2 citations · 3 across the 6 of their papers we have counts for
6 papers
THUIR at WSDM Cup 2023 Task 1: Unbiased Learning to Rank
Jia Chen, Haitao Li, Weihang Su +2
This paper introduces the approaches we have used to participate in the WSDM Cup 2023 Task 1: Unbiased Learning to Rank. In brief, we have attempted a combination of both tradition…
A Unified and Efficient Coordinating Framework for Autonomous DBMS Tuning
Xinyi Zhang, Zhuo Chang, Hong Wu +5
Recently using machine learning (ML) based techniques to optimize modern database management systems has attracted intensive interest from both industry and academia. With an objec…
Towards Better Web Search Performance: Pre-training, Fine-tuning and Learning to Rank
Haitao Li, Jia Chen, Weihang Su +2
This paper describes the approach of the THUIR team at the WSDM Cup 2023 Pre-training for Web Search task. This task requires the participant to rank the relevant documents for eac…
An Adam-enhanced Particle Swarm Optimizer for Latent Factor Analysis
Jia Chen, Renyu Zhang, Yuanyi Liu
Digging out the latent information from large-scale incomplete matrices is a key issue with challenges. The Latent Factor Analysis (LFA) model has been investigated in depth to an…
A Dynamic-Neighbor Particle Swarm Optimizer for Accurate Latent Factor Analysis
Jia Chen, Yixian Chun, Yuanyi Liu +2
High-Dimensional and Incomplete matrices, which usually contain a large amount of valuable latent information, can be well represented by a Latent Factor Analysis model. The perfor…
An Adam-adjusting-antennae BAS Algorithm for Refining Latent Factors
Yuanyi Liu, Jia Chen, Di Wu
Extracting the latent information in high-dimensional and incomplete matrices is an important and challenging issue. The Latent Factor Analysis (LFA) model can well handle the high…