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ICML
2007
IEEE
14 years 9 months ago
Asymptotic Bayesian generalization error when training and test distributions are different
In supervised learning, we commonly assume that training and test data are sampled from the same distribution. However, this assumption can be violated in practice and then standa...
Keisuke Yamazaki, Klaus-Robert Müller, Masash...
ALT
2002
Springer
14 years 5 months ago
Optimally-Smooth Adaptive Boosting and Application to Agnostic Learning
We describe a new boosting algorithm that is the first such algorithm to be both smooth and adaptive. These two features make possible performance improvements for many learning ...
Dmitry Gavinsky
COLT
2008
Springer
13 years 10 months ago
An Efficient Reduction of Ranking to Classification
This paper describes an efficient reduction of the learning problem of ranking to binary classification. The reduction guarantees an average pairwise misranking regret of at most t...
Nir Ailon, Mehryar Mohri
INFOCOM
2002
IEEE
14 years 1 months ago
Distributed Construction of Connected Dominating Set in Wireless Ad Hoc Networks
—Connected dominating set (CDS) has been proposed as virtual backbone or spine of wireless ad hoc networks. Three distributed approximation algorithms have been proposed in the l...
Peng-Jun Wan, Khaled M. Alzoubi, Ophir Frieder
CORR
2011
Springer
178views Education» more  CORR 2011»
13 years 5 days ago
Online Learning: Stochastic and Constrained Adversaries
Learning theory has largely focused on two main learning scenarios. The first is the classical statistical setting where instances are drawn i.i.d. from a fixed distribution and...
Alexander Rakhlin, Karthik Sridharan, Ambuj Tewari