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Loss function

Known as: Zero-one loss, Loss, Risk function 
In mathematical optimization, statistics, decision theory and machine learning, a loss function or cost function is a function that maps an event or… Expand
Wikipedia

Related topics

Related topics

50 relations
Adaptive filterBackpropagationBootstrapping (statistics)Constrained optimization
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Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Review
2021
Review
2021
Deep Face Recognition: A Survey
Deep learning applies multiple processing layers to learn representations of data with multiple levels of feature extraction… Expand
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Review
2020
Review
2020
A survey of the recent architectures of deep convolutional neural networks
Deep Convolutional Neural Network (CNN) is a special type of Neural Networks, which has shown exemplary performance on several… Expand
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Review
2020
Review
2020
A review of change point detection methods
In this work, methods to detect one or several change points in multivariate time series are reviewed. They include retrospective… Expand
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Review
2019
Review
2019
Feature-based aggregation and deep reinforcement learning: a survey and some new implementations
  • D. Bertsekas
  • IEEE/CAA Journal of Automatica Sinica
  • 2019
    • Corpus ID: 4881243
In this paper we discuss policy iteration methods for approximate solution of a finite-state discounted Markov decision problem… Expand
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Review
2019
Review
2019
A unified framework for stochastic optimization
  • W. Powell
  • Eur. J. Oper. Res.
  • 2019
    • Corpus ID: 85512222
Abstract Stochastic optimization is an umbrella term that includes over a dozen fragmented communities, using a patchwork of… Expand
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Review
2019
Review
2019
Model Predictive Control of High-Power Modular Multilevel Converters—An Overview
Model predictive control (MPC) has emerged as a promising approach to control a modular multilevel converter (MMC). With the help… Expand
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Review
2018
Review
2018
WaterGAN: Unsupervised Generative Network to Enable Real-Time Color Correction of Monocular Underwater Images
This letter reports on WaterGAN, a generative adversarial network (GAN) for generating realistic underwater images from in-air… Expand
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Review
2017
Review
2017
Classifying Radio Galaxies with the Convolutional Neural Network
We present the application of deep machine learning technique to classify radio images of extended sources on a morphological… Expand
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Highly Cited
1997
Highly Cited
1997
Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces
A new heuristic approach for minimizing possiblynonlinear and non-differentiable continuous spacefunctions is presented. By means… Expand
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Highly Cited
1996
Highly Cited
1996
Bias Plus Variance Decomposition for Zero-One Loss Functions
We present a bias variance decomposition of expected misclassi cation rate the most commonly used loss function in supervised… Expand
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