Search Results for author: Jia-Qi Yang

Found 8 papers, 5 papers with code

JobFormer: Skill-Aware Job Recommendation with Semantic-Enhanced Transformer

no code implementations5 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.

Click-Through Rate Prediction Representation Learning

Learning Operators with Stochastic Gradient Descent in General Hilbert Spaces

no code implementations7 Feb 2024 Lei Shi, Jia-Qi Yang

This study investigates leveraging stochastic gradient descent (SGD) to learn operators between general Hilbert spaces.

Operator learning valid

RE-SORT: Removing Spurious Correlation in Multilevel Interaction for CTR Prediction

1 code implementation26 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.

Click-Through Rate Prediction Recommendation Systems +1

Generalized Delayed Feedback Model with Post-Click Information in Recommender Systems

1 code implementation1 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.

Recommendation Systems

RID-Noise: Towards Robust Inverse Design under Noisy Environments

1 code implementation7 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.

Robust Design

Capturing Delayed Feedback in Conversion Rate Prediction via Elapsed-Time Sampling

1 code implementation6 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.

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