5 citations · 13 across the 5 of their papers we have counts for
5 papers
CDR-Adapter: Learning Adapters to Dig Out More Transferring Ability for Cross-Domain Recommendation Models
Yanyu Chen, Yao Yao, Wai Kin Victor Chan +4
Data sparsity and cold-start problems are persistent challenges in recommendation systems. Cross-domain recommendation (CDR) is a promising solution that utilizes knowledge from th…
i-Razor: A Differentiable Neural Input Razor for Feature Selection and Dimension Search in DNN-Based Recommender Systems
Yao Yao, Bin Liu, Haoxun He +4
Input features play a crucial role in DNN-based recommender systems with thousands of categorical and continuous fields from users, items, contexts, and interactions. Noisy feature…
CLS: Cross Labeling Supervision for Semi-Supervised Learning
Yao Yao, Junyi Shen, Jin Xu +2
It is well known that the success of deep neural networks is greatly attributed to large-scale labeled datasets. However, it can be extremely time-consuming and laborious to collec…
Sample Efficient Reinforcement Learning via Model-Ensemble Exploration and Exploitation
Yao Yao, Li Xiao, Zhicheng An +2
Model-based deep reinforcement learning has achieved success in various domains that require high sample efficiencies, such as Go and robotics. However, there are some remaining is…
IGrow: A Smart Agriculture Solution to Autonomous Greenhouse Control
Xiaoyan Cao, Yao Yao, Lanqing Li +8
Agriculture is the foundation of human civilization. However, the rapid increase of the global population poses a challenge on this cornerstone by demanding more food. Modern auton…