24 citations · 61 across the 12 of their papers we have counts for
6 papers · 1 filter
Sustainable Online Reinforcement Learning for Auto-bidding
Zhiyu Mou, Yusen Huo, Rongquan Bai +4
Recently, auto-bidding technique has become an essential tool to increase the revenue of advertisers. Facing the complex and ever-changing bidding environments in the real-world ad…
Joint Optimization of Ranking and Calibration with Contextualized Hybrid Model
Xiang-Rong Sheng, Jingyue Gao, Yueyao Cheng +6
Despite the development of ranking optimization techniques, pointwise loss remains the dominating approach for click-through rate prediction. It can be attributed to the calibratio…
Visual Encoding and Debiasing for CTR Prediction
Si Chen, Chen Lin, Wanxian Guan +7
Extracting expressive visual features is crucial for accurate Click-Through-Rate (CTR) prediction in visual search advertising systems. Current commercial systems use off-the-shelf…
GBA: A Tuning-free Approach to Switch between Synchronous and Asynchronous Training for Recommendation Model
Wenbo Su, Yuanxing Zhang, Yufeng Cai +9
High-concurrency asynchronous training upon parameter server (PS) architecture and high-performance synchronous training upon all-reduce (AR) architecture are the most commonly dep…
APG: Adaptive Parameter Generation Network for Click-Through Rate Prediction
Bencheng Yan, Pengjie Wang, Kai Zhang +4
In many web applications, deep learning-based CTR prediction models (deep CTR models for short) are widely adopted. Traditional deep CTR models learn patterns in a static manner, i…
Asymptotically Unbiased Estimation for Delayed Feedback Modeling via Label Correction
Yu Chen, Jiaqi Jin, Hui Zhao +4
Alleviating the delayed feedback problem is of crucial importance for the conversion rate(CVR) prediction in online advertising. Previous delayed feedback modeling methods using an…