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Learning Distributed Word Representations for Natural Logic Reasoning
Samuel R. Bowman, Christopher Potts, Christopher D. Manning
Natural logic offers a powerful relational conception of meaning that is a natural counterpart to distributed semantic representations, which have proven valuable in a wide range o…
Recursive Neural Networks Can Learn Logical Semantics
Samuel R. Bowman, Christopher Potts, Christopher D. Manning
Tree-structured recursive neural networks (TreeRNNs) for sentence meaning have been successful for many applications, but it remains an open question whether the fixed-length repre…
Relaxations for inference in restricted Boltzmann machines
Sida I. Wang, Roy Frostig, Percy Liang +1
We propose a relaxation-based approximate inference algorithm that samples near-MAP configurations of a binary pairwise Markov random field. We experiment on MAP inference tasks in…