ASR n-best fusion nets X Liu, M Li, L Chen, P Wanigasekara, W Ruan, H Khan, W Hamza, C Su ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021 | 48 | 2021 |
Mining conditional functional dependency rules on big data M Li, H Wang, J Li Big Data Mining and Analytics 3 (1), 68-84, 2019 | 46 | 2019 |
Automated debugging in data-intensive scalable computing MA Gulzar, M Interlandi, X Han, M Li, T Condie, M Kim Proceedings of the 2017 Symposium on Cloud Computing, 520-534, 2017 | 34 | 2017 |
Cleanix: A parallel big data cleaning system H Wang, M Li, Y Bu, J Li, H Gao, J Zhang ACM SIGMOD Record 44 (4), 35-40, 2016 | 30 | 2016 |
An Efficient Sliding Window Approach for Approximate Entity Extraction with Synonyms. J Wang, C Lin, M Li, C Zaniolo EDBT, 109-120, 2019 | 27 | 2019 |
Rios: Runtime integrated optimizer for spark Y Li, M Li, L Ding, M Interlandi Proceedings of the ACM Symposium on Cloud Computing, 275-287, 2018 | 27 | 2018 |
Improving spoken language understanding by exploiting asr n-best hypotheses M Li, W Ruan, X Liu, L Soldaini, W Hamza, C Su arXiv preprint arXiv:2001.05284, 2020 | 22 | 2020 |
Boosting approximate dictionary-based entity extraction with synonyms J Wang, C Lin, M Li, C Zaniolo Information Sciences 530, 1-21, 2020 | 20 | 2020 |
Cleanix: A big data cleaning parfait H Wang, M Li, Y Bu, J Li, H Gao, J Zhang Proceedings of the 23rd ACM International Conference on Conference on …, 2014 | 15 | 2014 |
BigData Applications from Graph Analytics to Machine Learning by Aggregates in Recursion CZ Ariyam Das, Youfu Li, Jin Wang, Mingda Li The 35th International Conference on Logic Programming (ICLP 2019) 306, 273-279, 2019 | 14* | 2019 |
Formal semantics and high performance in declarative machine learning using datalog J Wang, J Wu, M Li, J Gu, A Das, C Zaniolo The VLDB Journal 30 (5), 859-881, 2021 | 13 | 2021 |
Monotonic properties of completed aggregates in recursive queries C Zaniolo, A Das, J Gu, Y Li, J Wang arXiv preprint arXiv:1910.08888, 2019 | 8 | 2019 |
Multi-task learning of spoken language understanding by integrating n-best hypotheses with hierarchical attention M Li, X Liu, W Ruan, L Soldaini, W Hamza, C Su Proceedings of the 28th International Conference on Computational …, 2020 | 7 | 2020 |
Deep Learning IP Network Representations M Li, C Lumezanu, B Zong, H Chen ACM SIGCOMM Big-DAMA, 33-39, 2018 | 7 | 2018 |
Developing Big-Data Application as Queries: an Aggregate-Based approach. C Zaniolo, A Das, J Gu, Y Li, M Li, J Wang IEEE Data Eng. Bull. 44 (2), 3-13, 2021 | 3 | 2021 |
Kddlog: Performance and scalability in knowledge discovery by declarative queries with aggregates Y Li, J Wang, M Li, A Das, J Gu, C Zaniolo 2021 IEEE 37th International Conference on Data Engineering (ICDE), 1260-1271, 2021 | 2 | 2021 |
Efficient Latent Semantic Extraction from Cross Domain Data with Declarative Language M Li University of California, Los Angeles, 2020 | 2 | 2020 |
Learning IP network representations M Li, B Zong, C Lumezanu, H Chen ACM SIGCOMM Computer Communication Review 48 (5), 48-54, 2019 | 2 | 2019 |
PEIF: 基于并行机群的大数据实体识别算法 李明达, 王宏志, 张佳程, 李建中, 高宏 计算机研究与发展, 211-220, 2013 | 1 | 2013 |
Policy-driven Knowledge Selection and Response Generation for Document-grounded Dialogue L Ma, J Li, M Li, WN Zhang, T Liu ACM Transactions on Information Systems 42 (2), 1-29, 2023 | | 2023 |