Ying Fan

How to Solve Contextual Goal-Oriented Problems with Offline Datasets?

2024 · arXiv (Cornell University)

We present a novel method, Contextual goal-Oriented Data Augmentation (CODA), which uses commonly available unlabeled trajectories and context-goal pairs to solve Contextual Goal-Oriented (CGO) problems. By carefully constructing an action-augmented MDP that is equivalent to …

Deep Interest Evolution Network for Click-Through Rate Prediction

2019 · Proceedings of the AAAI Conference on Artificial Intelligence

Click-through rate (CTR) prediction, whose goal is to estimate the probability of a user clicking on the item, has become one of the core tasks in the advertising system. For CTR prediction model, it is …

Search-based User Interest Modeling with Lifelong Sequential Behavior Data for Click-Through Rate Prediction

2020

Rich user behavior data has been proven to be of great value for click-through rate prediction tasks, especially in industrial applications such as recommender systems and online advertising. Both industry and academy have paid much …