Fetching the paper…
Reading the bibliography…
Shapley value-based data valuation methods, originating from cooperative game theory, quantify the usefulness of each individual sample by considering its contribution to all possible training subsets.
A value for n-person games
Lloyd S Shapley et al · 1953
Earlier work this paper cites.
Residuals and influence in regression
R Dennis Cook and Sanford Weisberg · 1982
Earlier work this paper cites.
The Shapley value: essays in honor of Lloyd S. Shapley
Alvin E Roth · 1988
Earlier work this paper cites.
Newsweeder: Learning to filter netnews
Ken Lang · 1995
Earlier work this paper cites.
Feature selection based on the shapley value
Shay Cohen, Eytan Ruppin, and Gideon Dror · 2005
Earlier work this paper cites.
Margin based active learning
Maria-Florina Balcan, Andrei Broder, and Tong Zhang · 2007
Earlier work this paper cites.
Entropy-based active learning for object recognition
Alex Holub, Pietro Perona, and Michael C Burl · 2008
Earlier work this paper cites.
Recursive deep models for semantic compositionality over a sentiment treebank
Richard Socher, Alex Perelygin, Jean Wu, Jason Chuang, Christopher D Manning, Andrew Y Ng, and Christopher Potts · 2013
Earlier work this paper cites.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Earlier work this paper cites.
A unified approach to interpreting model predictions
Scott M Lundberg and Su-In Lee · 2017
Earlier work this paper cites.
Fashion-mnist: a novel image dataset for benchmarking machine learning algorithms
Han Xiao, Kashif Rasul, and Roland Vollgraf · 2017
Earlier work this paper cites.
A feature selection method based on shapley value to false alarm reduction in icus a genetic-algorithm approach
Mohammad Zaeri-Amirani, Fatemeh Afghah, and Sajad Mousavi · 2018
Earlier work this paper cites.
Towards efficient data valuation based on the shapley value
Ruoxi Jia, David Dao, Boxin Wang, Frances Ann Hubis, Nick Hynes, Nezihe Merve Gürel, Bo Li, Ce Zhang, Dawn Song, and Costas J Spanos · 2019
Earlier work this paper cites.
Data shapley: Equitable valuation of data for machine learning
Amirata Ghorbani and James Zou · 2019
Earlier work this paper cites.
Efficient task-specific data valuation for nearest neighbor algorithms
Ruoxi Jia, David Dao, Boxin Wang, Frances Ann Hubis, Nezihe Merve Gurel, Bo Li4 Ce Zhang, and Costas Spanos1 Dawn Song · 2019
Earlier work this paper cites.
Sentence-bert: Sentence embeddings using siamese bert-networks
Nils Reimers and Iryna Gurevych · 2019
Earlier work this paper cites.
Outlier detection: Methods, models, and classification
Azzedine Boukerche, Lining Zheng, and Omar Alfandi · 2020
Earlier work this paper cites.
Fast best subset selection: Coordinate descent and local combinatorial optimization algorithms
Hussein Hazimeh and Rahul Mazumder · 2020
Cited alongside, same era.
The shapley taylor interaction index
Mukund Sundararajan, Kedar Dhamdhere, and Ashish Agarwal · 2020
Cited alongside, same era.
Improving kernelshap: Practical shapley value estimation via linear regression
Ian Covert and Su-In Lee · 2020
Cited alongside, same era.
Collaborative machine learning with incentive-aware model rewards
Rachael Hwee Ling Sim, Yehong Zhang, Mun Choon Chan, and Bryan Kian Hsiang Low · 2020
Cited alongside, same era.
A distributional framework for data valuation
Amirata Ghorbani, Michael Kim, and James Zou · 2020
Cited alongside, same era.
Meta label correction for noisy label learning
Fair clustering using antidote data
Anshuman Chhabra, Adish Singla, and Prasant Mohapatra · 2022
Later among the works it cites.
