Quantizer design for distributed estimation with communication constraints and unknown observation statistics

We consider the problem of quantizer design in a distributed estimation system with communication constraints in the case where only a training sequence is available. Our approach is based on a generalization of regression trees. The look-ahead method that we also propose improves significantly the performance. The final system performs similarly to the one that assumes known statistics.