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@@ -52,6 +52,8 @@ Google 的 Wide & Deep 模型,论文将模型用于推荐系统中,但也可
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一篇比较简单但是全面的CTR预估的文章,有一定实用性
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* [Practical Lessons from Predicting Clicks on Ads at Facebook.pdf](https://github.com/wzhe06/Ad-papers/blob/master/CTR%20Prediction/Practical%20Lessons%20from%20Predicting%20Clicks%20on%20Ads%20at%20Facebook.pdf) <br />
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Facebook的一篇非常出名的文章,GBDT+LR/FM解决CTR预估问题,工程性很强
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* [Bid-aware Gradient Descent for Unbiased Learning with Censored Data in Display Advertising.pdf](https://github.com/wzhe06/Ad-papers/blob/master/CTR%20Prediction/Bid-aware%20Gradient%20Descent%20for%20Unbiased%20Learning%20with%20Censored%20Data%20in%20Display%20Advertising.pdf)<br />
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RTB 中训练 CTR 模型数据集是赢得出价的广告,预测时的样本却是所有候选的广告,也就是训练集和测试集的分布不一致,这篇文章就是要消除这样的 bias
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### Topic Model
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话题模型相关文章,PLSA,LDA,进行广告Context特征提取,创意优化经常会用到Topic Model

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