Jul 26, 2019 · In this paper, we show how to address both problems by designing targeted regularization strategies, which are able to minimize the number of ...

In this paper we show how to address both problems by designing targeted regularization strategies, able to minimize the number of connections and neurons of ...

Aug 3, 2020 · and structured regularisations to the quaternion domain. In the authors' experimental evaluation, they show that these tailored strategies ...

Jun 30, 2020 · Abstract: In recent years, hyper-complex deep networks (such as complex-valued and quaternion-valued neural networks – QVNNs) have received ...

In this study, the authors show how to address both problems by designing targeted regularisation strategies, which can minimise the number of connections and ...

Jul 26, 2019 · This paper investigates two extensions of l1 and structured regularization to the quaternion domain and shows that these tailored strategies ...

Nov 30, 2020 · It's helpful not from a theoretical aspect but from a practical one. Weights of a neural net are usually stored as 16 or 32-bit floating ...

Mar 25, 2024 · Abstract—We propose a novel quaternionic time-series com- pression methodology where we divide a long time-series into seg-.

Jul 26, 2019 · In this paper we show how to address both problems by designing targeted regularization strategies, able to minimize the number of connections ...

Jan 4, 2023 · RetroKD : Leveraging Past States for Regularizing Targets in Teacher-Student Learning ... A survey of model compression and acceleration for deep ...