19 citations · 38 across the 11 of their papers we have counts for
11 papers
STAN: Stage-Adaptive Network for Multi-Task Recommendation by Learning User Lifecycle-Based Representation
Wanda Li, Wenhao Zheng, Xuanji Xiao +1
Recommendation systems play a vital role in many online platforms, with their primary objective being to satisfy and retain users. As directly optimizing user retention is challeng…
Robust Image Ordinal Regression with Controllable Image Generation
Yi Cheng, Haochao Ying, Renjun Hu +5
Image ordinal regression has been mainly studied along the line of exploiting the order of categories. However, the issues of class imbalance and category overlap that are very com…
Breaking the Curse of Knowledge: Towards Effective Multimodal Recommendation using Knowledge Soft Integration
Kai Ouyang, Chen Tang, Zenghao Chai +4
A critical challenge in contemporary recommendation systems lies in effectively leveraging multimodal content to enhance recommendation personalization. Although various solutions…
Click-aware Structure Transfer with Sample Weight Assignment for Post-Click Conversion Rate Estimation
Kai Ouyang, Wenhao Zheng, Chen Tang +2
Post-click Conversion Rate (CVR) prediction task plays an essential role in industrial applications, such as recommendation and advertising. Conventional CVR methods typically suff…
PNM: Pixel Null Model for General Image Segmentation
Han Zhang, Zihao Zhang, Wenhao Zheng +1
A major challenge in image segmentation is classifying object boundaries. Recent efforts propose to refine the segmentation result with boundary masks. However, models are still pr…
A Deep Learning Approach to Predicting Ventilator Parameters for Mechanically Ventilated Septic Patients
Zhijun Zeng, Zhen Hou, Ting Li +10
We develop a deep learning approach to predicting a set of ventilator parameters for a mechanically ventilated septic patient using a long and short term memory (LSTM) recurrent ne…
Modeling Heterogeneous Statistical Patterns in High-dimensional Data by Adversarial Distributions: An Unsupervised Generative Framework
Han Zhang, Wenhao Zheng, Charley Chen +4
Since the label collecting is prohibitive and time-consuming, unsupervised methods are preferred in applications such as fraud detection. Meanwhile, such applications usually requi…
Multi-label Zero-shot Classification by Learning to Transfer from External Knowledge
He Huang, Yuanwei Chen, Wei Tang +4
Multi-label zero-shot classification aims to predict multiple unseen class labels for an input image. It is more challenging than its single-label counterpart. On one hand, the unc…
Deep Time-Stream Framework for Click-Through Rate Prediction by Tracking Interest Evolution
Shu-Ting Shi, Wenhao Zheng, Jun Tang +4
Click-through rate (CTR) prediction is an essential task in industrial applications such as video recommendation. Recently, deep learning models have been proposed to learn the rep…
Distributed Deep Forest and its Application to Automatic Detection of Cash-out Fraud
Ya-Lin Zhang, Jun Zhou, Wenhao Zheng +10
Internet companies are facing the need for handling large-scale machine learning applications on a daily basis and distributed implementation of machine learning algorithms which c…
Code Attention: Translating Code to Comments by Exploiting Domain Features
Wenhao Zheng, Hong-Yu Zhou, Ming Li +1
Appropriate comments of code snippets provide insight for code functionality, which are helpful for program comprehension. However, due to the great cost of authoring with the comm…