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We investigate the utility of side information in the context of machine learning and, in particular, in supervised neural networks. Side information can be ...
Nov 10, 2023 · We investigate the utility of side information in the context of machine learning and, in particular, in supervised neural networks.
Abstract. Read online. We investigate the utility of side information in the context of machine learning and, in particular, in supervised neural networks.
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Oct 28, 2015 · Neural nets don't "understand", they are trained. Despite the fancy term, a neural net is simple a regression model on steroid - often high-dimensional.
Jul 20, 2021 · This side information can help the model to generalize better. Modify the neural network to use the additional features as input. Add more ...
Nov 18, 2019 · This concept of learning from some data and correctly applying the gained knowledge on other data is called generalization.
There are many types of artificial neural networks (ANN). Artificial neural networks are computational models inspired by biological neural networks.
Jul 26, 2016 · Neural networks can have a large number of free parameters (the weights and biases between interconnected units) and this gives them the flexibility to fit ...
A neural network can be considered as a simplified computer model of the human brain consisting of several layers of neurons that send signals to other neurons ...
We then describe our new modeling approach, which is a combination of a novel recurrent neural network architecture with domain registration side information.