123 citations · 159 across the 6 of their papers we have counts for
19 papers
AutoLoss: Automated Loss Function Search in Recommendations
Xiangyu Zhao, Haochen Liu, Wenqi Fan +3
Designing an effective loss function plays a crucial role in training deep recommender systems. Most existing works often leverage a predefined and fixed loss function that could l…
Data-Efficient Reinforcement Learning for Malaria Control
Lixin Zou, Long Xia, Linfang Hou +2
Sequential decision-making under cost-sensitive tasks is prohibitively daunting, especially for the problem that has a significant impact on people's daily lives, such as malaria c…
D2A U-Net: Automatic Segmentation of COVID-19 Lesions from CT Slices with Dilated Convolution and Dual Attention Mechanism
Xiangyu Zhao, Peng Zhang, Fan Song +6
Coronavirus Disease 2019 (COVID-19) has caused great casualties and becomes almost the most urgent public health events worldwide. Computed tomography (CT) is a significant screeni…
Contrastive Learning for Label-Efficient Semantic Segmentation
Xiangyun Zhao, Raviteja Vemulapalli, Philip Mansfield +4
Collecting labeled data for the task of semantic segmentation is expensive and time-consuming, as it requires dense pixel-level annotations. While recent Convolutional Neural Netwo…
Object Detection with a Unified Label Space from Multiple Datasets
Xiangyun Zhao, Samuel Schulter, Gaurav Sharma +3
Given multiple datasets with different label spaces, the goal of this work is to train a single object detector predicting over the union of all the label spaces. The practical ben…
Neural Interactive Collaborative Filtering
Lixin Zou, Long Xia, Yulong Gu +4
In this paper, we study collaborative filtering in an interactive setting, in which the recommender agents iterate between making recommendations and updating the user profile base…