What is a loss surface?
A graph of weight(s) versus loss.
loss surface explained in plain English
Example
Practitioners refer to loss surface when building, training, or evaluating machine learning systems. It appears in research papers, product documentation, and technical discussions about AI capabilities and limitations.
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A sophisticated gradient descent algorithm that rescales the gradients of each parameter, effectively giving each parameter an independent learning rate.
- Attention
A mechanism that lets a model focus on the most relevant parts of its input when producing an output, weighting what matters most in context.
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A model that infers a prediction based on its own previous predictions.
- autoencoder
A system that learns to extract the most important information from the input.
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A loss function—used in conjunction with a neural network model's main loss function—that helps accelerate training during the early iterations when weights are randomly initialized.
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The process that tells a neural network which internal settings caused an error and how to adjust them, working backwards through layers.
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The set of examples used in one training iteration.
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Normalizing the input or output of the activation functions in a hidden layer.