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NIPS
2007
15 years 5 months ago
Learning Bounds for Domain Adaptation
Empirical risk minimization offers well-known learning guarantees when training and test data come from the same domain. In the real world, though, we often wish to adapt a classi...
John Blitzer, Koby Crammer, Alex Kulesza, Fernando...
MFPS
1993
15 years 8 months ago
Some Quasi-Varieties of Iteration Theories
All known structures involving a constructively obtainable fixed point (or iteration) operation satisfy the equational laws defining iteration theories. Hence, there seems to be...
Stephen L. Bloom, Zoltán Ésik
CORR
2010
Springer
104views Education» more  CORR 2010»
15 years 4 months ago
Empirical learning aided by weak domain knowledge in the form of feature importance
Standard hybrid learners that use domain knowledge require stronger knowledge that is hard and expensive to acquire. However, weaker domain knowledge can benefit from prior knowle...
Ridwan Al Iqbal
CRYPTO
2010
Springer
228views Cryptology» more  CRYPTO 2010»
15 years 5 months ago
On Generalized Feistel Networks
We prove beyond-birthday-bound security for most of the well-known types of generalized Feistel networks: (1) unbalanced Feistel networks, where the n-bit to m-bit round functions ...
Viet Tung Hoang, Phillip Rogaway
ICIP
2005
IEEE
16 years 5 months ago
Improving frequency domain super-resolution via undersampling model
The super-resolution problem is considered using a meansquared error minimizing solution of a generalized undersampling model in this non-iterative frequency domain approach. Whil...
Ryan S. Prendergast, Truong Q. Nguyen