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On the Decision Boundaries of Neural Networks. A Tropical Geometry Perspective
This work tackles the problem of characterizing and understanding the decision boundaries of neural networks with piecewise linear non-linearity activations.
On the Decision Boundaries of Neural Networks: A Tropical Geometry Perspective
Our main finding is that the decision boundaries are a subset of a tropical hypersurface, which is intimately related to a polytope formed by the convex hull of two zonotopes.
On the Decision Boundaries of Deep Neural Networks: A Tropical Geometry Perspective
We use tropical geometry, a new development in the area of algebraic geometry, to provide a characterization of the decision boundaries of a simple neural network of the form (Affine, ReLU, Affine).
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