79 citations · 855 across the 98 of their papers we have counts for
Showing 2017 · stat.MLShow all
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stat.ML2017★ 10 cited
Compression-Based Regularization with an Application to Multi-Task Learning
Matías Vera, Leonardo Rey Vega, Pablo Piantanida
This paper investigates, from information theoretic grounds, a learning problem based on the principle that any regularity in a given dataset can be exploited to extract compact fe…
stat.ML2017★ 1 cited
The Multi-layer Information Bottleneck Problem
Qianqian Yang, Pablo Piantanida, Deniz Gündüz
The muti-layer information bottleneck (IB) problem, where information is propagated (or successively refined) from layer to layer, is considered. Based on information forwarded by…