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A Comparison of Different Loss Computations in Siamese Networks for Authorship Verification
(Springer, 2023)
In this study, we consider the author verification problem as a binary
classification problem where the aim is to identify whether the two inputs belong to
the same author or not. For this task, we have used several ...
Novel Surrogate Measures Based on a Similarity Network for Neural Architecture Search
(IEEE, 2023)
We propose two novel surrogate measures to predict the validation accuracy of the classification
produced by a given neural architecture, thus eliminating the need to train it, in order to speed up neural
architecture ...
Triplet MAML for Few-shot Classification Problems
(Springer, 2023)
In this study, we propose a TripletMAML algorithm as an extension to Model-Agnostic Meta-Learning (MAML) which is the most widely-used optimization-based meta-learning algorithm. We approach MAML from a metric-learning ...