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89
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CIKM
2008
Springer
15 years 2 months ago
Group-based learning: a boosting approach
This paper points out that many machine learning problems in IR should be and can be formalized in a novel way, referred to as `group-based learning'. In group-based learning...
Weijian Ni, Jun Xu, Hang Li, Yalou Huang
93
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DCC
2006
IEEE
16 years 1 days ago
Compression and Machine Learning: A New Perspective on Feature Space Vectors
The use of compression algorithms in machine learning tasks such as clustering and classification has appeared in a variety of fields, sometimes with the promise of reducing probl...
D. Sculley, Carla E. Brodley
90
Voted
JMLR
2006
80views more  JMLR 2006»
15 years 12 days ago
Using Machine Learning to Guide Architecture Simulation
An essential step in designing a new computer architecture is the careful examination of different design options. It is critical that computer architects have efficient means by ...
Greg Hamerly, Erez Perelman, Jeremy Lau, Brad Cald...
117
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HIS
2007
15 years 1 months ago
Pareto-based Multi-Objective Machine Learning
—Machine learning is inherently a multiobjective task. Traditionally, however, either only one of the objectives is adopted as the cost function or multiple objectives are aggreg...
Yaochu Jin
ECCV
2008
Springer
16 years 2 months ago
Training Hierarchical Feed-Forward Visual Recognition Models Using Transfer Learning from Pseudo-Tasks
Abstract. Building visual recognition models that adapt across different domains is a challenging task for computer vision. While feature-learning machines in the form of hierarchi...
Amr Ahmed, Kai Yu, Wei Xu, Yihong Gong, Eric P. Xi...