受强制性开放获取政策约束的文章 - Wentao Wu了解详情
可在其他位置公开访问的文章：15 篇
Towards demystifying serverless machine learning training
J Jiang, S Gan, Y Liu, F Wang, G Alonso, A Klimovic, A Singla, W Wu, ...
Proceedings of the 2021 International Conference on Management of Data, 857-871, 2021
强制性开放获取政策： Swiss National Science Foundation, European Commission
Ease. ml: Towards multi-tenant resource sharing for machine learning workloads
T Li, J Zhong, J Liu, W Wu, C Zhang
Proceedings of the VLDB Endowment 11 (5), 607-620, 2018
强制性开放获取政策： Swiss National Science Foundation
Semantic bootstrapping: a theoretical perspective
W Wu, H Li, H Wang, KQ Zhu
IEEE Transactions on Knowledge and Data Engineering 29 (2), 446-457, 2016
强制性开放获取政策： 国家自然科学基金委员会
Openbox: A generalized black-box optimization service
Y Li, Y Shen, W Zhang, Y Chen, H Jiang, M Liu, J Jiang, J Gao, W Wu, ...
Proceedings of the 27th ACM SIGKDD conference on knowledge discovery & data …, 2021
强制性开放获取政策： 国家自然科学基金委员会
Mlog: Towards declarative in-database machine learning
X Li, B Cui, Y Chen, W Wu, C Zhang
Proceedings of the VLDB Endowment 10 (12), 1933-1936, 2017
强制性开放获取政策： Swiss National Science Foundation, 国家自然科学基金委员会
VolcanoML: speeding up end-to-end AutoML via scalable search space decomposition
Y Li, Y Shen, W Zhang, J Jiang, Y Li, B Ding, J Zhou, Z Yang, W Wu, ...
Proceedings of the VLDB Endowment 14 (11), 2167-2176, 2021
强制性开放获取政策： Swiss National Science Foundation, 国家自然科学基金委员会, European Commission
Mllib*: Fast training of glms using spark mllib
Z Zhang, J Jiang, W Wu, C Zhang, L Yu, B Cui
2019 IEEE 35th International Conference on Data Engineering (ICDE), 1778-1789, 2019
强制性开放获取政策： 国家自然科学基金委员会
Ease. ML: A lifecycle management system for MLDev and MLOps
L Aguilar, D Dao, S Gan, NM Gurel, N Hollenstein, J Jiang, B Karlas, ...
Conference on Innovative Data Systems Research (CIDR), 2021
强制性开放获取政策： Swiss National Science Foundation, European Commission
MLbench: benchmarking machine learning services against human experts
Y Liu, H Zhang, L Zeng, W Wu, C Zhang
Proceedings of the VLDB Endowment 11 (10), 1220-1232, 2018
强制性开放获取政策： Swiss National Science Foundation, 国家自然科学基金委员会, European Commission
In-database machine learning with corgipile: Stochastic gradient descent without full data shuffle
L Xu, S Qiu, B Yuan, J Jiang, C Renggli, S Gan, K Kara, G Li, J Liu, W Wu, ...
Proceedings of the 2022 International Conference on Management of Data, 1286 …, 2022
强制性开放获取政策： Swiss National Science Foundation, 中国科学院, European Commission
Ease. ml/ci and ease. ml/meter in action: Towards data management for statistical generalization
C Renggli, FA Hubis, B Karlaš, K Schawinski, W Wu, C Zhang
Proceedings of the VLDB Endowment 12 (12), 1962-1965, 2019
强制性开放获取政策： Swiss National Science Foundation
The Case for ML-Enhanced High-Dimensional Indexes
R Kang, W Wu, C Wang, C Zhang, J Wang
3rd International Workshop on Applied AI for Database Systems and …, 2021
强制性开放获取政策： 国家自然科学基金委员会
Ease. ml/snoopy in action: Towards automatic feasibility analysis for machine learning application development
C Renggli, L Rimanic, L Kolar, W Wu, C Zhang
Proceedings of the VLDB Endowment 13 (12), 2837-2840, 2020
强制性开放获取政策： Swiss National Science Foundation
ColumnSGD: A Column-oriented Framework for Distributed Stochastic Gradient Descent
Z Zhang, W Wu, J Jiang, L Yu, B Cui, C Zhang
2020 IEEE 36th International Conference on Data Engineering (ICDE), 1513-1524, 2020
强制性开放获取政策： 国家自然科学基金委员会
Automatic feasibility study via data quality analysis for ml: A case-study on label noise
C Renggli, L Rimanic, L Kolar, W Wu, C Zhang
2023 IEEE 39th International Conference on Data Engineering (ICDE), 218-231, 2023
强制性开放获取政策： US National Science Foundation, Swiss National Science Foundation, European …
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