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ORCIDWentao Wu 0001
Person information
- affiliation: Microsoft Research, Redmond, WA, USA
- affiliation (former): University of Wisconsin-Madison, USA
Other persons with the same name
- Wentao Wu — disambiguation page
- Wentao Wu 0002 — Rensselaer Polytechnic Institute, Troy, NY, USA
- Wentao Wu 0003 — Nanjing University, China
- Wentao Wu 0004 — Soochow University, Center for Systems Biology, Suzhou, China
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2020 – today
- 2024
[j26]Matteo Brucato
, Tarique Siddiqui, Wentao Wu, Vivek R. Narasayya, Surajit Chaudhuri:
Wred: Workload Reduction for Scalable Index Tuning. Proc. ACM Manag. Data 2(1): 50:1-50:26 (2024)- [j25]Xiaoying Wang, Wentao Wu, Chi Wang, Vivek R. Narasayya, Surajit Chaudhuri:
Wii: Dynamic Budget Reallocation In Index Tuning. Proc. ACM Manag. Data 2(3): 182 (2024) - [j24]Jiawei Jiang, Shaoduo Gan, Bo Du, Gustavo Alonso, Ana Klimovic, Ankit Singla, Wentao Wu, Sheng Wang, Ce Zhang:
A systematic evaluation of machine learning on serverless infrastructure. VLDB J. 33(2): 425-449 (2024) - [j23]Jiawei Jiang, Yi Wei, Yu Liu, Wentao Wu, Chuang Hu, Zhigao Zheng, Ziyi Zhang, Yingxia Shao, Ce Zhang:
How good are machine learning clouds? Benchmarking two snapshots over 5 years. VLDB J. 33(3): 833-857 (2024) - [j22]Lijie Xu, Shuang Qiu, Binhang Yuan, Jiawei Jiang, Cédric Renggli, Shaoduo Gan, Kaan Kara, Guoliang Li, Ji Liu, Wentao Wu, Jieping Ye, Ce Zhang:
Stochastic gradient descent without full data shuffle: with applications to in-database machine learning and deep learning systems. VLDB J. 33(5): 1231-1255 (2024) - [c33]Bojan Karlas, David Dao, Matteo Interlandi, Sebastian Schelter, Wentao Wu, Ce Zhang:
Data Debugging with Shapley Importance over Machine Learning Pipelines. ICLR 2024 - [i22]Lijie Xu, Chulin Xie, Yiran Guo, Gustavo Alonso, Bo Li, Guoliang Li, Wei Wang, Wentao Wu, Ce Zhang:
TablePuppet: A Generic Framework for Relational Federated Learning. CoRR abs/2403.15839 (2024) - [i21]Wentao Wu, Chi Wang:
Budget-aware Query Tuning: An AutoML Perspective. CoRR abs/2404.00137 (2024) - 2023
- [j21]Tarique Siddiqui, Wentao Wu:
ML-Powered Index Tuning: An Overview of Recent Progress and Open Challenges. SIGMOD Rec. 52(4): 19-30 (2023) - [c32]Cédric Renggli, Luka Rimanic, Luka Kolar, Wentao Wu, Ce Zhang:
Automatic Feasibility Study via Data Quality Analysis for ML: A Case-Study on Label Noise. ICDE 2023: 218-231 - [i20]Tarique Siddiqui, Wentao Wu:
ML-Powered Index Tuning: An Overview of Recent Progress and Open Challenges. CoRR abs/2308.13641 (2023) - 2022
- [j20]Tarique Siddiqui, Wentao Wu, Vivek R. Narasayya, Surajit Chaudhuri:
DISTILL: Low-Overhead Data-Driven Techniques for Filtering and Costing Indexes for Scalable Index Tuning. Proc. VLDB Endow. 15(10): 2019-2031 (2022) - [j19]Fotis Psallidas, Yiwen Zhu, Bojan Karlas, Jordan Henkel, Matteo Interlandi, Subru Krishnan, Brian Kroth, K. Venkatesh Emani, Wentao Wu, Ce Zhang, Markus Weimer, Avrilia Floratou, Carlo Curino, Konstantinos Karanasos:
Data Science Through the Looking Glass: Analysis of Millions of GitHub Notebooks and ML.NET Pipelines. SIGMOD Rec. 51(2): 30-37 (2022) - [c31]Wentao Wu, Philip A. Bernstein, Alex Raizman, Christina Pavlopoulou:
