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20152022
most citedIntelligent Electric Vehicle Charging Recommendation Based on Multi-Agent Reinforcement Learning

97 citations · 457 across the 50 of their papers we have counts for

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Showing 2021Show all

21 papers · 1 filter

cs.CL2021

Hierarchical Heterogeneous Graph Representation Learning for Short Text Classification

Yaqing Wang, Song Wang, Quanming Yao +1

Short text classification is a fundamental task in natural language processing. It is hard due to the lack of context information and labeled data in practice. In this paper, we pr…

cs.CV20215 cited

Generalized Data Weighting via Class-level Gradient Manipulation

Can Chen, Shuhao Zheng, Xi Chen +4

Label noise and class imbalance are two major issues coexisting in real-world datasets. To alleviate the two issues, state-of-the-art methods reweight each instance by leveraging a…

cs.LG202122 cited

SenseMag: Enabling Low-Cost Traffic Monitoring using Non-invasive Magnetic Sensing

Kafeng Wang, Haoyi Xiong, Jie Zhang +3

The operation and management of intelligent transportation systems (ITS), such as traffic monitoring, relies on real-time data aggregation of vehicular traffic information, includi…

cs.LG2021

AgFlow: Fast Model Selection of Penalized PCA via Implicit Regularization Effects of Gradient Flow

Haiyan Jiang, Haoyi Xiong, Dongrui Wu +2

Principal component analysis (PCA) has been widely used as an effective technique for feature extraction and dimension reduction. In the High Dimension Low Sample Size (HDLSS) sett…

cs.LG2021

Exploring the Common Principal Subspace of Deep Features in Neural Networks

Haoran Liu, Haoyi Xiong, Yaqing Wang +3

We find that different Deep Neural Networks (DNNs) trained with the same dataset share a common principal subspace in latent spaces, no matter in which architectures (e.g., Convolu…

cs.LG202111 cited

GeomGCL: Geometric Graph Contrastive Learning for Molecular Property Prediction

Shuangli Li, Jingbo Zhou, Tong Xu +2

Recently many efforts have been devoted to applying graph neural networks (GNNs) to molecular property prediction which is a fundamental task for computational drug and material di…