Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Gromov-Wasserstein Alignment of Word Embedding Spaces   Cross-lingual or cross-domain correspondences play key roles in tasks ranging
from machine translation to transfer learning. Recently, purely unsupervised
methods operating on monolingual embeddings have become effective alignment
tools. Current state-of-the-art methods, however, involve multiple steps,
including heuristic post-hoc refinement strategies. In this paper, we cast the
correspondence problem directly as an optimal transport (OT) problem, building
on the idea that word embeddings arise from metric recovery algorithms. Indeed,
we exploit the Gromov-Wasserstein distance that measures how similarities
between pairs of words relate across languages. We show that our OT objective
can be estimated efficiently, requires little or no tuning, and results in
performance comparable with the state-of-the-art in various unsupervised word
translation tasks.

21
The categories of this paper are: adap-org
28
The categories of this paper are: alg-geom
29
The categories of this paper are: funct-an
5
The categories of this paper are: gr-qc
2
The categories of this paper are: math
30
The categories of this paper are: q-alg
8
The categories of this paper are: hep-ex
26
The categories of this paper are: bayes-an
15
The categories of this paper are: nucl-ex
16
The categories of this paper are: stat
34
The categories of this paper are: chem-ph
12
The categories of this paper are: nucl-th
20
The categories of this paper are: acc-phys
10
The categories of this paper are: q-bio
27
The categories of this paper are: comp-gas
36
The categories of this paper are: cmp-lg