Wentao Wu

According to our database, Wentao Wu authored at least 69 papers between 2008 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of four.

2024

Stochastic gradient descent without full data shuffle: with applications to in-database machine learning and deep learning systems.

Lijie Xu, Shuang Qiu, Binhang Yuan, Jiawei Jiang, Cédric Renggli, Shaoduo Gan, Kaan Kara, Guoliang Li, Ji Liu, Wentao Wu, Jieping Ye, Ce Zhang

VLDB J., September, 2024

Budget-aware Query Tuning: An AutoML Perspective.

Wentao Wu, Chi Wang

SIGMOD Rec., September, 2024

How good are machine learning clouds? Benchmarking two snapshots over 5 years.

Jiawei Jiang, Yi Wei, Yu Liu, Wentao Wu, Chuang Hu, Zhigao Zheng, Ziyi Zhang, Yingxia Shao, Ce Zhang

VLDB J., May, 2024

Wred: Workload Reduction for Scalable Index Tuning.

Matteo Brucato, Tarique Siddiqui, Wentao Wu, Vivek R. Narasayya, Surajit Chaudhuri

Proc. ACM Manag. Data, February, 2024

A systematic evaluation of machine learning on serverless infrastructure.

Jiawei Jiang, Shaoduo Gan, Bo Du, Gustavo Alonso, Ana Klimovic, Ankit Singla, Wentao Wu, Sheng Wang, Ce Zhang

VLDB J., 2024

Wii: Dynamic Budget Reallocation In Index Tuning.

Xiaoying Wang, Wentao Wu, Chi Wang, Vivek R. Narasayya, Surajit Chaudhuri

Proc. ACM Manag. Data, 2024

TablePuppet: A Generic Framework for Relational Federated Learning.

Lijie Xu, Chulin Xie, Yiran Guo, Gustavo Alonso, Bo Li, Guoliang Li, Wei Wang, Wentao Wu, Ce Zhang

CoRR, 2024

Data Debugging with Shapley Importance over Machine Learning Pipelines.

Bojan Karlas, David Dao, Matteo Interlandi, Sebastian Schelter, Wentao Wu, Ce Zhang

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

ML-Powered Index Tuning: An Overview of Recent Progress and Open Challenges.

Tarique Siddiqui, Wentao Wu

SIGMOD Rec., December, 2023

Automatic Feasibility Study via Data Quality Analysis for ML: A Case-Study on Label Noise.

Cédric Renggli, Luka Rimanic, Luka Kolar, Wentao Wu, Ce Zhang

Proceedings of the 39th IEEE International Conference on Data Engineering, 2023

2022

Data Science Through the Looking Glass: Analysis of Millions of GitHub Notebooks and ML.NET Pipelines.

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

SIGMOD Rec., 2022

DISTILL: Low-Overhead Data-Driven Techniques for Filtering and Costing Indexes for Scalable Index Tuning.

Tarique Siddiqui, Wentao Wu, Vivek R. Narasayya, Surajit Chaudhuri

Proc. VLDB Endow., 2022

Stochastic Gradient Descent without Full Data Shuffle.

Lijie Xu, Shuang Qiu, Binhang Yuan, Jiawei Jiang, Cédric Renggli, Shaoduo Gan, Kaan Kara, Guoliang Li, Ji Liu, Wentao Wu, Jieping Ye, Ce Zhang

CoRR, 2022

Data Debugging with Shapley Importance over End-to-End Machine Learning Pipelines.

Bojan Karlas, David Dao, Matteo Interlandi, Bo Li, Sebastian Schelter, Wentao Wu, Ce Zhang

CoRR, 2022

In-Database Machine Learning with CorgiPile: Stochastic Gradient Descent without Full Data Shuffle.

Lijie Xu, Shuang Qiu, Binhang Yuan, Jiawei Jiang, Cédric Renggli, Shaoduo Gan, Kaan Kara, Guoliang Li, Ji Liu, Wentao Wu, Jieping Ye, Ce Zhang

Proceedings of the SIGMOD '22: International Conference on Management of Data, Philadelphia, PA, USA, June 12, 2022

ISUM: Efficiently Compressing Large and Complex Workloads for Scalable Index Tuning.

