no code implementations • 5 Apr 2024 • Zhihao Guan, Jia-Qi Yang, Yang Yang, HengShu Zhu, Wenjie Li, Hui Xiong
Moreover, we adopt a two-stage learning strategy for skill-aware recommendation, in which we utilize the skill distribution to guide JD representation learning in the recall stage, and then combine the user profiles for final prediction in the ranking stage.
no code implementations • 7 Feb 2024 • Lei Shi, Jia-Qi Yang
This study investigates leveraging stochastic gradient descent (SGD) to learn operators between general Hilbert spaces.
1 code implementation • 26 Sep 2023 • Songli Wu, Liang Du, Jia-Qi Yang, Yuai Wang, De-Chuan Zhan, Shuang Zhao, Zixun Sun
Click-through rate (CTR) prediction is a critical task in recommendation systems, serving as the ultimate filtering step to sort items for a user.
no code implementations • 8 Jun 2023 • Jia-Qi Yang, Chenglei Dai, OU Dan, Ju Huang, De-Chuan Zhan, Qingwen Liu, Xiaoyi Zeng, Yang Yang
To this end, we propose a recommendation-aware image pre-training method that can learn visual features from user click histories.
1 code implementation • 30 May 2023 • Jia-Qi Yang, Yucheng Xu, Jia-Lei Shen, Kebin Fan, De-Chuan Zhan, Yang Yang
These obstacles prevent AI researchers from developing specialized methods for scientific designs.
1 code implementation • 1 Jun 2022 • Jia-Qi Yang, De-Chuan Zhan
We propose a generalized delayed feedback model (GDFM) that unifies both post-click behaviors and early conversions as stochastic post-click information, which could be utilized to train GDFM in a streaming manner efficiently.
1 code implementation • 7 Dec 2021 • Jia-Qi Yang, Ke-Bin Fan, Hao Ma, De-Chuan Zhan
We also define a sample-wise weight, which can be used in the maximum weighted likelihood estimation of an inverse model based on a cINN.
1 code implementation • 6 Dec 2020 • Jia-Qi Yang, Xiang Li, Shuguang Han, Tao Zhuang, De-Chuan Zhan, Xiaoyi Zeng, Bin Tong
To strike a balance in this trade-off, we propose Elapsed-Time Sampling Delayed Feedback Model (ES-DFM), which models the relationship between the observed conversion distribution and the true conversion distribution.