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Learning Reductions That Really Work
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AI
DOI：10.1109/JPROC.2015.2494118.png)
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摘要
En 中文
In this paper, we provide a summary of the mathematical and computational techniques that have enabled learning reductions to effectively address a wide class of tasks, and show that this approach to solving machine learning problems can be broadly useful. Our work is instantiated and tested in a machine learning library, Vowpal Wabbit, to prove that the techniques discussed here are fully viable in practice.
Keyword:
Learning systems
machine learning
prediction methods
期刊
IF:
25.9
论文数:
9.9K
被引数:
4.5W
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Gradient-based learning applied to document recognition基于梯度的学习在文档识别中的应用.png)
PROCEEDINGS OF THE IEEE
PROCEEDINGS OF THE IEEEIF25.9
PREAI
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