1 INTRODUCTION

2 LEARNING STRATEGIES FOR MULTI-STEP FORECASTING  
2.1 Iterative Multi-step Estimation  
2.2 Direct Multi-step Estimation  
2.3 Comparison of IMS and DMS  
2.4 Boosting Strategy  
2.5 Scheduled Sampling  

3 CLASSICAL METHODS FOR STSF  
3.1 Feature-based Methods  
3.2 State Space Models  
3.3 Gaussian Process  
3.4 Remarks  

4 DEEP LEARNING METHODS FOR STSF  
4.1 Preliminaries  
4.2 Deep Temporal Generative Models  
4.3 FNN and RNN based Models  
4.4 Remarks  

5 SUMMARY AND FUTURE WORKS