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ACML
2009
Springer
15 years 8 months ago
Learning Algorithms for Domain Adaptation
A fundamental assumption for any machine learning task is to have training and test data instances drawn from the same distribution while having a sufficiently large number of tra...
Manas A. Pathak, Eric Nyberg
116
Voted
AUSAI
2004
Springer
15 years 9 months ago
A Bayesian Metric for Evaluating Machine Learning Algorithms
How to assess the performance of machine learning algorithms is a problem of increasing interest and urgency as the data mining application of myriad algorithms grows. The standard...
Lucas R. Hope, Kevin B. Korb
107
Voted
FOCM
2008
140views more  FOCM 2008»
15 years 3 months ago
Online Gradient Descent Learning Algorithms
This paper considers the least-square online gradient descent algorithm in a reproducing kernel Hilbert space (RKHS) without explicit regularization. We present a novel capacity i...
Yiming Ying, Massimiliano Pontil
136
Voted
AAAI
2006
15 years 4 months ago
An Efficient Algorithm for Local Distance Metric Learning
Learning application-specific distance metrics from labeled data is critical for both statistical classification and information retrieval. Most of the earlier work in this area h...
Liu Yang, Rong Jin, Rahul Sukthankar, Yi Liu
117
Voted
NIPS
2007
15 years 4 months ago
An online Hebbian learning rule that performs Independent Component Analysis
Independent component analysis (ICA) is a powerful method to decouple signals. Most of the algorithms performing ICA do not consider the temporal correlations of the signal, but o...
Claudia Clopath, André Longtin, Wulfram Ger...