activity
20172022
most citedImproving Deep Pancreas Segmentation in CT and MRI Images via Recurrent Neural Contextual Learning and Direct Loss Function

130 citations · 195 across the 4 of their papers we have counts for

collaborators

5 papers

cs.IR2022

Learning to Rank For Push Notifications Using Pairwise Expected Regret

Yuguang Yue, Yuanpu Xie, Huasen Wu +4

Listwise ranking losses have been widely studied in recommender systems. However, new paradigms of content consumption present new challenges for ranking methods. In this work we c…

cs.SI20201 cited

Model Size Reduction Using Frequency Based Double Hashing for Recommender Systems

Caojin Zhang, Yicun Liu, Yuanpu Xie +10

Deep Neural Networks (DNNs) with sparse input features have been widely used in recommender systems in industry. These models have large memory requirements and need a huge amount…

cs.CV2018

Photographic Text-to-Image Synthesis with a Hierarchically-nested Adversarial Network

Zizhao Zhang, Yuanpu Xie, Lin Yang

This paper presents a novel method to deal with the challenging task of generating photographic images conditioned on semantic image descriptions. Our method introduces accompanyin…

cs.CV2017130 cited

Improving Deep Pancreas Segmentation in CT and MRI Images via Recurrent Neural Contextual Learning and Direct Loss Function

Jinzheng Cai, Le Lu, Yuanpu Xie +2

Deep neural networks have demonstrated very promising performance on accurate segmentation of challenging organs (e.g., pancreas) in abdominal CT and MRI scans. The current deep le…

cs.CV201764 cited

MDNet: A Semantically and Visually Interpretable Medical Image Diagnosis Network

Zizhao Zhang, Yuanpu Xie, Fuyong Xing +2

The inability to interpret the model prediction in semantically and visually meaningful ways is a well-known shortcoming of most existing computer-aided diagnosis methods. In this…