Factor Windows: Cost-based Query Rewriting for Optimizing Correlated Window Aggregates. ICDE 2022: 2722-2734 - [c30]Tarique Siddiqui, Saehan Jo, Wentao Wu, Chi Wang, Vivek R. Narasayya, Surajit Chaudhuri:
ISUM: Efficiently Compressing Large and Complex Workloads for Scalable Index Tuning. SIGMOD Conference 2022: 660-673 - [c29]Lijie Xu, Shuang Qiu, Binhang Yuan, Jiawei Jiang, Cédric Renggli, Shaoduo Gan, Kaan Kara, Guoliang Li, Ji Liu, Wentao Wu, Jieping Ye, Ce Zhang:
In-Database Machine Learning with CorgiPile: Stochastic Gradient Descent without Full Data Shuffle. SIGMOD Conference 2022: 1286-1300 - [c28]Wentao Wu, Chi Wang, Tarique Siddiqui, Junxiong Wang, Vivek R. Narasayya, Surajit Chaudhuri, Philip A. Bernstein:
Budget-aware Index Tuning with Reinforcement Learning. SIGMOD Conference 2022: 1528-1541 - [i19]Bojan Karlas, David Dao, Matteo Interlandi, Bo Li, Sebastian Schelter, Wentao Wu, Ce Zhang:
Data Debugging with Shapley Importance over End-to-End Machine Learning Pipelines. CoRR abs/2204.11131 (2022) - [i18]Lijie Xu, Shuang Qiu, Binhang Yuan, Jiawei Jiang, Cédric Renggli, Shaoduo Gan, Kaan Kara, Guoliang Li, Ji Liu, Wentao Wu, Jieping Ye, Ce Zhang:
Stochastic Gradient Descent without Full Data Shuffle. CoRR abs/2206.05830 (2022) - 2021
- [j18]Cédric Renggli, Luka Rimanic, Nezihe Merve Gürel, Bojan Karlas, Wentao Wu, Ce Zhang:
A Data Quality-Driven View of MLOps. IEEE Data Eng. Bull. 44(1): 11-23 (2021) - [j17]Walter Cai, Philip A. Bernstein, Wentao Wu, Badrish Chandramouli:
Optimization of Threshold Functions over Streams. Proc. VLDB Endow. 14(6): 878-889 (2021) - [j16]Yang Li, Yu Shen, Wentao Zhang, Jiawei Jiang, Yaliang Li, Bolin Ding, Jingren Zhou, Zhi Yang, Wentao Wu, Ce Zhang, Bin Cui:
VolcanoML: Speeding up End-to-End AutoML via Scalable Search Space Decomposition. Proc. VLDB Endow. 14(11): 2167-2176 (2021) - [j15]Rahul Potharaju, Terry Kim, Eunjin Song, Wentao Wu, Lev Novik, Apoorve Dave, Pouria Pirzadeh, Andrew Fogarty, Gurleen Dhody, Jiying Li, Vidip Acharya, Sinduja Ramanujam, Nicolas Bruno, César A. Galindo-Legaria, Vivek R. Narasayya, Surajit Chaudhuri, Anil Nori, Tomas Talius, Raghu Ramakrishnan:
Hyperspace: The Indexing Subsystem of Azure Synapse. Proc. VLDB Endow. 14(12): 3043-3055 (2021) - [j14]Yunyan Guo, Zhipeng Zhang, Jiawei Jiang, Wentao Wu, Ce Zhang, Bin Cui, Jianzhong Li:
Model averaging in distributed machine learning: a case study with Apache Spark. VLDB J. 30(4): 693-712 (2021) - [c27]Alekh Jindal, K. Venkatesh Emani, Maureen Daum, Olga Poppe, Brandon Haynes, Anna Pavlenko, Ayushi Gupta, Karthik Ramachandra, Carlo Curino, Andreas Müller, Wentao Wu, Hiren Patel:
Magpie: Python at Speed and Scale using Cloud Backends. CIDR 2021 - [c26]Leonel Aguilar Melgar, David Dao, Shaoduo Gan, Nezihe Merve Gürel, Nora Hollenstein, Jiawei Jiang, Bojan Karlas, Thomas Lemmin, Tian Li, Yang Li, Susie Xi Rao, Johannes Rausch, Cédric Renggli, Luka Rimanic, Maurice Weber, Shuai Zhang, Zhikuan Zhao, Kevin Schawinski, Wentao Wu, Ce Zhang:
Ease.ML: A Lifecycle Management System for Machine Learning. CIDR 2021 - [c25]Yang Li, Yu Shen, Wentao Zhang, Yuanwei Chen, Huaijun Jiang, Mingchao Liu, Jiawei Jiang, Jinyang Gao, Wentao Wu, Zhi Yang, Ce Zhang, Bin Cui:
