This is the second post (here’s the first one) about an approach to introducing the derivative to calculus students that is counter to what I’ve seen in textbooks and other traditional treatments of ...

We develop an algorithm to construct approximate decision rules that are piecewise-linear and continuous for DSGE models with an occasionally binding constraint. The functional form of the decision ...

Abstract: We present two secure two party computation (STPC) protocols for piecewise function approximation on private data. The protocols rely on a piecewise approximation of the to-be-computed ...

Abstract: Deep feedforward neural networks with piecewise linear activations are currently producing the state-of-the-art results in several public datasets (e.g., CIFAR-10, CIFAR-100, MNIST, and SVHN ...

ABSTRACT: In many medical image segmentation applications identifying and extracting the region of interest (ROI) accurately is an important step. The usual approach to extract ROI is to apply image ...

Generally, a piecewise function can take values of any type as an input and return numbers of any type as an output. However, in its current implementation numpy.piecewise forces the output type to be ...

This is a PyTorch implementation of my tensorflow repository and is more complete due to the flexibility of PyTorch. Lagrange Polynomial, Piecewise Lagrange Polynomial, Discontinuous Piecewise ...