Interactive compression refers to the problem of compressing data while sending only the part requested by the user. In this context, the challenge is to perform the extraction in the compressed domain directly. Theoretical results exist, but they assume that the true distribution is known. In practical scenarios instead, the distribution must be estimated. In this paper, we first formulate the model selection problem for interactive compression and show that it requires to estimate the excess rate incurred by mismatched decoding. Then, we propose a new expression to evaluate the excess rate of mismatched decoding in a practical case of interest: when the decoder is the belief propagation algorithm. We also propose a novel experimental setup to validate this closed-form formula. We show a good match for practical interactive compression schemes based on fixed-length Low-Density Parity-Check (LDPC) codes. This new formula is of great importance to perform model and rate selection.

交互式压缩是指仅发送用户请求的部分时压缩数据的问题。在这种情况下，挑战在于直接在压缩域中执行提取。存在理论结果，但他们假设真实分布是已知的。相反，在实际情况下，必须估计分布。在本文中，我们首先提出了交互式压缩的模型选择问题，并表明它需要估计不匹配解码所引起的过剩率。然后，我们提出了一个新的表达式来评估感兴趣的实际情况下的不匹配解码的过多速率：当解码器是置信传播算法时。我们还提出了一种新颖的实验装置来验证该封闭式公式。我们展示了基于固定长度低密度奇偶校验（LDPC）码的实用交互式压缩方案的良好匹配。这个新公式对于执行模型和速率选择非常重要。