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pro vyhledávání: '"Hay, Guy"'
Autor:
Hay, Guy, Sharon, Nir
This paper addresses the problem of accurately estimating a function on one domain when only its discrete samples are available on another domain. To answer this challenge, we utilize a neural network, which we train to incorporate prior knowledge of
Externí odkaz:
http://arxiv.org/abs/2405.10563
Autor:
Hay, Guy, Volk, Ohad
High-dimensional imbalanced data poses a machine learning challenge. In the absence of sufficient or high-quality labels, unsupervised feature selection methods are crucial for the success of subsequent algorithms. Therefore, we introduce a Marginal
Externí odkaz:
http://arxiv.org/abs/2311.17795
Autor:
Hay, Guy, Liberman, Pablo
We consider a self-supervised approach to anomaly detection in tabular data. Random transformations are applied to the data, and then each transformation is identified based on its output. These predicted transformations are used to identify anomalie
Externí odkaz:
http://arxiv.org/abs/2311.11018