OpenBox: A Generalized Black-box Optimization Service. KDD 2021: 3209-3219 - [c24]Wentao Wu, Ce Zhang:
Towards understanding end-to-end learning in the context of data: machine learning dancing over semirings & Codd's table. DEEM@SIGMOD 2021: 1:1-1:4 - [c23]Jiawei Jiang, Shaoduo Gan, Yue Liu, Fanlin Wang, Gustavo Alonso, Ana Klimovic, Ankit Singla, Wentao Wu, Ce Zhang:
Towards Demystifying Serverless Machine Learning Training. SIGMOD Conference 2021: 857-871 - [i17]Cédric Renggli, Luka Rimanic, Nezihe Merve Gürel, Bojan Karlas, Wentao Wu, Ce Zhang:
A Data Quality-Driven View of MLOps. CoRR abs/2102.07750 (2021) - [i16]Jiawei Jiang, Shaoduo Gan, Yue Liu, Fanlin Wang, Gustavo Alonso, Ana Klimovic, Ankit Singla, Wentao Wu, Ce Zhang:
Towards Demystifying Serverless Machine Learning Training. CoRR abs/2105.07806 (2021) - [i15]Yang Li, Yu Shen, Wentao Zhang, Yuanwei Chen, Huaijun Jiang, Mingchao Liu, Jiawei Jiang, Jinyang Gao, Wentao Wu, Zhi Yang, Ce Zhang, Bin Cui:
OpenBox: A Generalized Black-box Optimization Service. CoRR abs/2106.00421 (2021) - [i14]Yang Li, Yu Shen, Wentao Zhang, Jiawei Jiang, Bolin Ding, Yaliang Li, Jingren Zhou, Zhi Yang, Wentao Wu, Ce Zhang, Bin Cui:
VolcanoML: Speeding up End-to-End AutoML via Scalable Search Space Decomposition. CoRR abs/2107.08861 (2021) - 2020
- [j13]Cédric Renggli, Luka Rimanic, Luka Kolar, Wentao Wu, Ce Zhang:
Ease.ml/snoopy in Action: Towards Automatic Feasibility Analysis for Machine Learning Application Development. Proc. VLDB Endow. 13(12): 2837-2840 (2020) - [j12]Rahul Potharaju, Terry Kim, Wentao Wu, Vidip Acharya, Steve Suh, Andrew Fogarty, Apoorve Dave, Sinduja Ramanujam, Tomas Talius, Lev Novik, Raghu Ramakrishnan:
Helios: Hyperscale Indexing for the Cloud & Edge. Proc. VLDB Endow. 13(12): 3231-3244 (2020) - [j11]Bojan Karlas, Peng Li, Renzhi Wu, Nezihe Merve Gürel, Xu Chu, Wentao Wu, Ce Zhang:
Nearest Neighbor Classifiers over Incomplete Information: From Certain Answers to Certain Predictions. Proc. VLDB Endow. 14(3): 255-267 (2020) - [c22]Zhipeng Zhang, Wentao Wu, Jiawei Jiang, Lele Yu, Bin Cui, Ce Zhang:
C olumnSGD: A Column-oriented Framework for Distributed Stochastic Gradient Descent. ICDE 2020: 1513-1524 - [c21]Bojan Karlas, Matteo Interlandi, Cédric Renggli, Wentao Wu, Ce Zhang, Deepak Mukunthu Iyappan Babu, Jordan Edwards, Chris Lauren, Andy Xu, Markus Weimer:
Building Continuous Integration Services for Machine Learning. KDD 2020: 2407-2415 - [i13]Wentao Wu:
A Note On Operator-Level Query Execution Cost Modeling. CoRR abs/2003.04410 (2020) - [i12]Bojan Karlas, Peng Li, Renzhi Wu, Nezihe Merve Gürel, Xu Chu, Wentao Wu, Ce Zhang:
Nearest Neighbor Classifiers over Incomplete Information: From Certain Answers to Certain Predictions. CoRR abs/2005.05117 (2020) - [i11]Wentao Wu, Philip A. Bernstein, Alex Raizman, Christina Pavlopoulou:
Cost-based Query Rewriting Techniques for Optimizing Aggregates Over Correlated Windows. CoRR abs/2008.12379 (2020) - [i10]Cédric Renggli, Luka Rimanic, Luka Kolar, Nora Hollenstein, Wentao Wu, Ce Zhang:
On Automatic Feasibility Study for Machine Learning Application Development with ease.ml/snoopy. CoRR abs/2010.08410 (2020)
2010 – 2019
- 2019
- [j10]Cédric Renggli, Frances Ann Hubis, Bojan Karlas, Kevin Schawinski, Wentao Wu, Ce Zhang:
