Assuming we can estimatep(a|x) accurately, we have followingresults: Lemma 3.1. So the value of yx is determined by the linear equation systemMxyx = ax. Each bin is represented with a 32-dimensional embedding. We found that increasing the number of bins or embedding size could not improve performance significantly. The CVR prediction modelpθ(x) is a feature network followed by a linear classification layer. Specifically,if δj <δj+1,1 j

However,accurate conversion labels arerevealed after along delay,which harms the timeliness ofrecommender systems. Previousliterature concentrates onutilizing early conversions to mitigate such a delayed feedback problem. In this paper, we show that post-click user behaviors are also informative to conversion rate prediction and can beused toimprovetimeliness.

Methods introduced in [4, 19] both fail toeffectively modify text-required attributes, and results are also farfrom satisfactory (see Figure 1).