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11/11/2020
CAN: Revisiting Feature Co-Action for Click-Through Rate Prediction
Inspired by the success of deep learning, recent industrial Click-Throug...
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06/17/2020
DCAF: A Dynamic Computation Allocation Framework for Online Serving System
Modern large-scale systems such as recommender system and online adverti...
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06/10/2020
Search-based User Interest Modeling with Lifelong Sequential Behavior Data for Click-Through Rate Prediction
Rich user behavior data has been proven to be of great value for click-t...
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09/11/2018
Deep Interest Evolution Network for Click-Through Rate Prediction
Click-through rate (CTR) prediction, whose goal is to estimate the proba...
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02/23/2018
Budget Constrained Bidding by Model-free Reinforcement Learning in Display Advertising
Real-time bidding (RTB) is almost the most important mechanism in online...
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01/08/2018
Learning Tree-based Deep Model for Recommender Systems
We propose a novel recommendation method based on tree. With user behavi...
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11/17/2017
