193 citations · 784 across the 42 of their papers we have counts for
13 papers · 1 filter
Action Candidate Based Clipped Double Q-learning for Discrete and Continuous Action Tasks
Haobo Jiang, Jin Xie, Jian Yang
Double Q-learning is a popular reinforcement learning algorithm in Markov decision process (MDP) problems. Clipped Double Q-learning, as an effective variant of Double Q-learning,…
Spatial-Temporal Tensor Graph Convolutional Network for Traffic Prediction
Xuran Xu, Tong Zhang, Chunyan Xu +2
Accurate traffic prediction is crucial to the guidance and management of urban traffics. However, most of the existing traffic prediction models do not consider the computational b…
Contrastive and Generative Graph Convolutional Networks for Graph-based Semi-Supervised Learning
Sheng Wan, Shirui Pan, Jian Yang +1
Graph-based Semi-Supervised Learning (SSL) aims to transfer the labels of a handful of labeled data to the remaining massive unlabeled data via a graph. As one of the most popular…
Graph Wasserstein Correlation Analysis for Movie Retrieval
Xueya Zhang, Tong Zhang, Xiaobin Hong +2
Movie graphs play an important role to bridge heterogenous modalities of videos and texts in human-centric retrieval. In this work, we propose Graph Wasserstein Correlation Analysi…
Network Cooperation with Progressive Disambiguation for Partial Label Learning
Yao Yao, Chen Gong, Jiehui Deng +1
Partial Label Learning (PLL) aims to train a classifier when each training instance is associated with a set of candidate labels, among which only one is correct but is not accessi…
Graph Inference Learning for Semi-supervised Classification
Chunyan Xu, Zhen Cui, Xiaobin Hong +3
In this work, we address semi-supervised classification of graph data, where the categories of those unlabeled nodes are inferred from labeled nodes as well as graph structures. Re…