Data Collaboration Analysis Over Matrix Manifolds

arXiv:2403.02780v1 Announce Type: new
Abstract: The effectiveness of machine learning (ML) algorithms is deeply intertwined with the quality and diversity of their training datasets. Improved datasets, marked by superior quality, enhance the predictive accuracy and broaden the applicability of models across varied scenarios. Researchers often integrate data from multiple sources to mitigate biases and limitations of single-source datasets. However, this extensive data amalgamation raises significant ethical concerns, particularly regarding user privacy and the risk of unauthorized data disclosure. Various global …

abstract accuracy algorithms analysis arxiv biases collaboration cs.lg data data collaboration datasets diversity machine machine learning math.oc matrix multiple predictive quality researchers training training datasets type