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» Machine Learning by Function Decomposition
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ML
2008
ACM
110views Machine Learning» more  ML 2008»
14 years 10 months ago
A theory of learning with similarity functions
Kernel functions have become an extremely popular tool in machine learning, with an attractive theory as well. This theory views a kernel as implicitly mapping data points into a ...
Maria-Florina Balcan, Avrim Blum, Nathan Srebro
ICML
2005
IEEE
16 years 19 days ago
Learning to rank using gradient descent
We investigate using gradient descent methods for learning ranking functions; we propose a simple probabilistic cost function, and we introduce RankNet, an implementation of these...
Christopher J. C. Burges, Tal Shaked, Erin Renshaw...
ML
2000
ACM
157views Machine Learning» more  ML 2000»
14 years 11 months ago
A Multistrategy Approach to Classifier Learning from Time Series
We present an approach to inductive concept learning using multiple models for time series. Our objective is to improve the efficiency and accuracy of concept learning by decomposi...
William H. Hsu, Sylvian R. Ray, David C. Wilkins
KI
2008
Springer
14 years 11 months ago
A Drum Machine That Learns to Groove
Music production relies increasingly on advanced hardware and software tools that makes the creative process more flexible and versatile. The advancement of these tools helps reduc...
Axel Tidemann, Yiannis Demiris
CORR
2004
Springer
140views Education» more  CORR 2004»
14 years 11 months ago
Integrating Defeasible Argumentation and Machine Learning Techniques
The field of machine learning (ML) is concerned with the question of how to construct algorithms that automatically improve with experience. In recent years many successful ML app...
Sergio Alejandro Gómez, Carlos Iván ...