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Data valuation has wide use cases in machine learning, including improving data quality and creating economic incentives for data sharing.
Efficient task-specific data valuation for nearest neighbor algorithms
Ruoxi Jia, David Dao, Boxin Wang, Frances Ann Hubis, Nezihe Merve Gurel, Bo Li, Ce Zhang, Costas J Spanos, and Dawn Song · 1908
Earlier work this paper cites.
Ruoxi Jia, Fan Wu, Xuehui Sun, Jiacen Xu, David Dao, Bhavya Kailkhura, Ce Zhang, Bo Li, and Dawn Song · 1911
Earlier work this paper cites.
The elementary statistics of majority voting
Lionel S Penrose · 1946
Earlier work this paper cites.
A value for n-person games
Lloyd S Shapley · 1953
Earlier work this paper cites.
Values of large games, IV: Evaluating the electoral college by Montecarlo techniques
Irwin Mann and Lloyd S Shapley · 1960
Earlier work this paper cites.
Handbook of mathematical functions with formulas, graphs, and mathematical tables , volume 55
Milton Abramowitz and Irene A Stegun · 1964
Earlier work this paper cites.
Weighted voting doesn’t work: A mathematical analysis
John F Banzhaf III · 1964
Earlier work this paper cites.
Control of collectivities and the power of a collectivity to act, in, b. lieberman (ed.), social choice, 1971
James Coleman · 1971
Earlier work this paper cites.
Multilinear extensions of games
Guillermo Owen · 1972
Earlier work this paper cites.
A new index of power for simplen-person games
John Deegan and Edward W Packel · 1978
Earlier work this paper cites.
Algorithm as 155: The distribution of a linear combination of χ \chi 2 random variables
Robert B Davies · 1980
Earlier work this paper cites.
Value theory without efficiency
Pradeep Dubey, Abraham Neyman, and Robert James Weber · 1981
Earlier work this paper cites.
Forming coalitions and measuring voting power
Manfred J Holler · 1982
Earlier work this paper cites.
Approximations to the banzhaf index of voting power
Samuel Merrill III · 1982
Earlier work this paper cites.
Power, luck and the right index
Manfred J Holler and Edward W Packel · 1983
Earlier work this paper cites.
Probabilistic values for games
Robert J Weber · 1988
Earlier work this paper cites.
Handwritten digit recognition with a back-propagation network
Yann LeCun, Bernhard Boser, John Denker, Donnie Henderson, Richard Howard, Wayne Hubbard, and Lawrence Jackel · 1989
Earlier work this paper cites.
Approximations of pseudo-boolean functions; applications to game theory
Peter L Hammer and Ron Holzman · 1992
Earlier work this paper cites.
On the complexity of cooperative solution concepts
Xiaotie Deng and Christos H Papadimitriou · 1994
Earlier work this paper cites.
The mnist database of handwritten digits
Yann LeCun · 1998
Earlier work this paper cites.
Vehicle classification in distributed sensor networks
Marco F Duarte and Yu Hen Hu · 2004
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Calibrating noise to sensitivity in private data analysis
Cynthia Dwork, Frank McSherry, Kobbi Nissim, and Adam Smith · 2006
Earlier work this paper cites.
Complexity of comparison of influence of players in simple games
Haris Aziz · 2008
Earlier work this paper cites.
A linear approximation method for the shapley value
Shaheen S Fatima, Michael Wooldridge, and Nicholas R Jennings · 2008
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Polynomial calculation of the shapley value based on sampling
Javier Castro, Daniel Gómez, and Juan Tejada · 2009
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Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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Learning multiple layers of features from tiny images
Alex Krizhevsky, Geoffrey Hinton, et al · 2009
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The comparisons of data mining techniques for the predictive accuracy of probability of default of credit card clients
I-Cheng Yeh and Che-hui Lien · 2009
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Approximating power indices: theoretical and empirical analysis
Yoram Bachrach, Evangelos Markakis, Ezra Resnick, Ariel D Procaccia, Jeffrey S Rosenschein, and Amin Saberi · 2010
Cited alongside, same era.
