20 citations · 38 across the 8 of their papers we have counts for
8 papers
Bridging the Gap Between Semantic and User Preference Spaces for Multi-modal Music Representation Learning
Xiaofeng Pan, Jing Chen, Haitong Zhang +4
Recent works of music representation learning mainly focus on learning acoustic music representations with unlabeled audios or further attempt to acquire multi-modal music represen…
DPAN: Dynamic Preference-based and Attribute-aware Network for Relevant Recommendations
Wei Dai, Yingmin Su, Xiaofeng Pan
In e-commerce platforms, the relevant recommendation is a unique scenario providing related items for a trigger item that users are interested in. However, users' preferences for t…
FAN: Fatigue-Aware Network for Click-Through Rate Prediction in E-commerce Recommendation
Ming Li, Naiyin Liu, Xiaofeng Pan +5
Since clicks usually contain heavy noise, increasing research efforts have been devoted to modeling implicit negative user behaviors (i.e., non-clicks). However, they either rely o…
MetaCVR: Conversion Rate Prediction via Meta Learning in Small-Scale Recommendation Scenarios
Xiaofeng Pan, Ming Li, Jing Zhang +5
Different from large-scale platforms such as Taobao and Amazon, CVR modeling in small-scale recommendation scenarios is more challenging due to the severe Data Distribution Fluctua…
MOEF: Modeling Occasion Evolution in Frequency Domain for Promotion-Aware Click-Through Rate Prediction
Xiaofeng Pan, Yibin Shen, Jing Zhang +5
Promotions are becoming more important and prevalent in e-commerce to attract customers and boost sales, leading to frequent changes of occasions, which drives users to behave diff…
ANL: Anti-Noise Learning for Cross-Domain Person Re-Identification
Hongliang Zhang, Shoudong Han, Xiaofeng Pan +1
Due to the lack of labels and the domain diversities, it is a challenge to study person re-identification in the cross-domain setting. An admirable method is to optimize the target…
MAT: Motion-Aware Multi-Object Tracking
Shoudong Han, Piao Huang, Hongwei Wang +4
Modern multi-object tracking (MOT) systems usually model the trajectories by associating per-frame detections. However, when camera motion, fast motion, and occlusion challenges oc…
Multi-Level Deep Cascade Trees for Conversion Rate Prediction in Recommendation System
Hong Wen, Jing Zhang, Quan Lin +2
Developing effective and efficient recommendation methods is very challenging for modern e-commerce platforms. Generally speaking, two essential modules named "Click-Through Rate P…