تقرير
The Real Tropical Geometry of Neural Networks
العنوان: | The Real Tropical Geometry of Neural Networks |
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المؤلفون: | Brandenburg, Marie-Charlotte, Loho, Georg, Montúfar, Guido |
سنة النشر: | 2024 |
المجموعة: | Computer Science Mathematics |
مصطلحات موضوعية: | Mathematics - Combinatorics, Computer Science - Machine Learning, 14T90, 52C45, 68T07 (Primary), 14P10, 52C35 (Secondary) |
الوصف: | We consider a binary classifier defined as the sign of a tropical rational function, that is, as the difference of two convex piecewise linear functions. The parameter space of ReLU neural networks is contained as a semialgebraic set inside the parameter space of tropical rational functions. We initiate the study of two different subdivisions of this parameter space: a subdivision into semialgebraic sets, on which the combinatorial type of the decision boundary is fixed, and a subdivision into a polyhedral fan, capturing the combinatorics of the partitions of the dataset. The sublevel sets of the 0/1-loss function arise as subfans of this classification fan, and we show that the level-sets are not necessarily connected. We describe the classification fan i) geometrically, as normal fan of the activation polytope, and ii) combinatorially through a list of properties of associated bipartite graphs, in analogy to covector axioms of oriented matroids and tropical oriented matroids. Our findings extend and refine the connection between neural networks and tropical geometry by observing structures established in real tropical geometry, such as positive tropicalizations of hypersurfaces and tropical semialgebraic sets. Comment: 43 pages, 6 figures; comments welcome! |
نوع الوثيقة: | Working Paper |
URL الوصول: | http://arxiv.org/abs/2403.11871 |
رقم الأكسشن: | edsarx.2403.11871 |
قاعدة البيانات: | arXiv |
الوصف غير متاح. |