Randomized smoothing for stochastic optimization
John C Duchi, Peter L Bartlett, and Martin J Wainwright · 2012
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Calibrating probability with undersampling for unbalanced classification
Data shapley valuation for efficient batch active learning
Amirata Ghorbani, James Zou, and Andre Esteva · 2021
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Improved feature importance computations for tree models: Shapley vs. banzhaf
Adam Karczmarz, Anish Mukherjee, Piotr Sankowski, and Piotr Wygocki · 2021
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Beta shapley: a unified and noise-reduced data valuation framework for machine learning
Yongchan Kwon and James Zou · 2021
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Efficient computation and analysis of distributional shapley values
Yongchan Kwon, Manuel A Rivas, and James Zou · 2021
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High dimensional model explanations: An axiomatic approach
Neel Patel, Martin Strobel, and Yair Zick · 2021
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Andrea Dal Pozzolo, Olivier Caelen, Reid A Johnson, and Gianluca Bontempi · 2015
Cited alongside, same era.
Influence in classification via cooperative game theory
Amit Datta, Anupam Datta, Ariel D Procaccia, and Yair Zick · 2015
Cited alongside, same era.
Addressing the computational issues of the Shapley value with applications in the smart grid
Sasan Maleki · 2015
Cited alongside, same era.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Cited alongside, same era.
Understanding black-box predictions via influence functions
Pang Wei Koh and Percy Liang · 2017
Cited alongside, same era.
Feature importance scores and lossless feature pruning using banzhaf power indices
Bogdan Kulynych and Carmela Troncoso · 2017
Cited alongside, same era.
A unified approach to interpreting model predictions
Scott M Lundberg and Su-In Lee · 2017
Cited alongside, same era.
Nondeterminism and instability in neural network optimization
Cecilia Summers and Michael J Dinneen · 2021
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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
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Fast hierarchical games for image explanations
Jacopo Teneggi, Alexandre Luster, and Jeremias Sulam · 2021
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Improving cooperative game theory-based data valuation via data utility learning
Tianhao Wang, Yu Yang, and Ruoxi Jia · 2021
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Validation free and replication robust volume-based data valuation
Xinyi Xu, Zhaoxuan Wu, Chuan Sheng Foo, and Bryan Kian Hsiang Low · 2021
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Who’s responsible? jointly quantifying the contribution of the learning algorithm and data
Gal Yona, Amirata Ghorbani, and James Zou · 2021
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It is not (only) about privacy: How multi-party computation redefines control, trust, and risk in data sharing
Wirawan Agahari, Hosea Ofe, and Mark de Reuver · 2022
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On the convergence of the shapley value in parametric bayesian learning games
Lucas Agussurja, Xinyi Xu, and Bryan Kian Hsiang Low · 2022
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Fundamentals of task-agnostic data valuation
Mohammad Mohammadi Amiri, Frederic Berdoz, and Ramesh Raskar · 2022
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Datamodels: Predicting predictions from training data
Andrew Ilyas, Sung Min Park, Logan Engstrom, Guillaume Leclerc, and Aleksander Madry · 2022
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Data debugging with shapley importance over end-to-end machine learning pipelines
Bojan Karlaš, David Dao, Matteo Interlandi, Bo Li, Sebastian Schelter, Wentao Wu, and Ce Zhang · 2022
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Measuring the effect of training data on deep learning predictions via randomized experiments
Jinkun Lin, Anqi Zhang, Mathias Lécuyer, Jinyang Li, Aurojit Panda, and Siddhartha Sen · 2022
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Quantifying inherent randomness in machine learning algorithms
Soham Raste, Rahul Singh, Joel Vaughan, and Vijayan N Nair · 2022
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Understanding influence functions and datamodels via harmonic analysis
Nikunj Saunshi, Arushi Gupta, Mark Braverman, and Sanjeev Arora · 2022
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Data valuation in machine learning:“ingredients”, strategies, and open challenges
Rachael Hwee Ling Sim, Xinyi Xu, and Bryan Kian Hsiang Low · 2022
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Incentivizing collaboration in machine learning via synthetic data rewards
Sebastian Shenghong Tay, Xinyi Xu, Chuan Sheng Foo, and Bryan Kian Hsiang Low · 2022
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Private data valuation and fair payment in data marketplaces
Zhihua Tian, Jian Liu, Jingyu Li, Xinle Cao, Ruoxi Jia, and Kui Ren · 2022
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Davinz: Data valuation using deep neural networks at initialization
Zhaoxuan Wu, Yao Shu, and Bryan Kian Hsiang Low · 2022
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Randomness in neural network training: Characterizing the impact of tooling
Donglin Zhuang, Xingyao Zhang, Shuaiwen Song, and Sara Hooker · 2022
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A note on "towards efficient data valuation based on the shapley value”, 2023
Jiachen T. Wang and Ruoxi Jia · 2023
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