Tarique Siddiqui, Saehan Jo, Wentao Wu, Chi Wang, Vivek R. Narasayya, Surajit Chaudhuri

Proceedings of the SIGMOD '22: International Conference on Management of Data, Philadelphia, PA, USA, June 12, 2022

Budget-aware Index Tuning with Reinforcement Learning.

Wentao Wu, Chi Wang, Tarique Siddiqui, Junxiong Wang, Vivek R. Narasayya, Surajit Chaudhuri, Philip A. Bernstein

Proceedings of the SIGMOD '22: International Conference on Management of Data, Philadelphia, PA, USA, June 12, 2022

Factor Windows: Cost-based Query Rewriting for Optimizing Correlated Window Aggregates.

Wentao Wu, Philip A. Bernstein, Alex Raizman, Christina Pavlopoulou

Proceedings of the 38th IEEE International Conference on Data Engineering, 2022

2021

Model averaging in distributed machine learning: a case study with Apache Spark.

Yunyan Guo, Zhipeng Zhang, Jiawei Jiang, Wentao Wu, Ce Zhang, Bin Cui, Jianzhong Li

VLDB J., 2021

Hyperspace: The Indexing Subsystem of Azure Synapse.

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

Proc. VLDB Endow., 2021

VolcanoML: Speeding up End-to-End AutoML via Scalable Search Space Decomposition.

Yang Li, Yu Shen, Wentao Zhang, Jiawei Jiang, Yaliang Li, Bolin Ding, Jingren Zhou, Zhi Yang, Wentao Wu, Ce Zhang, Bin Cui

Proc. VLDB Endow., 2021

Optimization of Threshold Functions over Streams.

Walter Cai, Philip A. Bernstein, Wentao Wu, Badrish Chandramouli

Proc. VLDB Endow., 2021

A Data Quality-Driven View of MLOps.

Cédric Renggli, Luka Rimanic, Nezihe Merve Gürel, Bojan Karlas, Wentao Wu, Ce Zhang

IEEE Data Eng. Bull., 2021

Towards Demystifying Serverless Machine Learning Training.

Jiawei Jiang, Shaoduo Gan, Yue Liu, Fanlin Wang, Gustavo Alonso, Ana Klimovic, Ankit Singla, Wentao Wu, Ce Zhang

Proceedings of the SIGMOD '21: International Conference on Management of Data, 2021

Towards understanding end-to-end learning in the context of data: machine learning dancing over semirings & Codd's table.

Wentao Wu, Ce Zhang

Proceedings of the Fifth Workshop on Data Management for End-To-End Machine Learning, 2021

OpenBox: A Generalized Black-box Optimization Service.

Yang Li, Yu Shen, Wentao Zhang, Yuanwei Chen, Huaijun Jiang, Mingchao Liu, Jiawei Jiang, Jinyang Gao, Wentao Wu, Zhi Yang, Ce Zhang, Bin Cui

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Ease.ML: A Lifecycle Management System for Machine Learning.

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

Proceedings of the 11th Conference on Innovative Data Systems Research, 2021

Magpie: Python at Speed and Scale using Cloud Backends.

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

Proceedings of the 11th Conference on Innovative Data Systems Research, 2021

2020

Ease.ml/snoopy in Action: Towards Automatic Feasibility Analysis for Machine Learning Application Development.

Cédric Renggli, Luka Rimanic, Luka Kolar, Wentao Wu, Ce Zhang

Proc. VLDB Endow., 2020

Helios: Hyperscale Indexing for the Cloud & Edge.

Rahul Potharaju, Terry Kim, Wentao Wu, Vidip Acharya, Steve Suh, Andrew Fogarty, Apoorve Dave, Sinduja Ramanujam, Tomas Talius, Lev Novik, Raghu Ramakrishnan

Proc. VLDB Endow., 2020

Nearest Neighbor Classifiers over Incomplete Information: From Certain Answers to Certain Predictions.

Bojan Karlas, Peng Li, Renzhi Wu, Nezihe Merve Gürel, Xu Chu, Wentao Wu, Ce Zhang

Proc. VLDB Endow., 2020

On Automatic Feasibility Study for Machine Learning Application Development with ease.ml/snoopy.

Cédric Renggli, Luka Rimanic, Luka Kolar, Nora Hollenstein, Wentao Wu, Ce Zhang

CoRR, 2020

Cost-based Query Rewriting Techniques for Optimizing Aggregates Over Correlated Windows.

