WebGlobal Optimality in Neural Network Training Benjamin D. Haeffele and Ren´e Vidal Johns Hopkins University, Center for Imaging Science, Baltimore, MD 21218, USA. [email protected] [email protected] Abstract The past few years have seen a dramatic increase in the performance of recognition systems thanks to the introduc- WebMar 4, 2012 · Abstract. Nonconvex penalties such as the smoothly clipped absolute deviation or minimax concave penalties have desirable properties such as the oracle property, even when the dimension of the predictive variables is large. However, checking whether a given local minimizer has such properties is not easy since there can be many …

Global Optimality - an overview ScienceDirect Topics

WebThe signomial global optimization algorithm is a method for solving nonconvex mixed-integer signomial problems to global optimality. A convex underestimation is … WebGlobal Optimality in Tensor Factorization, Deep Learning, and Beyond. arXiv:1506.07540, 2015. Main Results • Assumptions: – : convex and once differentiable in – and : sums of … restriction arrosage gers

Proceedings of the Thirty-First AAAI Conference on Artificial ...

http://www.vision.jhu.edu/assets/HaeffeleCVPR17.pdf WebHowever, it is known that, in presence of a huge solution space and many local optima, GAs cannot guarantee the achievement of global optimality. In this work, in order to make GAs more effective in finding the global optimal solution, we propose a hybrid GA which combines the classical genetic mechanisms with the gradient-descent (GD ... WebGlobal Optimality in Tensor Factorization, Deep Learning, and Beyond. arXiv:1506.07540, 2015. Main Results • Assumptions: – : convex and once differentiable in – and : sums of positively homogeneous functions of same degree • Theorem 2: spurious ... restriction a georgia