Learning Local Feature Aggregation Functions with Backpropagation

26 Jun 2017Angelos KatharopoulosDespoina PaschalidouChristos DiouAnastasios Delopoulos

This paper introduces a family of local feature aggregation functions and a novel method to estimate their parameters, such that they generate optimal representations for classification (or any task that can be expressed as a cost function minimization problem). To achieve that, we compose the local feature aggregation function with the classifier cost function and we backpropagate the gradient of this cost function in order to update the local feature aggregation function parameters... (read more)

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