Post-click conversion rate (CVR) prediction is an essential task for discovering user interests
and increasing platform revenues in a range of industrial applications. One of the most …

Online travel platforms (OTPs), eg, bookings. com and Ctrip. com, deliver travel experiences
to online users by providing travel-related products. Although much progress has been …

Conversion rate prediction is critical to many online applications such as digital display
advertising. To capture dynamic data distribution, industrial systems often require retraining …

As huge commercial value of the recommender system, there has been growing interest to
improve its performance in recent years. The majority of existing methods have achieved …

Alleviating the delayed feedback problem is of crucial importance for the conversion rate
(CVR) prediction in online advertising. Previous delayed feedback modeling methods using …

In recommendation scenarios, there are two long-standing challenges, ie, selection bias and
data sparsity, which lead to a significant drop in prediction accuracy for both Click-Through …

Predicting conversion rate (eg, the probability that a user will purchase an item) is a
fundamental problem in machine learning based recommender systems. However, accurate …

Conversion rate (CVR) prediction is an essential task for e-commerce platforms. However,
refunds frequently occur after conversion in online shopping systems, which drives us to pay …

The delayed feedback is becoming one of the main obstacles in online advertising due to
the pervasive deployment of the cost-per-conversion display strategy requesting a real-time …

In recent years, multi-task learning models based on deep learning in recommender
systems have attracted increasing attention from researchers in industry and academia …