Search Results for author:
Found 7 papers, 4 papers with code
DPAN: Dynamic Preference-based and Attribute-aware Network for Relevant Recommendations
In e-commerce platforms, the relevant recommendation is a unique scenario providing related items for a trigger item that users are interested in.
FAN: Fatigue-Aware Network for Click-Through Rate Prediction in E-commerce Recommendation
Then the frequency spectrum is modulated by category information of the target item to model the bias that both the upper bound of fatigue and users' patience is different for different categories.
AIM 2022 Challenge on Super-Resolution of Compressed Image and Video: Dataset, Methods and Results
The homepage of this challenge is at https://github. com/RenYang-home/AIM22_CompressSR.
MetaCVR: Conversion Rate Prediction via Meta Learning in Small-Scale Recommendation Scenarios
At last, we develop an Ensemble Prediction Network (EPN) which incorporates the output of FRN and DMN to make the final CVR prediction.
MOEF: Modeling Occasion Evolution in Frequency Domain for Promotion-Aware Click-Through Rate Prediction
In this paper, we propose a novel CTR model named MOEF for recommendations under frequent changes of occasions.
ANL: Anti-Noise Learning for Cross-Domain Person Re-Identification
Usually, attributed to the domain gaps, the pre-trained source domain model cannot extract appropriate target domain features, which will dramatically affect the clustering performance and the accuracy of pseudo-labels.
MAT: Motion-Aware Multi-Object Tracking
Modern multi-object tracking (MOT) systems usually model the trajectories by associating per-frame detections.
