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Number of items: 4.
Proceedings paper
Denevi, G;
Ciliberto, C;
Stamos, D;
Pontil, M;
(2018)
Incremental learning-to-learn with statistical guarantees.
In: Globerson, Amir and Silva, Ricardo, (eds.)
Proceedings of the Thirty-Fourth Conference (2018), Uncertainty in Artificial Intelligence.
(pp. pp. 457-466).
AUAI: California, USA.
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Denevi, G;
Ciliberto, C;
Stamos, D;
Pontil, M;
(2018)
Learning To Learn Around A Common Mean.
In: Bengio, S and Wallach, H and Larochelle, H and Grauman, K and CesaBianchi, N and Garnett, R, (eds.)
Advances in Neural Information Processing Systems 31.
NIPS Proceedings: Montréal, Canada.
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McDonald, AM;
Pontil, M;
Stamos, D;
(2016)
Fitting Spectral Decay with the k-Support Norm.
In: Gretton, A and Robert, CC, (eds.)
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics.
(pp. pp. 1061-1069).
Journal of Machine Learning Research
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Thesis
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Stamos, Dimitris;
(2020)
Frameworks for Learning from Multiple Tasks.
Doctoral thesis (Ph.D), UCL (University College London).
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