Efficient Algorithms for Node Disjoint Subgraph Homeomorphism Determination. - Yanghua Xiao; Wentao Wu 001; Wei Wang 009; Zhenying He (DASFAA, 2008)

Structure-based graph distance measures of high degree of precision. - Yanghua Xiao; Hua Dong; Wentao Wu 001; Momiao Xiong; Wei Wang 009; Baile Shi (Pattern Recognit., 2008)

iMecho: an associative memory based desktop search system. - Jidong Chen; Hang Guo; Wentao Wu 001; Wei Wang 009 (CIKM, 2009)

Personalization as a service: the architecture and a case study. - Hang Guo; Jidong Chen; Wentao Wu 001; Wei Wang 009 (CloudDB@CIKM, 2009)

Efficiently indexing shortest paths by exploiting symmetry in graphs. - Yanghua Xiao; Wentao Wu 001; Jian Pei 001; Wei Wang 009; Zhenying He (EDBT, 2009)

Search your memory ! - an associative memory based desktop search system. - Jidong Chen; Hang Guo; Wentao Wu 001; Chunxin Xie (SIGMOD Conference, 2009)

k-symmetry model for identity anonymization in social networks. - Wentao Wu 001; Yanghua Xiao; Wei Wang 009; Zhenying He; Zhihui Wang 009 (EDBT, 2010)

iMecho: a context-aware desktop search system. - Jidong Chen; Hang Guo; Wentao Wu 001; Wei Wang 009 (SIGIR, 2011)

Context-aware Search for Personal Information Management Systems. - Jidong Chen; Wentao Wu 001; Hang Guo; Wei Wang 009 (SDM, 2012)

Probase: a probabilistic taxonomy for text understanding. - Wentao Wu 001; Hongsong Li; Haixun Wang; Kenny Qili Zhu (SIGMOD Conference, 2012)

Predicting query execution time: Are optimizer cost models really unusable? - Wentao Wu 001; Yun Chi; Shenghuo Zhu; Jun'ichi Tatemura; Hakan Hacigümüs; Jeffrey F. Naughton (ICDE, 2013)

Towards Predicting Query Execution Time for Concurrent and Dynamic Database Workloads. - Wentao Wu 001; Yun Chi; Hakan Hacigümüs; Jeffrey F. Naughton (Proc. VLDB Endow., 2013)

Uncertainty Aware Query Execution Time Prediction. - Wentao Wu 001; Xi Wu 001; Hakan Hacigümüs; Jeffrey F. Naughton (Proc. VLDB Endow., 2014)

On Debugging Non-Answers in Keyword Search Systems. - Akanksha Baid; Wentao Wu 001; Chong Sun; AnHai Doan; Jeffrey F. Naughton (EDBT, 2015)

Revisiting Differentially Private Regression: Lessons From Learning Theory and their Consequences. - Xi Wu 001; Matthew Fredrikson; Wentao Wu 001; Somesh Jha; Jeffrey F. Naughton (CoRR, 2015)

Sampling-Based Query Re-Optimization. - Wentao Wu 001; Jeffrey F. Naughton; Harneet Singh (SIGMOD Conference, 2016)

How good are machine learning clouds for binary classification with good features?: extended abstract. - Hantian Zhang; Luyuan Zeng; Wentao Wu 001; Ce Zhang 001 (SoCC, 2017)

Towards Interactive Debugging of Rule-based Entity Matching. - Fatemah Panahi; Wentao Wu 001; AnHai Doan; Jeffrey F. Naughton (EDBT, 2017)

An Overreaction to the Broken Machine Learning Abstraction: The ease.ml Vision. - Ce Zhang 001; Wentao Wu 001; Tian Li 005 (HILDA@SIGMOD, 2017)

How Good Are Machine Learning Clouds for Binary Classification with Good Features? - Hantian Zhang; Luyuan Zeng; Wentao Wu 001; Ce Zhang 001 (CoRR, 2017)

MLog: Towards Declarative In-Database Machine Learning. - Xupeng Li; Bin Cui 001; Yiru Chen; Wentao Wu 001; Ce Zhang 001 (Proc. VLDB Endow., 2017)

