Renzhi Wu

According to our database, Renzhi Wu authored at least 20 papers between 2019 and 2024.

Collaborative distances:

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

2024

SketchQL: Video Moment Querying with a Visual Query Interface.

Renzhi Wu, Pramod Chunduri, Ali Payani, Xu Chu, Joy Arulraj, Kexin Rong

Proc. ACM Manag. Data, September, 2024

SketchQL Demonstration: Zero-shot Video Moment Querying with Sketches.

Renzhi Wu, Pramod Chunduri, Dristi J. Shah, Ashmitha Julius Aravind, Ali Payani, Xu Chu, Joy Arulraj, Kexin Rong

Proc. VLDB Endow., August, 2024

User-centered Programmatic Data Labeling.

Renzhi Wu

PhD thesis, 2024

2023

Experiences and Lessons Learned from the SIGMOD Entity Resolution Programming Contests.

Andrea De Angelis, Maurizio Mazzei, Federico Piai, Paolo Merialdo, Giovanni Simonini, Luca Zecchini, Sonia Bergamaschi, Donatella Firmani, Xu Chu, Peng Li, Renzhi Wu

SIGMOD Rec., June, 2023

Ground Truth Inference for Weakly Supervised Entity Matching.

Renzhi Wu, Alexander Bendeck, Xu Chu, Yeye He

Proc. ACM Manag. Data, 2023

Rethinking Similarity Search: Embracing Smarter Mechanisms over Smarter Data.

Renzhi Wu, Jingfan Meng, Jie Jeff Xu, Huayi Wang, Kexin Rong

CoRR, 2023

Learning Hyper Label Model for Programmatic Weak Supervision.

Renzhi Wu, Shen-En Chen, Jieyu Zhang, Xu Chu

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Decentralized Personalized Online Federated Learning.

Renzhi Wu, Saayan Mitra, Xiang Chen, Anup B. Rao

Proceedings of the IEEE International Conference on Big Data, 2023

2022

A Cluster-then-label Approach for Few-shot Learning with Application to Automatic Image Data Labeling.

Renzhi Wu, Nilaksh Das, Sanya Chaba, Sakshi Gandhi, Duen Horng Chau, Xu Chu

ACM J. Data Inf. Qual., 2022

Learned Label Aggregation for Weak Supervision.

Renzhi Wu, Shen-En Chen, Xu Chu

CoRR, 2022

A Model-Agnostic Approach for Learning with Noisy Labels of Arbitrary Distributions.

Shuang Hao, Peng Li, Renzhi Wu, Xu Chu

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

2021

Demonstration of Panda: A Weakly Supervised Entity Matching System.

Renzhi Wu, Prem Sakala, Peng Li, Xu Chu, Yeye He

Proc. VLDB Endow., 2021

Learning to be a Statistician: Learned Estimator for Number of Distinct Values.

Renzhi Wu, Bolin Ding, Xu Chu, Zhewei Wei, Xiening Dai, Tao Guan, Jingren Zhou

Proc. VLDB Endow., 2021

Improving video anomaly detection performance by mining useful data from unseen video frames.

Renzhi Wu, Shuai Li, Chenglizhao Chen, Aimin Hao

Neurocomputing, 2021

2020

Dynamic pattern matching with multiple queries on large scale data streams.

Sergey Sukhanov, Renzhi Wu, Christian Debes, Abdelhak M. Zoubir

Signal Process., 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

ZeroER: Entity Resolution using Zero Labeled Examples.

Renzhi Wu, Sanya Chaba, Saurabh Sawlani, Xu Chu, Saravanan Thirumuruganathan

Proceedings of the 2020 International Conference on Management of Data, 2020

GOGGLES: Automatic Image Labeling with Affinity Coding.

Nilaksh Das, Sanya Chaba, Renzhi Wu, Sakshi Gandhi, Duen Horng Chau, Xu Chu

Proceedings of the 2020 International Conference on Management of Data, 2020

2019

Real Time Pattern Matching with Dynamic Normalization.

Renzhi Wu, Sergey Sukhanov, Christian Debes

CoRR, 2019

AutoER: Automated Entity Resolution using Generative Modelling.

Renzhi Wu, Sanya Chaba, Saurabh Sawlani, Xu Chu, Saravanan Thirumuruganathan

CoRR, 2019