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Found 7 papers, 1 papers with code
Synthetic, yet natural: Properties of WordNet random walk corpora and the impact of rare words on embedding performance
Creating word embeddings that reflect semantic relationships encoded in lexical knowledge resources is an open challenge.
Mutual Information Decay Curves and Hyper-Parameter Grid Search Design for Recurrent Neural Architectures
We present an approach to design the grid searches for hyper-parameter optimization for recurrent neural architectures.
English WordNet Random Walk Pseudo-Corpora
Our WordNet taxonomic random walk implementation allows the exploration of different random walk hyperparameters and the generation of a variety of different pseudo-corpora.
Multi-Element Long Distance Dependencies: Using SPk Languages to Explore the Characteristics of Long-Distance Dependencies
In order to successfully model Long Distance Dependencies (LDDs) it is necessary to understand the full-range of the characteristics of the LDDs exhibited in a target dataset.
Generating Diverse and Meaningful Captions
Image Captioning is a task that requires models to acquire a multi-modal understanding of the world and to express this understanding in natural language text.
Understanding Recurrent Neural Architectures by Analyzing and Synthesizing Long Distance Dependencies in Benchmark Sequential Datasets
In this paper, we presentdetailed analysis of the dependency decay curve exhibited by various datasets.
Using Regular Languages to Explore the Representational Capacity of Recurrent Neural Architectures
However, one of the drawbacks of existing datasets is the lack of experimental control with regards to the presence and/or degree of LDDs.
