Compress LSTMs and infer models on the edge

Figure 1: Tishby et. al [1] present the principle of variational information bottleneck to obtain the most concise yet prediction relevant representation based on information theoretic measures.

Continue reading: https://towardsdatascience.com/a-variational-information-bottleneck-vib-based-method-to-compress-sequential-networks-for-human-b559d3a50e30?source=rss—-7f60cf5620c9—4

Source: towardsdatascience.com