1 Introduction  
2 Unbiased linear estimation  
2.1 Bias correction by subsampling  
2.2 Rao-Blackwellisation  
2.3 Relative efficiency to GREG  
2.4 Delete-one RB method  
2.5 Monte Carlo RB  
3 Unbiased non-linear learning  
3.1 Design-unbiased ML for survey sampling  
3.2 Subsampling RB and bootstrap aggregating  
3.3 Design consistency  
4 Simulations  
4.1 Simulations with synthetic data  
4.2 Simulations with real data  
5 Summary remarks