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20212026
most citedA Comprehensive Survey on Data Augmentation

20 citations · 31 across the 31 of their papers we have counts for

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Showing 2021Show all

5 papers · 1 filter

cs.RO2021★ 1 cited

Automated Urban Planning for Reimagining City Configuration via Adversarial Learning: Quantification, Generation, and Evaluation

Dongjie Wang, Yanjie Fu, Kunpeng Liu +3

Urban planning refers to the efforts of designing land-use configurations given a region. However, to obtain effective urban plans, urban experts have to spend much time and effort…

cs.CV2021

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…

cs.LG2021

Efficient Reinforced Feature Selection via Early Stopping Traverse Strategy

Kunpeng Liu, Pengfei Wang, Dongjie Wang +3

In this paper, we propose a single-agent Monte Carlo based reinforced feature selection (MCRFS) method, as well as two efficiency improvement strategies, i.e., early stopping (ES)…

cs.LG2021

Automated Feature-Topic Pairing: Aligning Semantic and Embedding Spaces in Spatial Representation Learning

Dongjie Wang, Kunpeng Liu, David Mohaisen +3

Automated characterization of spatial data is a kind of critical geographical intelligence. As an emerging technique for characterization, Spatial Representation Learning (SRL) use…

cs.AI2021★ 2 cited

Reinforced Imitative Graph Representation Learning for Mobile User Profiling: An Adversarial Training Perspective

Dongjie Wang, Pengyang Wang, Kunpeng Liu +3

In this paper, we study the problem of mobile user profiling, which is a critical component for quantifying users' characteristics in the human mobility modeling pipeline. Human mo…