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ICML
2004
IEEE
16 years 5 months ago
The Bayesian backfitting relevance vector machine
Traditional non-parametric statistical learning techniques are often computationally attractive, but lack the same generalization and model selection abilities as state-of-the-art...
Aaron D'Souza, Sethu Vijayakumar, Stefan Schaal
BIRTHDAY
1997
Springer
15 years 8 months ago
The Job Assignment Problem: A Study in Parallel and Distributed Machine Learning
This article describes a parallel and distributed machine learning approach to a basic variant of the job assignment problem. The approach is in the line of the multiagent learning...
Gerhard Weiß
ICANN
2005
Springer
15 years 10 months ago
Reducing the Effect of Out-Voting Problem in Ensemble Based Incremental Support Vector Machines
Although Support Vector Machines (SVMs) have been successfully applied to solve a large number of classification and regression problems, they suffer from the catastrophic forgetti...
Zeki Erdem, Robi Polikar, Fikret S. Gürgen, N...
CHI
2008
ACM
16 years 5 months ago
Investigating statistical machine learning as a tool for software development
As statistical machine learning algorithms and techniques continue to mature, many researchers and developers see statistical machine learning not only as a topic of expert study,...
Kayur Patel, James Fogarty, James A. Landay, Bever...
JMLR
2006
108views more  JMLR 2006»
15 years 4 months ago
The Interplay of Optimization and Machine Learning Research
The fields of machine learning and mathematical programming are increasingly intertwined. Optimization problems lie at the heart of most machine learning approaches. The Special T...
Kristin P. Bennett, Emilio Parrado-Hernánde...