| k-Shape: Efficient and Accurate Clustering of Time Series J Paparrizos, L Gravano Proceedings of the 2015 ACM SIGMOD International Conference on Management of …, 2015 | 1078 | 2015 |
| Fast and Accurate Time-Series Clustering J Paparrizos, L Gravano ACM Transactions on Database Systems (TODS) 42 (2), 1-49, 2017 | 254 | 2017 |
| Machine Learned Job Recommendation J Paparrizos, BB Cambazoglu, A Gionis Proceedings of the fifth ACM Conference on Recommender Systems, 325-328, 2011 | 211 | 2011 |
| Screening for pancreatic adenocarcinoma using signals from web search logs: Feasibility study and results J Paparrizos, RW White, E Horvitz Journal of Oncology Practice 12 (8), 737-744, 2016 | 158 | 2016 |
| TSB-UAD: an end-to-end benchmark suite for univariate time-series anomaly detection J Paparrizos, Y Kang, P Boniol, RS Tsay, T Palpanas, MJ Franklin Proceedings of the VLDB Endowment 15 (8), 1697-1711, 2022 | 123 | 2022 |
| SAND: streaming subsequence anomaly detection P Boniol, J Paparrizos, T Palpanas, MJ Franklin Proceedings of the VLDB Endowment 14 (10), 1717-1729, 2021 | 97* | 2021 |
| The social dynamics of language change in online networks R Goel, S Soni, N Goyal, J Paparrizos, H Wallach, F Diaz, J Eisenstein International conference on social informatics, 41-57, 2016 | 87 | 2016 |
| Predicting the impact of scientific concepts using full‐text features K McKeown, H Daume III, S Chaturvedi, J Paparrizos, K Thadani, P Barrio, ... Journal of the Association for Information Science and Technology 67 (11 …, 2016 | 85 | 2016 |
| Volume under the surface: a new accuracy evaluation measure for time-series anomaly detection J Paparrizos, P Boniol, T Palpanas, RS Tsay, A Elmore, MJ Franklin Proceedings of the VLDB Endowment 15 (11), 2774-2787, 2022 | 84 | 2022 |
| Debunking four long-standing misconceptions of time-series distance measures J Paparrizos, C Liu, AJ Elmore, MJ Franklin Proceedings of the 2020 ACM SIGMOD International Conference on Management of …, 2020 | 74 | 2020 |
| VergeDB: A Database for IoT Analytics on Edge Devices. J Paparrizos, C Liu, B Barbarioli, J Hwang, I Edian, AJ Elmore, ... CIDR, 2021 | 73 | 2021 |
| GRAIL: efficient time-series representation learning J Paparrizos, MJ Franklin Proceedings of the VLDB Endowment 12 (11), 1762-1777, 2019 | 66 | 2019 |
| Band-limited training and inference for convolutional neural networks A Dziedzic*, J Paparrizos* (*equal contribution), S Krishnan, A Elmore, ... International Conference on Machine Learning, 1745-1754, 2019 | 60 | 2019 |
| Effective metadata management in federated sensor networks H Jeung, S Sarni, I Paparrizos, S Sathe, K Aberer, N Dawes, ... 2010 IEEE International Conference on Sensor Networks, Ubiquitous, and …, 2010 | 58 | 2010 |
| Decomposed bounded floats for fast compression and queries C Liu, H Jiang, J Paparrizos, AJ Elmore Proceedings of the VLDB Endowment 14 (11), 2586-2598, 2021 | 43 | 2021 |
| Good to the Last Bit: Data-Driven Encoding with CodecDB H Jiang, C Liu, J Paparrizos, AA Chien, J Ma, AJ Elmore Proceedings of the 2021 International Conference on Management of Data, 843-856, 2021 | 41 | 2021 |
| Fast Adaptive Similarity Search through Variance-Aware Quantization J Paparrizos, I Edian, C Liu, AJ Elmore, MJ Franklin 2022 IEEE 38th International Conference on Data Engineering (ICDE), 2969-2983, 2022 | 32 | 2022 |
| PIDS: attribute decomposition for improved compression and query performance in columnar storage H Jiang, C Liu, Q Jin, J Paparrizos, AJ Elmore Proceedings of the VLDB Endowment 13 (6), 925-938, 2020 | 29 | 2020 |
| Detecting devastating diseases in search logs J Paparrizos, RW White, E Horvitz Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge …, 2016 | 27 | 2016 |
| Theseus: navigating the labyrinth of time-series anomaly detection P Boniol, J Paparrizos, Y Kang, T Palpanas, RS Tsay, AJ Elmore, ... Proceedings of the VLDB Endowment 15 (12), 3702-3705, 2022 | 24* | 2022 |
Michael FranklinUniversity of ChicagoDirección de correo verificada de uchicago.edu
