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Found 6 papers, 0 papers with code
The Internet of Federated Things (IoFT): A Vision for the Future and In-depth Survey of Data-driven Approaches for Federated Learning
The Internet of Things (IoT) is on the verge of a major paradigm shift.
On Negative Transfer and Structure of Latent Functions in Multi-output Gaussian Processes
The multi-output Gaussian process ($\mathcal{MGP}$) is based on the assumption that outputs share commonalities, however, if this assumption does not hold negative transfer will lead to decreased performance relative to learning outputs independently or in subsets.
The Renyi Gaussian Process: Towards Improved Generalization
We introduce an alternative closed form lower bound on the Gaussian process ($\mathcal{GP}$) likelihood based on the R\'enyi $\alpha$-divergence.
Functional Principal Component Analysis for Extrapolating Multi-stream Longitudinal Data
A Gaussian process prior for the FPC scores is then established based on a functional semi-metric that measures similarities between streams of historical units and the in-service unit.
Variational Inference of Joint Models using Multivariate Gaussian Convolution Processes
We present a non-parametric prognostic framework for individualized event prediction based on joint modeling of both longitudinal and time-to-event data.
Minimizing Negative Transfer of Knowledge in Multivariate Gaussian Processes: A Scalable and Regularized Approach
The proposed method has excellent scalability when the number of outputs is large and minimizes the negative transfer of knowledge between uncorrelated outputs.
