4 citations · 6 across the 5 of their papers we have counts for
8 papers
AutoTS: Automatic Time Series Forecasting Model Design Based on Two-Stage Pruning
Chunnan Wang, Xingyu Chen, Chengyue Wu +1
Automatic Time Series Forecasting (TSF) model design which aims to help users to efficiently design suitable forecasting model for the given time series data scenarios, is a novel…
TPAD: Identifying Effective Trajectory Predictions Under the Guidance of Trajectory Anomaly Detection Model
Chunnan Wang, Chen Liang, Xiang Chen +1
Trajectory Prediction (TP) is an important research topic in computer vision and robotics fields. Recently, many stochastic TP models have been proposed to deal with this problem a…
Auto-STGCN: Autonomous Spatial-Temporal Graph Convolutional Network Search Based on Reinforcement Learning and Existing Research Results
Chunnan Wang, Kaixin Zhang, Hongzhi Wang +1
In recent years, many spatial-temporal graph convolutional network (STGCN) models are proposed to deal with the spatial-temporal network data forecasting problem. These STGCN model…
Multi-Objective Neural Architecture Search Based on Diverse Structures and Adaptive Recommendation
Chunnan Wang, Hongzhi Wang, Guosheng Feng +1
The search space of neural architecture search (NAS) for convolutional neural network (CNN) is huge. To reduce searching cost, most NAS algorithms use fixed outer network level str…
Auto-CASH: Autonomous Classification Algorithm Selection with Deep Q-Network
Tianyu Mu, Hongzhi Wang, Chunnan Wang +1
The great amount of datasets generated by various data sources have posed the challenge to machine learning algorithm selection and hyperparameter configuration. For a specific mac…
Automatic Hyper-Parameter Optimization Based on Mapping Discovery from Data to Hyper-Parameters
Bozhou Chen, Kaixin Zhang, Longshen Ou +3
Machine learning algorithms have made remarkable achievements in the field of artificial intelligence. However, most machine learning algorithms are sensitive to the hyper-paramete…