Semantic Bootstrapping: A Theoretical Perspective. - Wentao Wu 001; Hongsong Li; Haixun Wang; Kenny Q. Zhu (IEEE Trans. Knowl. Data Eng., 2017)

Plan Stitch: Harnessing the Best of Many Plans. - Bailu Ding; Sudipto Das; Wentao Wu 001; Surajit Chaudhuri; Vivek R. Narasayya (Proc. VLDB Endow., 2018)

Ease.ml in Action: Towards Multi-tenant Declarative Learning Services. - Bojan Karlas; Ji Liu 002; Wentao Wu 001; Ce Zhang 001 (Proc. VLDB Endow., 2018)

Ease.ml: Towards Multi-tenant Resource Sharing for Machine Learning Workloads. - Tian Li 005; Jie Zhong; Ji Liu 002; Wentao Wu 001; Ce Zhang 001 (Proc. VLDB Endow., 2018)

MLBench: Benchmarking Machine Learning Services Against Human Experts. - Yu Liu 075; Hantian Zhang; Luyuan Zeng; Wentao Wu 001; Ce Zhang 001 (Proc. VLDB Endow., 2018)

Serverless Event-Stream Processing over Virtual Actors. - Philip A. Bernstein; Todd Porter; Rahul Potharaju; Alejandro Z. Tomsic; Shivaram Venkataraman; Wentao Wu 001 (CIDR, 2019)

MLlib*: Fast Training of GLMs Using Spark MLlib. - Zhipeng Zhang; Jiawei Jiang 001; Wentao Wu 001; Ce Zhang 001; Lele Yu; Bin Cui 001 (ICDE, 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 001; Ce Zhang 001 (SysML, 2019)

AI Meets AI: Leveraging Query Executions to Improve Index Recommendations. - Bailu Ding; Sudipto Das; Ryan Marcus; Wentao Wu 001; Surajit Chaudhuri; Vivek R. Narasayya (SIGMOD Conference, 2019)

Quantitative Overfitting Management for Human-in-the-loop ML Application Development with ease.ml/meter. - Frances Ann Hubis; Wentao Wu 001; Ce Zhang 001 (CoRR, 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 001; Ce Zhang 001; Subru Krishnan; Carlo Curino; Markus Weimer (CoRR, 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 001; Ce Zhang 001 (Proc. VLDB Endow., 2019)

C olumnSGD: A Column-oriented Framework for Distributed Stochastic Gradient Descent. - Zhipeng Zhang; Wentao Wu 001; Jiawei Jiang 001; Lele Yu; Bin Cui 001; Ce Zhang 001 (ICDE, 2020)

Building Continuous Integration Services for Machine Learning. - Bojan Karlas; Matteo Interlandi; Cédric Renggli; Wentao Wu 001; Ce Zhang 001; Deepak Mukunthu Iyappan Babu; Jordan Edwards; Chris Lauren; Andy Xu; Markus Weimer (KDD, 2020)

A Note On Operator-Level Query Execution Cost Modeling. - Wentao Wu 001 (CoRR, 2020)

Cost-based Query Rewriting Techniques for Optimizing Aggregates Over Correlated Windows. - Wentao Wu 001; Philip A. Bernstein; Alex Raizman; Christina Pavlopoulou (CoRR, 2020)

On Automatic Feasibility Study for Machine Learning Application Development with ease.ml/snoopy. - Cédric Renggli; Luka Rimanic; Luka Kolar; Nora Hollenstein; Wentao Wu 001; Ce Zhang 001 (CoRR, 2020)

Nearest Neighbor Classifiers over Incomplete Information: From Certain Answers to Certain Predictions. - Bojan Karlas; Peng Li 062; Renzhi Wu; Nezihe Merve Gürel; Xu Chu 002; Wentao Wu 001; Ce Zhang 001 (Proc. VLDB Endow., 2020)

Helios: Hyperscale Indexing for the Cloud & Edge. - Rahul Potharaju; Terry Kim; Wentao Wu 001; Vidip Acharya; Steve Suh; Andrew Fogarty; Apoorve Dave; Sinduja Ramanujam; Tomas Talius; Lev Novik; Raghu Ramakrishnan 001 (Proc. VLDB Endow., 2020)