Ease.ml/ci and Ease.ml/meter in Action: Towards Data Management for Statistical Generalization. Proc. VLDB Endow. 12(12): 1962-1965 (2019) - [c20]Philip A. Bernstein, Todd Porter, Rahul Potharaju, Alejandro Z. Tomsic, Shivaram Venkataraman, Wentao Wu:
Serverless Event-Stream Processing over Virtual Actors. CIDR 2019 - [c19]Zhipeng Zhang, Jiawei Jiang, Wentao Wu, Ce Zhang, Lele Yu, Bin Cui:
MLlib*: Fast Training of GLMs Using Spark MLlib. ICDE 2019: 1778-1789 - [c18]Cédric Renggli, Bojan Karlas, Bolin Ding, Feng Liu, Kevin Schawinski, Wentao Wu, Ce Zhang:
Continuous Integration of Machine Learning Models with ease.ml/ci: Towards a Rigorous Yet Practical Treatment. SysML 2019 - [c17]Bailu Ding, Sudipto Das, Ryan Marcus, Wentao Wu, Surajit Chaudhuri, Vivek R. Narasayya:
AI Meets AI: Leveraging Query Executions to Improve Index Recommendations. SIGMOD Conference 2019: 1241-1258 - [i9]Cédric Renggli, Bojan Karlas, Bolin Ding, Feng Liu, Kevin Schawinski, Wentao Wu, Ce Zhang:
Continuous Integration of Machine Learning Models with ease.ml/ci: Towards a Rigorous Yet Practical Treatment. CoRR abs/1903.00278 (2019) - [i8]Frances Ann Hubis, Wentao Wu, Ce Zhang:
Quantitative Overfitting Management for Human-in-the-loop ML Application Development with ease.ml/meter. CoRR abs/1906.00299 (2019) - [i7]Fotis Psallidas, Yiwen Zhu, Bojan Karlas, Matteo Interlandi, Avrilia Floratou, Konstantinos Karanasos, Wentao Wu, Ce Zhang, Subru Krishnan, Carlo Curino, Markus Weimer:
Data Science through the looking glass and what we found there. CoRR abs/1912.09536 (2019) - 2018
- [j9]Tian Li, Jie Zhong, Ji Liu, Wentao Wu, Ce Zhang:
Ease.ml: Towards Multi-tenant Resource Sharing for Machine Learning Workloads. Proc. VLDB Endow. 11(5): 607-620 (2018) - [j8]Bailu Ding, Sudipto Das, Wentao Wu, Surajit Chaudhuri, Vivek R. Narasayya:
Plan Stitch: Harnessing the Best of Many Plans. Proc. VLDB Endow. 11(10): 1123-1136 (2018) - [j7]Yu Liu, Hantian Zhang, Luyuan Zeng, Wentao Wu, Ce Zhang:
MLBench: Benchmarking Machine Learning Services Against Human Experts. Proc. VLDB Endow. 11(10): 1220-1232 (2018) - [j6]Bojan Karlas, Ji Liu, Wentao Wu, Ce Zhang:
Ease.ml in Action: Towards Multi-tenant Declarative Learning Services. Proc. VLDB Endow. 11(12): 2054-2057 (2018) - 2017
- [j5]Xupeng Li, Bin Cui, Yiru Chen, Wentao Wu, Ce Zhang:
MLog: Towards Declarative In-Database Machine Learning. Proc. VLDB Endow. 10(12): 1933-1936 (2017) - [j4]Wentao Wu, Hongsong Li, Haixun Wang, Kenny Q. Zhu:
Semantic Bootstrapping: A Theoretical Perspective. IEEE Trans. Knowl. Data Eng. 29(2): 446-457 (2017) - [c16]Hantian Zhang, Luyuan Zeng, Wentao Wu, Ce Zhang:
How good are machine learning clouds for binary classification with good features?: extended abstract. SoCC 2017: 649 - [c15]Fatemah Panahi, Wentao Wu, AnHai Doan, Jeffrey F. Naughton:
Towards Interactive Debugging of Rule-based Entity Matching. EDBT 2017: 354-365 - [c14]Wentao Wu, Hongsong Li, Haixun Wang, Kenny Q. Zhu:
Semantic Bootstrapping: A Theoretical Perspective. ICDE 2017: 7-8 - [c13]Ce Zhang, Wentao Wu, Tian Li:
An Overreaction to the Broken Machine Learning Abstraction: The ease.ml Vision. HILDA@SIGMOD 2017: 3:1-3:6 - [i6]Hantian Zhang, Luyuan Zeng, Wentao Wu, Ce Zhang:
