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RECOMB
2005
Springer
16 years 23 days ago
Learning Interpretable SVMs for Biological Sequence Classification
Background: Support Vector Machines (SVMs) ? using a variety of string kernels ? have been successfully applied to biological sequence classification problems. While SVMs achieve ...
Christin Schäfer, Gunnar Rätsch, Sö...
112
Voted
EUROCRYPT
2003
Springer
15 years 5 months ago
Facts and Myths of Enigma: Breaking Stereotypes
In spite of a relatively large number of publications about breaking Enigma by the Allies before and during the World War II, this subject remains relatively unknown not only to th...
Kris Gaj, Arkadiusz Orlowski
IJCV
2008
192views more  IJCV 2008»
15 years 14 days ago
Learning to Locate Informative Features for Visual Identification
Object identification (OID) is specialized recognition where the category is known (e.g. cars) and the algorithm recognizes an object's exact identity (e.g. Bob's BMW). ...
Andras Ferencz, Erik G. Learned-Miller, Jitendra M...
142
Voted
ALT
1999
Springer
15 years 4 months ago
Extended Stochastic Complexity and Minimax Relative Loss Analysis
We are concerned with the problem of sequential prediction using a givenhypothesis class of continuously-manyprediction strategies. An e ectiveperformance measure is the minimax re...
Kenji Yamanishi
96
Voted
EPIA
2003
Springer
15 years 5 months ago
Adaptation to Drifting Concepts
Most of supervised learning algorithms assume the stability of the target concept over time. Nevertheless in many real-user modeling systems, where the data is collected over an ex...
Gladys Castillo, João Gama, Pedro Medas