An In-Depth Comparison of Neural and Probabilistic Tree Models for Learning-to-rank.
Haonan TanKaiyu YangHaitao YuPublished in: ECIR (3) (2024)
Keyphrases
- learning to rank
- tree models
- ranking functions
- information retrieval
- loss function
- ranking svm
- human pose estimation
- document retrieval
- collaborative filtering
- learning to rank algorithms
- test collection
- supervised learning
- probabilistic model
- tree structure
- efficient learning
- depth images
- bayesian networks
- regression model
- retrieval systems
- generative model
- depth map
- depth information
- keywords
- computer vision
- data sets