Wentao Wu, Philip A. Bernstein, Alex Raizman, Christina Pavlopoulou

CoRR, 2020

A Note On Operator-Level Query Execution Cost Modeling.

Wentao Wu

CoRR, 2020

Building Continuous Integration Services for Machine Learning.

Bojan Karlas, Matteo Interlandi, Cédric Renggli, Wentao Wu, Ce Zhang, Deepak Mukunthu Iyappan Babu, Jordan Edwards, Chris Lauren, Andy Xu, Markus Weimer

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

C olumnSGD: A Column-oriented Framework for Distributed Stochastic Gradient Descent.

Zhipeng Zhang, Wentao Wu, Jiawei Jiang, Lele Yu, Bin Cui, Ce Zhang

Proceedings of the 36th IEEE International Conference on Data Engineering, 2020

2019

Ease.ml/ci and Ease.ml/meter in Action: Towards Data Management for Statistical Generalization.

Cédric Renggli, Frances Ann Hubis, Bojan Karlas, Kevin Schawinski, Wentao Wu, Ce Zhang

Proc. VLDB Endow., 2019

Data Science through the looking glass and what we found there.

Fotis Psallidas, Yiwen Zhu, Bojan Karlas, Matteo Interlandi, Avrilia Floratou, Konstantinos Karanasos, Wentao Wu, Ce Zhang, Subru Krishnan, Carlo Curino, Markus Weimer

CoRR, 2019

Quantitative Overfitting Management for Human-in-the-loop ML Application Development with ease.ml/meter.

Frances Ann Hubis, Wentao Wu, Ce Zhang

CoRR, 2019

AI Meets AI: Leveraging Query Executions to Improve Index Recommendations.

Bailu Ding, Sudipto Das, Ryan Marcus, Wentao Wu, Surajit Chaudhuri, Vivek R. Narasayya

Proceedings of the 2019 International Conference on Management of Data, 2019

Continuous Integration of Machine Learning Models with ease.ml/ci: Towards a Rigorous Yet Practical Treatment.

Cédric Renggli, Bojan Karlas, Bolin Ding, Feng Liu, Kevin Schawinski, Wentao Wu, Ce Zhang

Proceedings of the Second Conference on Machine Learning and Systems, SysML 2019, 2019

MLlib*: Fast Training of GLMs Using Spark MLlib.

Zhipeng Zhang, Jiawei Jiang, Wentao Wu, Ce Zhang, Lele Yu, Bin Cui

Proceedings of the 35th IEEE International Conference on Data Engineering, 2019

Serverless Event-Stream Processing over Virtual Actors.

Philip A. Bernstein, Todd Porter, Rahul Potharaju, Alejandro Z. Tomsic, Shivaram Venkataraman, Wentao Wu

Proceedings of the 9th Biennial Conference on Innovative Data Systems Research, 2019

2018

MLBench: Benchmarking Machine Learning Services Against Human Experts.

Yu Liu, Hantian Zhang, Luyuan Zeng, Wentao Wu, Ce Zhang

Proc. VLDB Endow., 2018

Ease.ml: Towards Multi-tenant Resource Sharing for Machine Learning Workloads.

Tian Li, Jie Zhong, Ji Liu, Wentao Wu, Ce Zhang

Proc. VLDB Endow., 2018

Ease.ml in Action: Towards Multi-tenant Declarative Learning Services.

Bojan Karlas, Ji Liu, Wentao Wu, Ce Zhang

Proc. VLDB Endow., 2018

Plan Stitch: Harnessing the Best of Many Plans.

Bailu Ding, Sudipto Das, Wentao Wu, Surajit Chaudhuri, Vivek R. Narasayya

Proc. VLDB Endow., 2018

2017

Semantic Bootstrapping: A Theoretical Perspective.

Wentao Wu, Hongsong Li, Haixun Wang, Kenny Q. Zhu

IEEE Trans. Knowl. Data Eng., 2017

MLog: Towards Declarative In-Database Machine Learning.

Xupeng Li, Bin Cui, Yiru Chen, Wentao Wu, Ce Zhang

Proc. VLDB Endow., 2017

How Good Are Machine Learning Clouds for Binary Classification with Good Features?

