Piecewise linear neural networks and deep learningdoi:10.1038/s43586-022-00137-3This PrimeView highlights best practices for the representation and learning of piecewise linear neural networks.Nature Publishing Group UKNature Reviews Methods Primers...
As a powerful modelling method, piecewise linear neural networks (PWLNNs) have proven successful in various fields, most recently in deep learning. To apply PWLNN methods, both the representation and the learning have long been studied. In 1977, the canonical representation pioneered the works of...
In this paper, a fast, convergent design algorithm for piecewise linear neural networks has been developed. Two efficient, polynomial time pruning algorithms for PLNs have been described. A sifting algorithm has been given that picks the best PLN of each size from tens of networks generated by ...
Neural networks are often thought of as opaque, black-box function approximators, but theoretical tools let us describe and visualize their behavior. In particular, let’s study piecewise-linearity, a property many neural networks share. This property hasbeenstudiedbefore, but we’ll try to visuali...
As a powerful modelling method, piecewise linear neural networks (PWLNNs) have proven successful in various fields, most recently in deep learning. To apply PWLNN methods, both the representation and the learning have long been studied. In 1977, the canonical representation pioneered the works of...
In this paper, we propose a piecewise linear quantization (PWLQ) scheme to enable accurate approximation for tensor values that have bell-shaped distributions with long tails. Our approach breaks the entire quantization range into non-overlapping regions for each tensor, with each region being ...
This repository contains all the code necessary to replicate the findings described in the paper: Piecewise Linear Neural Networks Verification: A comparative study. If you use it in your research, please cite:@Article{Bunel2017, author = {Bunel, Rudy and Turkaslan, Ilker and Torr, Philip H....
1) piecewise-linear neural network 分片线性神经网络 1. During this process,feature points were used in place of sample data to do triangulation,then an algorithm ofpiecewise-linear neural networks approximation based on optimal triangulation was given. ...
Radu Dogaru Piecewise Linear Neural Networks Introduction 1.1 Principles of Feedforward Neural Networks 来自 Semantic Scholar 喜欢 0 阅读量: 1 作者: R Dogaru 摘要: The paradigm of artificial neural networks has an important role for intelligent information processing. An artificial intelligent system (...
Recurrent Neural Networks with Unsaturating Piecewise Linear Activation Functionsdoi:10.1007/978-1-4757-3819-3_4It is known that in the dynamical analysis of RNNs, the activation functions are important factors which affect the dynamics of neural networks. Various activation functions have been used ...