Generalization Bounds for Set-to-Set Matching with Negative Sampling
- URL: http://arxiv.org/abs/2302.12991v1
- Date: Sat, 25 Feb 2023 05:05:59 GMT
- Title: Generalization Bounds for Set-to-Set Matching with Negative Sampling
- Authors: Masanari Kimura
- Abstract summary: The problem of matching two sets of multiple elements, namely set-to-set matching, has received a great deal of attention in recent years.
This paper aims to perform a generalization error analysis in set-to-set matching to reveal the behavior of the model in that task.
- Score: 2.3859169601259347
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: The problem of matching two sets of multiple elements, namely set-to-set
matching, has received a great deal of attention in recent years. In
particular, it has been reported that good experimental results can be obtained
by preparing a neural network as a matching function, especially in complex
cases where, for example, each element of the set is an image. However,
theoretical analysis of set-to-set matching with such black-box functions is
lacking. This paper aims to perform a generalization error analysis in
set-to-set matching to reveal the behavior of the model in that task.
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