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2020 – today
- 2024
[j8]Aaditya Naik
, Adam Stein, Yinjun Wu, Mayur Naik, Eric Wong:
TorchQL: A Programming Framework for Integrity Constraints in Machine Learning. Proc. ACM Program. Lang. 8(OOPSLA1): 833-863 (2024)- [c11]Adam Stein, Aaditya Naik, Yinjun Wu, Mayur Naik, Eric Wong:
Towards Compositionality in Concept Learning. ICML 2024 - [c10]Yinjun Wu, Mayank Keoliya, Kan Chen, Neelay Velingker, Ziyang Li, Emily J. Getzen, Qi Long, Mayur Naik, Ravi B. Parikh, Eric Wong:
DISCRET: Synthesizing Faithful Explanations For Treatment Effect Estimation. ICML 2024 - [i11]Yinjun Wu, Mayank Keoliya, Kan Chen, Neelay Velingker, Ziyang Li, Emily J. Getzen, Qi Long, Mayur Naik, Ravi B. Parikh, Eric Wong:
DISCRET: Synthesizing Faithful Explanations For Treatment Effect Estimation. CoRR abs/2406.00611 (2024) - [i10]Adam Stein, Aaditya Naik, Yinjun Wu, Mayur Naik, Eric Wong:
Towards Compositionality in Concept Learning. CoRR abs/2406.18534 (2024) - 2023
- [c9]Yinjun Wu, Adam Stein, Jacob Gardner, Mayur Naik:
Learning to Select Pivotal Samples for Meta Re-weighting. AAAI 2023: 6128-6136 - [c8]Aaditya Naik, Yinjun Wu, Mayur Naik, Eric Wong:
Do Machine Learning Models Learn Statistical Rules Inferred from Data? ICML 2023: 25677-25693 - [i9]Yinjun Wu, Adam Stein, Jacob Gardner, Mayur Naik:
Learning to Select Pivotal Samples for Meta Re-weighting. CoRR abs/2302.04418 (2023) - [i8]Aaditya Naik, Yinjun Wu, Mayur Naik, Eric Wong:
Do Machine Learning Models Learn Common Sense? CoRR abs/2303.01433 (2023) - [i7]Adam Stein, Yinjun Wu, Eric Wong, Mayur Naik:
Rectifying Group Irregularities in Explanations for Distribution Shift. CoRR abs/2305.16308 (2023) - [i6]Aaditya Naik, Adam Stein, Yinjun Wu, Eric Wong, Mayur Naik:
MDB: Interactively Querying Datasets and Models. CoRR abs/2308.06686 (2023) - 2022
- [j7]Yinjun Wu, Val Tannen, Susan B. Davidson:
Provenance-based Model Maintenance: Implications for Privacy. IEEE Data Eng. Bull. 45(1): 37-49 (2022) - 2021
- [j6]Yinjun Wu, James Weimer, Susan B. Davidson:
CHEF: A Cheap and Fast Pipeline for Iteratively Cleaning Label Uncertainties. Proc. VLDB Endow. 14(11): 2410-2418 (2021) - [c7]Yinjun Wu, Jingchao Ni, Wei Cheng, Bo Zong, Dongjin Song, Zhengzhang Chen, Yanchi Liu, Xuchao Zhang, Haifeng Chen, Susan B. Davidson:
Dynamic Gaussian Mixture based Deep Generative Model For Robust Forecasting on Sparse Multivariate Time Series. AAAI 2021: 651-659 - [i5]Yinjun Wu, Jingchao Ni, Wei Cheng, Bo Zong, Dongjin Song, Zhengzhang Chen, Yanchi Liu, Xuchao Zhang, Haifeng Chen, Susan B. Davidson:
Dynamic Gaussian Mixture based Deep Generative Model For Robust Forecasting on Sparse Multivariate Time Series. CoRR abs/2103.02164 (2021) - [i4]Yinjun Wu, James Weimer, Susan B. Davidson:
CHEF: A Cheap and Fast Pipeline for Iteratively Cleaning Label Uncertainties (Technical Report). CoRR abs/2107.08588 (2021) - 2020
- [j5]Peter Buneman, Greig Christie, Jamie A. Davies, Roza Dimitrellou, Simon D. Harding, Adam J. Pawson, Joanna L. Sharman, Yinjun Wu:
Why data citation isn't working, and what to do about it. Database J. Biol. Databases Curation 2020 (2020) - [c6]Yinjun Wu, Kwanghyun Park, Rathijit Sen, Brian Kroth, Jaeyoung Do:
Lessons learned from the early performance evaluation of Intel optane DC persistent memory in DBMS. DaMoN 2020: 14:1-14:3 - [c5]Yinjun Wu, Edgar Dobriban, Susan B. Davidson:
DeltaGrad: Rapid retraining of machine learning models. ICML 2020: 10355-10366 - [c4]Yinjun Wu, Val Tannen, Susan B. Davidson:
PrIU: A Provenance-Based Approach for Incrementally Updating Regression Models. SIGMOD Conference 2020: 447-462 - [i3]Yinjun Wu, Val Tannen, Susan B. Davidson:
PrIU: A Provenance-Based Approach for Incrementally Updating Regression Models. CoRR abs/2002.11791 (2020) - [i2]Yinjun Wu, Kwanghyun Park, Rathijit Sen, Brian Kroth, Jaeyoung Do:
Lessons learned from the early performance evaluation of Intel Optane DC Persistent Memory in DBMS. CoRR abs/2005.07658 (2020) - [i1]Yinjun Wu, Edgar Dobriban, Susan B. Davidson:
DeltaGrad: Rapid retraining of machine learning models. CoRR abs/2006.14755 (2020)
2010 – 2019
- 2019
- [j4]Yinjun Wu, Abdussalam Alawini, Daniel Deutch, Tova Milo, Susan B. Davidson:
ProvCite: Provenance-based Data Citation. Proc. VLDB Endow. 12(7): 738-751 (2019) - 2018
- [j3]Abdussalam Alawini, Susan B. Davidson, Gianmaria Silvello, Val Tannen, Yinjun Wu:
Data Citation: A New Provenance Challenge. IEEE Data Eng. Bull. 41(1): 27-38 (2018) - [c3]Yinjun Wu, Abdussalam Alawini, Susan B. Davidson, Gianmaria Silvello:
Data Citation: Giving Credit Where Credit is Due. SIGMOD Conference 2018: 99-114 - 2017
- [j2]Abdussalam Alawini, Susan B. Davidson, Wei Hu, Yinjun Wu:
Automating Data Citation in CiteDB. Proc. VLDB Endow. 10(12): 1881-1884 (2017) - 2016
- [j1]Yinjun Wu, Zhen Chen, Junwei Cao, Haoxun Li, Chenxing Li, Yijie Wang, Wenxun Zheng, Jiahui Chang, Jing Zhou, Ziwei Hu, Jinghong Guo:
CAMP: A New Bitmap Index for Data Retrieval in Traffic Archival. IEEE Commun. Lett. 20(6): 1128-1131 (2016) - [c2]Chenxing Li, Zhen Chen, Wenxun Zheng, Yinjun Wu, Junwei Cao:
BAH: A Bitmap Index Compression Algorithm for Fast Data Retrieval. LCN 2016: 697-705 - 2015
- [c1]Yinjun Wu, Zhen Chen, Yuhao Wen, Junwei Cao, Wenxun Zheng, Ge Ma:
A General Analytical Model for Spatial and Temporal Performance of Bitmap Index Compression Algorithms in Big Data. ICCCN 2015: 1-10
Coauthor Index
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