Results 71 to 80 of about 66,452 (290)

Federated Learning Incentive Mechanism with Supervised Fuzzy Shapley Value

Axioms
The distributed training of federated machine learning, referred to as federated learning (FL), is discussed in models by multiple participants using local data without compromising data privacy and violating laws. In this paper, we consider the training
Xun Yang, Shuwen Xiang, Changgen Peng, Weijie Tan, Yue Wang, Hai Liu, Hongfa Ding   +6 more
doaj   +1 more source

Integrating Machine Learning With Constant‐Potential Simulation to Unravel Charge‐Transfer Mechanisms in Electrochemical Nitrogen Fixation

Advanced Science, EarlyView.
Integrating interpretable machine learning with the fixed‐potential method reveals a novel mechanism: the catalytic activity of the electrochemical nitrogen reduction reaction is governed by partial charge transfer, induced by variations in the intermediate potential of zero charge under constant potential.
Yufei Xue, Dushuo Feng, Yuefei Zhang, Yang Zhang, Yalong Jiao, Aijun Du, Guoping Gao   +6 more
wiley   +1 more source

Matrix approach to consistency of the additive efficient normalization of semivalues [PDF]

, 2007
In fact the Shapley value is the unique efficient semivalue. This motivated Ruiz et al. to do additive efficient normalization for semivalues. In this paper, by matrix approach we derive the relationship between the additive efficient normalization of ...
Driessen, T.S.H., Sun, H., Xu, G.
core   +2 more sources

High‐Throughput Screening and Interpretable Machine Learning for Rational Design of Bimetallic Catalysts for Methane Activation

Advanced Science, EarlyView.
ABSTRACT Methane's efficient catalytic removal is vital for sustainable development. Bimetallic catalysts, though promising for methane activation, pose a design challenge due to their complex compositional space. This work introduces an integrated framework that combines high‐throughput density functional theory (DFT) and interpretable machine ...
Mingzhang Pan, Tian Zhang, Jiawei Dong, Yubao Xie, Kaifeng Zhong, Wei Guan, Haiqiao Wei, Changcheng Fu, Yaqiong Su   +8 more
wiley   +1 more source

Applications of cooperative games to business activities

Intangible Capital, 2008
We show several applications of the cooperative game theory and the Shapley value to business activities. Among them we emphasize on the sharing of costs or profits.
Rafel Amer, Francesc Carreras, Antonio Magaña   +2 more
doaj   +1 more source

Towards Efficient Data Valuation Based on the Shapley Value

, 2020
"How much is my data worth?" is an increasingly common question posed by organizations and individuals alike. An answer to this question could allow, for instance, fairly distributing profits among multiple data contributors and determining prospective ...
Dao, David, Gurel, Nezihe Merve, Hubis, Frances Ann, Hynes, Nick, Jia, Ruoxi, Li, Bo, Song, Dawn, Spanos, Costas, Wang, Boxin, Zhang, Ce   +9 more
core  

Associated consistency and values for TU games [PDF]

, 2006
In the framework of the solution theory for cooperative transferable utility games, Hamiache axiomatized the well-known Shapley value as the unique one-point solution verifying the inessential game property, continuity, and associated consistency.
T. S. H. Driessen, Theo Driessen
core   +2 more sources

The Ranking Problem of Alternatives as a Cooperative Game

, 2015
This paper considers the ranking problem of candidates for a certain position based on ballot papers filled by voters. We suggest a ranking procedure of alternatives using cooperative game theory methods.
Kondratev, Aleksei, Mazalov, Vladimir
core   +1 more source

Absolute Shapley Value

, 2020
Shapley value is a concept in cooperative game theory for measuring the contribution of each participant, which was named in honor of Lloyd Shapley. Shapley value has been recently applied in data marketplaces for compensation allocation based on their contribution to the models.
openaire   +2 more sources

From Cell‐Free Transcriptomes to Single‐Cell Landscapes: Biomarker Discovery and Originating Cell Alteration Analysis via Graph Matrix Factorization

Advanced Science, EarlyView.
CellFreeGMF traces plasma cfRNA to likely originating cell types by integrating single‐cell atlases with graph‐regularized matrix factorization. The method decomposes cfRNA profiles into sample–cell contributions to reconstruct pseudo single‐cell expression.
Wenxiang Zhang, Wenjing Zhang, Hang Wei, Shiyan Liu, Junliang Shang, Weijie Gong, Hanwen Cheng, Xiujuan Lei, Yuhui Kou, Baoguo Jiang   +9 more
wiley   +1 more source