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Deep Tree Transductions - A Short Survey
Published 5 Feb 2019 in cs.LG, cs.NE, and stat.ML | (1902.01737v1)
Abstract: The paper surveys recent extensions of the Long-Short Term Memory networks to handle tree structures from the perspective of learning non-trivial forms of isomorph structured transductions. It provides a discussion of modern TreeLSTM models, showing the effect of the bias induced by the direction of tree processing. An empirical analysis is performed on real-world benchmarks, highlighting how there is no single model adequate to effectively approach all transduction problems.
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