Search Results for author:
Found 3 papers, 2 papers with code
Efficient Sentence Embedding via Semantic Subspace Analysis
Given the fact that word embeddings can capture semantic relationship while semantically similar words tend to form semantic groups in a high-dimensional embedding space, we develop a sentence representation scheme by analyzing semantic subspaces of its constituent words.
Graph Representation Learning: A Survey
Research on graph representation learning has received a lot of attention in recent years since many data in real-world applications come in form of graphs.
Evaluating Word Embedding Models: Methods and Experimental Results
Extensive evaluation on a large number of word embedding models for language processing applications is conducted in this work.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
