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Slow subspace learning from stationary processes
Published on Feb 4, 20253128 Views
The talk presents a method of unsupervised learning from stationary, vector-valued processes. The method selects a subspace on the basis of an objective which can be used to bound the expected classif
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Presentation
BOUNDS FOR LINEAR MTL00:02
ingredients of linear MTL00:34
objective04:10
error bound05:18
Rademacher complexity09:37
Hölders inequality11:40
theorem13:28
multi-task subspace learning23:39