Timothy M. Hospedales
3 أوراق في مجموعة PaperMetrix
أوراق هذا المؤلف
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Multivariate Regression on the Grassmannian for Predicting Novel Domains
2016
We study the problem of predicting how to recognise visual objects in novel domains with neither labelled nor unlabelled training data. Domain adaptation is now an established research area due to its value in ameliorating …
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FedH2L: Federated Learning with Model and Statistical Heterogeneity
2021 · arXiv (Cornell University)
Federated learning (FL) enables distributed participants to collectively learn a strong global model without sacrificing their individual data privacy. Mainstream FL approaches require each participant to share a common network architecture and further assume that …
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Model Diffusion for Certifiable Few-shot Transfer Learning
2025 · arXiv (Cornell University)
In contemporary deep learning, a prevalent and effective workflow for solving low-data problems is adapting powerful pre-trained foundation models (FMs) to new tasks via parameter-efficient fine-tuning (PEFT). However, while empirically effective, the resulting solutions lack …