Ease.ml/snoopy in Action: Towards Automatic Feasibility Analysis for Machine Learning Application Development. - Cédric Renggli; Luka Rimanic; Luka Kolar; Wentao Wu 001; Ce Zhang 001 (Proc. VLDB Endow., 2020)

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 002; Carlo Curino; Andreas Müller 024; Wentao Wu 001; Hiren Patel (CIDR, 2021)

Ease.ML: A Lifecycle Management System for Machine Learning. - Leonel Aguilar Melgar; David Dao; Shaoduo Gan; Nezihe Merve Gürel; Nora Hollenstein; Jiawei Jiang 001; Bojan Karlas; Thomas Lemmin; Tian Li 005; Yang Li 106; Susie Xi Rao; Johannes Rausch; et al. (CIDR, 2021)

OpenBox: A Generalized Black-box Optimization Service. - Yang Li 106; Yu Shen 003; Wentao Zhang 001; Yuanwei Chen; Huaijun Jiang; Mingchao Liu; Jiawei Jiang 001; Jinyang Gao; Wentao Wu 001; Zhi Yang 001; Ce Zhang 001; Bin Cui 001 (KDD, 2021)

Towards understanding end-to-end learning in the context of data: machine learning dancing over semirings & Codd's table. - Wentao Wu 001; Ce Zhang 001 (DEEM@SIGMOD, 2021)

Towards Demystifying Serverless Machine Learning Training. - Jiawei Jiang 001; Shaoduo Gan; Yue Liu; Fanlin Wang; Gustavo Alonso; Ana Klimovic; Ankit Singla; Wentao Wu 001; Ce Zhang 001 (SIGMOD Conference, 2021)

A Data Quality-Driven View of MLOps. - Cédric Renggli; Luka Rimanic; Nezihe Merve Gürel; Bojan Karlas; Wentao Wu 001; Ce Zhang 001 (IEEE Data Eng. Bull., 2021)

Optimization of Threshold Functions over Streams. - Walter Cai; Philip A. Bernstein; Wentao Wu 001; Badrish Chandramouli (Proc. VLDB Endow., 2021)

VolcanoML: Speeding up End-to-End AutoML via Scalable Search Space Decomposition. - Yang Li 106; Yu Shen 003; Wentao Zhang 001; Jiawei Jiang 001; Yaliang Li; Bolin Ding; Jingren Zhou 001; Zhi Yang 001; Wentao Wu 001; Ce Zhang 001; Bin Cui 001 (Proc. VLDB Endow., 2021)

Hyperspace: The Indexing Subsystem of Azure Synapse. - Rahul Potharaju; Terry Kim; Eunjin Song; Wentao Wu 001; Lev Novik; Apoorve Dave; Pouria Pirzadeh; Andrew Fogarty; Gurleen Dhody; Jiying Li; Vidip Acharya; Sinduja Ramanujam; et al. (Proc. VLDB Endow., 2021)

Model averaging in distributed machine learning: a case study with Apache Spark. - Yunyan Guo; Zhipeng Zhang; Jiawei Jiang 001; Wentao Wu 001; Ce Zhang 001; Bin Cui 001; Jianzhong Li (VLDB J., 2021)

Factor Windows: Cost-based Query Rewriting for Optimizing Correlated Window Aggregates. - Wentao Wu 001; Philip A. Bernstein; Alex Raizman; Christina Pavlopoulou (ICDE, 2022)

Budget-aware Index Tuning with Reinforcement Learning. - Wentao Wu 001; Chi Wang 001; Tarique Siddiqui; Junxiong Wang; Vivek R. Narasayya; Surajit Chaudhuri; Philip A. Bernstein (SIGMOD Conference, 2022)

ISUM: Efficiently Compressing Large and Complex Workloads for Scalable Index Tuning. - Tarique Siddiqui; Saehan Jo; Wentao Wu 001; Chi Wang 001; Vivek R. Narasayya; Surajit Chaudhuri (SIGMOD Conference, 2022)

In-Database Machine Learning with CorgiPile: Stochastic Gradient Descent without Full Data Shuffle. - Lijie Xu; Shuang Qiu; Binhang Yuan; Jiawei Jiang 001; Cédric Renggli; Shaoduo Gan; Kaan Kara; Guoliang Li 001; Ji Liu 002; Wentao Wu 001; Jieping Ye; Ce Zhang 001 (SIGMOD Conference, 2022)

