no code implementations • EMNLP 2020 • Pratik Jawanpuria, Mayank Meghwanshi, Bamdev Mishra
Recent progress on unsupervised learning of cross-lingual embeddings in bilingual setting has given impetus to learning a shared embedding space for several languages without any supervision.
no code implementations • ACL 2020 • Pratik Jawanpuria, Mayank Meghwanshi, Bamdev Mishra
We propose a novel manifold based geometric approach for learning unsupervised alignment of word embeddings between the source and the target languages.
no code implementations • 18 Mar 2019 • Pratik Jawanpuria, Mayank Meghwanshi, Bamdev Mishra
While the hyperbolic manifold is well-studied in the literature, it has gained interest in the machine learning and natural language processing communities lately due to its usefulness in modeling continuous hierarchies.
1 code implementation • 3 Oct 2018 • Mayank Meghwanshi, Pratik Jawanpuria, Anoop Kunchukuttan, Hiroyuki Kasai, Bamdev Mishra
In this paper, we introduce McTorch, a manifold optimization library for deep learning that extends PyTorch.