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Improving the sample complexity using global data

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1 Author(s)
S. Mendelson ; Comput. Sci. Lab., Australian Nat. Univ., Canberra, ACT, Australia

We study the sample complexity of proper and improper learning problems with respect to different q-loss functions. We improve the known estimates for classes which have relatively small covering numbers in empirical L2 spaces (e.g. log-covering numbers which are polynomial with exponent p<2). We present several examples of relevant classes which have a "small" fat-shattering dimension, and hence fit our setup, the most important of which are kernel machines

Published in:

IEEE Transactions on Information Theory  (Volume:48 ,  Issue: 7 )