Steven Schockaert

Modelling Semantic Categories Using Conceptual Neighborhood

2020 · Proceedings of the AAAI Conference on Artificial Intelligence

While many methods for learning vector space embeddings have been proposed in the field of Natural Language Processing, these methods typically do not distinguish between categories and individuals. Intuitively, if individuals are represented as vectors, …

Few-shot Image Classification with Multi-Facet Prototypes

2021 · Open Access at Essex (University of Essex)

The aim of few-shot learning (FSL) is to learn how to recognize image categories from a small number of training examples. A central challenge is that the available training examples are normally insufficient to determine …

Jointly Learning Word Embeddings and Latent Topics

2017

Word embedding models such as Skip-gram learn a vector-space representation for each word, based on the local word collocation patterns that are observed in a text corpus. Latent topic models, on the other hand, take …