Hantian Zhang, Luyuan Zeng, Wentao Wu, Ce Zhang

CoRR, 2017

An Overreaction to the Broken Machine Learning Abstraction: The ease.ml Vision.

Ce Zhang, Wentao Wu, Tian Li

Proceedings of the 2nd Workshop on Human-In-the-Loop Data Analytics, 2017

Towards Interactive Debugging of Rule-based Entity Matching.

Fatemah Panahi, Wentao Wu, AnHai Doan, Jeffrey F. Naughton

Proceedings of the 20th International Conference on Extending Database Technology, 2017

How good are machine learning clouds for binary classification with good features?: extended abstract.

Hantian Zhang, Luyuan Zeng, Wentao Wu, Ce Zhang

Proceedings of the 2017 Symposium on Cloud Computing, SoCC 2017, Santa Clara, CA, USA, 2017

2016

Sampling-Based Query Re-Optimization.

Wentao Wu, Jeffrey F. Naughton, Harneet Singh

Proceedings of the 2016 International Conference on Management of Data, 2016

2015

Revisiting Differentially Private Regression: Lessons From Learning Theory and their Consequences.

Xi Wu, Matthew Fredrikson, Wentao Wu, Somesh Jha, Jeffrey F. Naughton

CoRR, 2015

On Debugging Non-Answers in Keyword Search Systems.

Akanksha Baid, Wentao Wu, Chong Sun, AnHai Doan, Jeffrey F. Naughton

Proceedings of the 18th International Conference on Extending Database Technology, 2015

2014

Uncertainty Aware Query Execution Time Prediction.

Wentao Wu, Xi Wu, Hakan Hacigümüs, Jeffrey F. Naughton

Proc. VLDB Endow., 2014

2013

Towards Predicting Query Execution Time for Concurrent and Dynamic Database Workloads.

Wentao Wu, Yun Chi, Hakan Hacigümüs, Jeffrey F. Naughton

Proc. VLDB Endow., 2013

Predicting query execution time: Are optimizer cost models really unusable?

Wentao Wu, Yun Chi, Shenghuo Zhu, Jun'ichi Tatemura, Hakan Hacigümüs, Jeffrey F. Naughton

Proceedings of the 29th IEEE International Conference on Data Engineering, 2013

2012

Probase: a probabilistic taxonomy for text understanding.

Wentao Wu, Hongsong Li, Haixun Wang, Kenny Qili Zhu

Proceedings of the ACM SIGMOD International Conference on Management of Data, 2012

Context-aware Search for Personal Information Management Systems.

Jidong Chen, Wentao Wu, Hang Guo, Wei Wang

Proceedings of the Twelfth SIAM International Conference on Data Mining, 2012

2011

iMecho: a context-aware desktop search system.

Jidong Chen, Hang Guo, Wentao Wu, Wei Wang

Proceedings of the Proceeding of the 34th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2011

2010

k-symmetry model for identity anonymization in social networks.

Wentao Wu, Yanghua Xiao, Wei Wang, Zhenying He, Zhihui Wang

Proceedings of the EDBT 2010, 2010

2009

Search your memory ! - an associative memory based desktop search system.

Jidong Chen, Hang Guo, Wentao Wu, Chunxin Xie

Proceedings of the ACM SIGMOD International Conference on Management of Data, 2009

Efficiently indexing shortest paths by exploiting symmetry in graphs.

Yanghua Xiao, Wentao Wu, Jian Pei, Wei Wang, Zhenying He

Proceedings of the EDBT 2009, 2009

Personalization as a service: the architecture and a case study.

Hang Guo, Jidong Chen, Wentao Wu, Wei Wang

Proceedings of the First International CIKM Workshop on Cloud Data Management, 2009

iMecho: an associative memory based desktop search system.

Jidong Chen, Hang Guo, Wentao Wu, Wei Wang

Proceedings of the 18th ACM Conference on Information and Knowledge Management, 2009

2008

Structure-based graph distance measures of high degree of precision.

Yanghua Xiao, Hua Dong, Wentao Wu, Momiao Xiong, Wei Wang, Baile Shi

Pattern Recognit., 2008

Efficient Algorithms for Node Disjoint Subgraph Homeomorphism Determination.

Yanghua Xiao, Wentao Wu, Wei Wang, Zhenying He

Proceedings of the Database Systems for Advanced Applications, 2008