2 citations · 3 across the 9 of their papers we have counts for
9 papers
Mitigating Popularity Bias in Recommendation with Unbalanced Interactions: A Gradient Perspective
Weijieying Ren, Lei Wang, Kunpeng Liu +3
Recommender systems learn from historical user-item interactions to identify preferred items for target users. These observed interactions are usually unbalanced following a long-t…
Automated Urban Planning aware Spatial Hierarchies and Human Instructions
Dongjie Wang, Kunpeng Liu, Yanyong Huang +3
Traditional urban planning demands urban experts to spend considerable time and effort producing an optimal urban plan under many architectural constraints. The remarkable imaginat…
Group-wise Reinforcement Feature Generation for Optimal and Explainable Representation Space Reconstruction
Dongjie Wang, Yanjie Fu, Kunpeng Liu +2
Representation (feature) space is an environment where data points are vectorized, distances are computed, patterns are characterized, and geometric structures are embedded. Extrac…
Feature and Instance Joint Selection: A Reinforcement Learning Perspective
Wei Fan, Kunpeng Liu, Hao Liu +3
Feature selection and instance selection are two important techniques of data processing. However, such selections have mostly been studied separately, while existing work towards…
Reinforced Imitative Graph Learning for Mobile User Profiling
Dongjie Wang, Pengyang Wang, Yanjie Fu +3
Mobile user profiling refers to the efforts of extracting users' characteristics from mobile activities. In order to capture the dynamic varying of user characteristics for generat…
Deep Human-guided Conditional Variational Generative Modeling for Automated Urban Planning
Dongjie Wang, Kunpeng Liu, Pauline Johnson +3
Urban planning designs land-use configurations and can benefit building livable, sustainable, safe communities. Inspired by image generation, deep urban planning aims to leverage d…