location Data Value Depending on the Users' Context., , , and . IEEE BigData, page 1545-1554. IEEE, (2020)Farming Robots.. J. Robotics Mechatronics, 9 (4): 287-292 (1997)Fine-grained social relationship extraction from real activity data under coarse supervision., , , , and . ISWC, page 183-187. ACM, (2015)Behavioral Differences between Tap and Swipe: Observations on Time, Error, Touch-point Distribution, and Trajectory for Tap-and-swipe Enabled Targets., , and . CHI, page 549:1-549:12. ACM, (2024)Fast Inverse Reinforcement Learning with Interval Consistent Graph for Driving Behavior Prediction., , , and . AAAI, page 1532-1538. AAAI Press, (2017)Single-tap Latency Reduction with Single- or Double- tap Prediction., , , , and . CoRR, (2024)