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Jun, 2018
使用计数草图实现超大规模特征选择
MISSION: Ultra Large-Scale Feature Selection using Count-Sketches
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Amirali Aghazadeh, Ryan Spring, Daniel LeJeune, Gautam Dasarathy, Anshumali Shrivastava...
TL;DR
本文提出 MISSION,一种用于超大规模特征选择的新框架,可以在保持特征的可解释性的同时使用 O(log^2(p)) 的工作内存准确、高效地选择具有数十亿维的真实世界大型数据集上的特征。
Abstract
feature selection
is an important challenge in
machine learning
. It plays a crucial role in the explainability of machine-driven decisions that are rapidly permeating throughout modern society. Unfortunately, the
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