Data Debugging with Shapley Importance over End-to-End Machine Learning Pipelines. - Bojan Karlas; David Dao; Matteo Interlandi; Bo Li 026; Sebastian Schelter; Wentao Wu 001; Ce Zhang 001 (CoRR, 2022)

Stochastic Gradient Descent without Full Data Shuffle. - Lijie Xu; Shuang Qiu; Binhang Yuan; Jiawei Jiang 001; Cédric Renggli; Shaoduo Gan; Kaan Kara; Guoliang Li 001; Ji Liu 002; Wentao Wu 001; Jieping Ye; Ce Zhang 001 (CoRR, 2022)

DISTILL: Low-Overhead Data-Driven Techniques for Filtering and Costing Indexes for Scalable Index Tuning. - Tarique Siddiqui; Wentao Wu 001; Vivek R. Narasayya; Surajit Chaudhuri (Proc. VLDB Endow., 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 001; Ce Zhang 001; Markus Weimer; Avrilia Floratou; et al. (SIGMOD Rec., 2022)

Automatic Feasibility Study via Data Quality Analysis for ML: A Case-Study on Label Noise. - Cédric Renggli; Luka Rimanic; Luka Kolar; Wentao Wu 001; Ce Zhang 001 (ICDE, 2023)

ML-Powered Index Tuning: An Overview of Recent Progress and Open Challenges. - Tarique Siddiqui; Wentao Wu 001 (SIGMOD Rec., 2023)

Data Debugging with Shapley Importance over Machine Learning Pipelines. - Bojan Karlas; David Dao; Matteo Interlandi; Sebastian Schelter; Wentao Wu 001; Ce Zhang 001 (ICLR, 2024)

TablePuppet: A Generic Framework for Relational Federated Learning. - Lijie Xu; Chulin Xie; Yiran Guo; Gustavo Alonso; Bo Li 026; Guoliang Li 001; Wei Wang 009; Wentao Wu 001; Ce Zhang 001 (CoRR, 2024)

Wii: Dynamic Budget Reallocation In Index Tuning. - Xiaoying Wang; Wentao Wu 001; Chi Wang 001; Vivek R. Narasayya; Surajit Chaudhuri (Proc. ACM Manag. Data, 2024)

A systematic evaluation of machine learning on serverless infrastructure. - Jiawei Jiang 001; Shaoduo Gan; Bo Du 001; Gustavo Alonso; Ana Klimovic; Ankit Singla; Wentao Wu 001; Sheng Wang 007; Ce Zhang 001 (VLDB J., 2024)

Wred: Workload Reduction for Scalable Index Tuning. - Matteo Brucato; Tarique Siddiqui; Wentao Wu 001; Vivek R. Narasayya; Surajit Chaudhuri (Proc. ACM Manag. Data, 2024)

How good are machine learning clouds? Benchmarking two snapshots over 5 years. - Jiawei Jiang 001; Yi Wei; Yu Liu 075; Wentao Wu 001; Chuang Hu; Zhigao Zheng 001; Ziyi Zhang; Yingxia Shao; Ce Zhang 001 (VLDB J., 2024)

Budget-aware Query Tuning: An AutoML Perspective. - Wentao Wu 001; Chi Wang 001 (SIGMOD Rec., 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 001; Cédric Renggli; Shaoduo Gan; Kaan Kara; Guoliang Li 001; Ji Liu 002; Wentao Wu 001; Jieping Ye; Ce Zhang 001 (VLDB J., 2024)

FreewayML: An Adaptive and Stable Streaming Learning Framework for Dynamic Data Streams. - Zheng Qin; Zheheng Liang; Lijie Xu; Wentao Wu 001; Mingchao Wu; Wuqiang Shen; Wei Wang 009 (ICDE, 2025)

Esc: An Early-Stopping Checker for Budget-aware Index Tuning. - Xiaoying Wang; Wentao Wu 001; Vivek R. Narasayya; Surajit Chaudhuri (Proc. VLDB Endow., 2025)

Hybrid Cost Modeling for Reducing Query Performance Regression in Index Tuning. - Wentao Wu 001 (IEEE Trans. Knowl. Data Eng., 2025)