SILO: Hidden Convexity of Deep Neural Networks: Exact and Transparent Lasso Formulations via Geometric Algebra
Abstract: In this talk, we introduce an analysis of deep neural networks through convex optimization and geometric (Clifford) algebra. We begin by introducing exact convex optimization formulations for ReLU neural networks. This approach demonstrates that deep networks can be globally trained through convex programs, offering a globally optimal solution. Our …