How Good Are Machine Learning Clouds for Binary Classification with Good Features? CoRR abs/1707.09562 (2017) - [i5]Tian Li, Jie Zhong, Ji Liu, Wentao Wu, Ce Zhang:
Ease.ml: Towards Multi-tenant Resource Sharing for Machine Learning Workloads. CoRR abs/1708.07308 (2017) - 2016
- [c12]Wentao Wu, Jeffrey F. Naughton, Harneet Singh:
Sampling-Based Query Re-Optimization. SIGMOD Conference 2016: 1721-1736 - [i4]Wentao Wu, Jeffrey F. Naughton, Harneet Singh:
Sampling-Based Query Re-Optimization. CoRR abs/1601.05748 (2016) - 2015
- [c11]Akanksha Baid, Wentao Wu, Chong Sun, AnHai Doan, Jeffrey F. Naughton:
On Debugging Non-Answers in Keyword Search Systems. EDBT 2015: 37-48 - [i3]Xi Wu, Matthew Fredrikson, Wentao Wu, Somesh Jha, Jeffrey F. Naughton:
Revisiting Differentially Private Regression: Lessons From Learning Theory and their Consequences. CoRR abs/1512.06388 (2015) - 2014
- [j3]Wentao Wu, Xi Wu, Hakan Hacigümüs, Jeffrey F. Naughton:
Uncertainty Aware Query Execution Time Prediction. Proc. VLDB Endow. 7(14): 1857-1868 (2014) - [i2]Wentao Wu, Xi Wu, Hakan Hacigümüs, Jeffrey F. Naughton:
Uncertainty Aware Query Execution Time Prediction. CoRR abs/1408.6589 (2014) - 2013
- [j2]Wentao Wu, Yun Chi, Hakan Hacigümüs, Jeffrey F. Naughton:
Towards Predicting Query Execution Time for Concurrent and Dynamic Database Workloads. Proc. VLDB Endow. 6(10): 925-936 (2013) - [c10]Wentao Wu, Yun Chi, Shenghuo Zhu, Jun'ichi Tatemura, Hakan Hacigümüs, Jeffrey F. Naughton:
Predicting query execution time: Are optimizer cost models really unusable? ICDE 2013: 1081-1092 - 2012
- [c9]Jidong Chen, Wentao Wu, Hang Guo, Wei Wang:
Context-aware Search for Personal Information Management Systems. SDM 2012: 708-719 - [c8]Wentao Wu, Hongsong Li, Haixun Wang, Kenny Qili Zhu:
Probase: a probabilistic taxonomy for text understanding. SIGMOD Conference 2012: 481-492 - 2011
- [c7]Jidong Chen, Hang Guo, Wentao Wu, Wei Wang:
iMecho: a context-aware desktop search system. SIGIR 2011: 1269-1270 - 2010
- [c6]Wentao Wu, Yanghua Xiao, Wei Wang, Zhenying He, Zhihui Wang:
k-symmetry model for identity anonymization in social networks. EDBT 2010: 111-122
2000 – 2009
- 2009
- [c5]Hang Guo, Jidong Chen, Wentao Wu, Wei Wang:
Personalization as a service: the architecture and a case study. CloudDB@CIKM 2009: 1-8 - [c4]Jidong Chen, Hang Guo, Wentao Wu, Wei Wang:
iMecho: an associative memory based desktop search system. CIKM 2009: 731-740 - [c3]Yanghua Xiao, Wentao Wu, Jian Pei, Wei Wang, Zhenying He:
Efficiently indexing shortest paths by exploiting symmetry in graphs. EDBT 2009: 493-504 - [c2]Jidong Chen, Hang Guo, Wentao Wu, Chunxin Xie:
Search your memory ! - an associative memory based desktop search system. SIGMOD Conference 2009: 1099-1102 - 2008
- [j1]Yanghua Xiao, Hua Dong, Wentao Wu, Momiao Xiong, Wei Wang, Baile Shi:
Structure-based graph distance measures of high degree of precision. Pattern Recognit. 41(12): 3547-3561 (2008) - [c1]Yanghua Xiao, Wentao Wu, Wei Wang, Zhenying He:
Efficient Algorithms for Node Disjoint Subgraph Homeomorphism Determination. DASFAA 2008: 452-460 - 2007
- [i1]Yanghua Xiao, Wentao Wu, Wei Wang, Zhenying He:
Efficient Algorithms for Node Disjoint Subgraph Homeomorphism Determination. CoRR abs/0709.1227 (2007)
Coauthor Index
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