438 citations · 808 across the 8 of their papers we have counts for
8 papers
Improving speech recognition models with small samples for air traffic control systems
Yi Lin, Qin Li, Bo Yang +3
In the domain of air traffic control (ATC) systems, efforts to train a practical automatic speech recognition (ASR) model always faces the problem of small training samples since t…
Non-recurrent Traffic Congestion Detection with a Coupled Scalable Bayesian Robust Tensor Factorization Model
Qin Li, Huachun Tan, Xizhu Jiang +2
Non-recurrent traffic congestion (NRTC) usually brings unexpected delays to commuters. Hence, it is critical to accurately detect and recognize the NRTC in a real-time manner. The…
Platoon trajectories generation: A unidirectional interconnected LSTM-based car following model
Yangxin Lin, Ping Wang, Yang Zhou +3
Car following models have been widely applied and made remarkable achievements in traffic engineering. However, the traffic micro-simulation accuracy of car following models in a p…
ES-CTC: A Deep Neuroevolution Model for Cooperative Intelligent Freeway Traffic Control
Yuankai Wu, Huachun Tan, Zhuxi Jiang +1
Cooperative intelligent freeway traffic control is an important application in intelligent transportation systems, which is expected to improve the mobility of freeway networks. In…
Differential Variable Speed Limits Control for Freeway Recurrent Bottlenecks via Deep Reinforcement learning
Yuankai Wu, Huachun Tan, Bin Ran
Variable speed limits (VSL) control is a flexible way to improve traffic condition,increase safety and reduce emission. There is an emerging trend of using reinforcement learning t…
Short-term traffic flow forecasting with spatial-temporal correlation in a hybrid deep learning framework
Yuankai Wu, Huachun Tan
Deep learning approaches have reached a celebrity status in artificial intelligence field, its success have mostly relied on Convolutional Networks (CNN) and Recurrent Networks. By…
Variational Deep Embedding: An Unsupervised and Generative Approach to Clustering
Zhuxi Jiang, Yin Zheng, Huachun Tan +2
Clustering is among the most fundamental tasks in computer vision and machine learning. In this paper, we propose Variational Deep Embedding (VaDE), a novel unsupervised generative…
A Gradient Descent Algorithm on the Grassman Manifold for Matrix Completion
Raghunandan H. Keshavan, Sewoong Oh
We consider the problem of reconstructing a low-rank matrix from a small subset of its entries. In this paper, we describe the implementation of an efficient algorithm called OptSp…