LGFeb 22, 2017

Training a Subsampling Mechanism in Expectation

arXiv:1702.06914v32 citations
Originality Synthesis-oriented
AI Analysis

This work addresses a methodological challenge in machine learning for researchers, but it is incremental as it focuses on a specific mechanism with limited testing.

The authors tackled the problem of training a subsampling mechanism for sequences by computing its expected output to enable standard backpropagation, and they tested it on a toy problem while noting its shortcomings.

We describe a mechanism for subsampling sequences and show how to compute its expected output so that it can be trained with standard backpropagation. We test this approach on a simple toy problem and discuss its shortcomings.

Code Implementations1 repo
Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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