- A Principled Approach to Data Valuation for Federated Learning🔍
- A Principled Approach to Data Valuation for Federated Learning.🔍
- "A Principled Approach to Data Valuation for Federated Learning ...🔍
- [PDF] A Principled Approach to Data Valuation for Federated Learning🔍
- daviddao/awesome|data|valuation🔍
- Data Valuation in Federated Learning with Jian Pei🔍
- Data Valuation and Detections in Federated Learning🔍
- DeepAI on X🔍
A Principled Approach to Data Valuation for Federated Learning
A Principled Approach to Data Valuation for Federated Learning
Title:A Principled Approach to Data Valuation for Federated Learning ... Abstract:Federated learning (FL) is a popular technique to train machine ...
A Principled Approach to Data Valuation for Federated Learning
This chapter proposes a variant of the SV amenable to FL, which we call the federated Shapley value.
A Principled Approach to Data Valuation for Federated Learning
Request PDF | A Principled Approach to Data Valuation for Federated Learning | Federated learning (FL) is a popular technique to train machine learning (ML) ...
A Principled Approach to Data Valuation for Federated Learning. - dblp
Bibliographic details on A Principled Approach to Data Valuation for Federated Learning.
A Principled Approach to Data Valuation for Federated Learning
It has been increasingly used for valuing training data in centralized learning. However, computing the SV requires exhaustively evaluating the ...
"A Principled Approach to Data Valuation for Federated Learning ...
The paper "A Principled Approach to Data Valuation for Federated Learning" by Tianhao Wang, Johannes Rausch, Ce Zhang, Ruoxi Jia, ...
[PDF] A Principled Approach to Data Valuation for Federated Learning
A variant of the SV amenable to FL that preserves the desirable properties of the canonical SV while it can be calculated without incurring ...
A Principled Approach to Data Valuation for Federated Learning
Chessa, M., Loiseau, P.: A cooperative game-theoretic approach to quantify the value of personal data in networks. · Ghorbani, A., Zou, J.: Data Shapley: ...
A Principled Approach to Data Valuation for Federated Learning · no code implementations • 14 Sep 2020 • Tianhao Wang, Johannes Rausch, Ce Zhang, Ruoxi Jia ...
daviddao/awesome-data-valuation - GitHub
Summary Federated learning (FL) is a machine learning paradigm that enables privacy-preserving cross-party data collaboration. This work introduces "FedValue," ...
Data Valuation in Federated Learning with Jian Pei - YouTube
Abstract: To enable practical federated learning, we not only have to improve the efficiency but also address the incentive and fairness ...
Data Valuation and Detections in Federated Learning
Federated Learning (FL) enables collaborative model training while preserving the privacy of raw data. A chal- lenge in this framework is the fair and ...
DeepAI on X: "A Principled Approach to Data Valuation for ...
A Principled Approach to Data Valuation for Federated Learning https://t.co/DLesTBPy74 by Tianhao Wang et al.
[PDF] Data Valuation and Detections in Federated Learning
This paper introduces a novel privacy-preserving method for evaluating client contributions and selecting relevant datasets without a pre-specified training ...
Improving Fairness for Data Valuation in Horizontal Federated ...
[29] proposed a reinforcement learning-based method to adaptively learn the contribution of each data point towards the learned predictor model. Zhao et al. [30] ...
Towards More Efficient Data Valuation in Healthcare Federated ...
Federated Learning (FL) wherein multiple institutions collaboratively train a machine learning model without sharing data is becoming popular.
Fundamentals of Task-Agnostic Data Valuation - AAAI Publications
A principled approach to data valuation for federated learn- ing. Lecture Notes in Computer Science, Springer, 12500: 153–167. Xiao et al. 2017. Fashion ...
Poster: Verifiable Data Valuation with Strong Fairness in Horizontal ...
Data valuation for each data provider becomes a critical issue to guarantee the fairness of federated learning by estimating the dataset quality ...
Class-wise Shapley Values for Data Valuation in Classification
We compute value estimates on the noised training sets using each valuation method ... A principled approach to data valuation for federated learning. In ...
Data valuation for machine learning and federated learning
We leverage Shapley value [16] to design a round-based data valuation approach, quantifying each client's contribution per round and using it as a real-time ...