Training data influence analysis and estimation: A survey
Zayd Hammoudeh and Daniel Lowd · 2022
Later among the works it cites.
Cs-shapley: class-wise shapley values for data valuation in classification
Stephanie Schoch, Haifeng Xu, and Yangfeng Ji · 2022
Later among the works it cites.
Beta Shapley: a unified and noise-reduced data valuation framework for machine learning
Yongchan Kwon and James Zou · 2022
Later among the works it cites.
On shapley value in data assemblage under independent utility
Xuan Luo, Jian Pei, Zicun Cong, and Cheng Xu · 2022
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Guoqing Zheng, Ahmed Hassan Awadallah, and Susan Dumais · 2021
Cited alongside, same era.
Influence selection for active learning
Zhuoming Liu, Hao Ding, Huaping Zhong, Weijia Li, Jifeng Dai, and Conghui He · 2021
Cited alongside, same era.
Scalability vs. utility: Do we have to sacrifice one for the other in data importance quantification?
Ruoxi Jia, Fan Wu, Xuehui Sun, Jiacen Xu, David Dao, Bhavya Kailkhura, Ce Zhang, Bo Li, and Dawn Song · 2021
Cited alongside, same era.
Fastshap: Real-time shapley value estimation
Neil Jethani, Mukund Sudarshan, Ian Connick Covert, Su-In Lee, and Rajesh Ranganath · 2021
Cited alongside, same era.
The shapley value of classifiers in ensemble games
Benedek Rozemberczki and Rik Sarkar · 2021
Cited alongside, same era.
Trustworthy machine learning for health care: scalable data valuation with the shapley value
Konstantin D Pandl, Fabian Feiland, Scott Thiebes, and Ali Sunyaev · 2021
Cited alongside, same era.
Data valuation for medical imaging using shapley value and application to a large-scale chest x-ray dataset
Siyi Tang, Amirata Ghorbani, Rikiya Yamashita, Sameer Rehman, Jared A Dunnmon, James Zou, and Daniel L Rubin · 2021
Cited alongside, same era.
How to measure uncertainty in uncertainty sampling for active learning
Vu-Linh Nguyen, Mohammad Hossein Shaker, and Eyke Hüllermeier · 2022
Later among the works it cites.
Data-centric ai: Perspectives and challenges
Daochen Zha, Zaid Pervaiz Bhat, Kwei-Herng Lai, Fan Yang, and Xia Hu · 2023
Later among the works it cites.
Learning antidote data to individual unfairness
Peizhao Li, Ethan Xia, and Hongfu Liu · 2023
Later among the works it cites.
A survey on active learning: State-of-the-art, practical challenges and research directions
Alaa Tharwat and Wolfram Schenck · 2023
Later among the works it cites.
From shapley values to generalized additive models and back
Sebastian Bordt and Ulrike von Luxburg · 2023
Later among the works it cites.
Faith-shap: The faithful shapley interaction index
Che-Ping Tsai, Chih-Kuan Yeh, and Pradeep Ravikumar · 2023
Later among the works it cites.
Opendataval: a unified benchmark for data valuation
Kevin Jiang, Weixin Liang, James Y Zou, and Yongchan Kwon · 2023
Later among the works it cites.
Data banzhaf: A robust data valuation framework for machine learning
Jiachen T Wang and Ruoxi Jia · 2023
Later among the works it cites.
A note on" efficient task-specific data valuation for nearest neighbor algorithms"
Jiachen T Wang and Ruoxi Jia · 2023
Later among the works it cites.
Threshold knn-shapley: A linear-time and privacy-friendly approach to data valuation
Jiachen T Wang, Yuqing Zhu, Yu-Xiang Wang, Ruoxi Jia, and Prateek Mittal · 2023
Later among the works it cites.
Efficient data shapley for weighted nearest neighbor algorithms
Jiachen T Wang, Prateek Mittal, and Ruoxi Jia · 2024
Closest in time.