44 citations · 239 across the 28 of their papers we have counts for
54 papers
Global Convolutional Neural Processes
Xuesong Wang, Lina Yao, Xianzhi Wang +2
The ability to deal with uncertainty in machine learning models has become equally, if not more, crucial to their predictive ability itself. For instance, during the pandemic, gove…
Generative Adversarial Reward Learning for Generalized Behavior Tendency Inference
Xiaocong Chen, Lina Yao, Xianzhi Wang +3
Recent advances in reinforcement learning have inspired increasing interest in learning user modeling adaptively through dynamic interactions, e.g., in reinforcement learning based…
Task Aligned Generative Meta-learning for Zero-shot Learning
Zhe Liu, Yun Li, Lina Yao +2
Zero-shot learning (ZSL) refers to the problem of learning to classify instances from the novel classes (unseen) that are absent in the training set (seen). Most ZSL methods infer…
Generative Inverse Deep Reinforcement Learning for Online Recommendation
Xiaocong Chen, Lina Yao, Aixin Sun +3
Deep reinforcement learning enables an agent to capture user's interest through interactions with the environment dynamically. It has attracted great interest in the recommendation…
Knowledge Adaption for Demand Prediction based on Multi-task Memory Neural Network
Can Li, Lei Bai, Wei Liu +2
Accurate demand forecasting of different public transport modes(e.g., buses and light rails) is essential for public service operation.However, the development level of various mod…
TRec: Sequential Recommender Based On Latent Item Trend Information
Ye Tao, Can Wang, Lina Yao +2
Recommendation system plays an important role in online web applications. Sequential recommender further models user short-term preference through exploiting information from lates…