Using additive noise in back-propagation training

No abstract is available for this paper.

• Publication year

  1992

• Venue

  IEEE Trans. Neural Networks

• Publication date

  Unknown publication date

• Fields of study

  Mathematics, Computer Science, Medicine

• Identifiers
  DOI 10.1109/72.105415PMID 18276403
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

• Compact Numerical Methods for Computers

  2018cited by this paper
• Generalization in a linear perceptron in the presence of noise

  1992cited by this paper
• Learning with noise in a linear perceptron

  1992cited by this paper
• Asymptotic bounds for the expected L 1 error of a multivariate kernel density estimator

  1992cited by this paper
• Kernel regression and backpropagation training with noise

  1991cited by this paper
• Creating artificial neural networks that generalize

  1991cited by this paper
• Inference of a rule by a neural network with thermal noise.

  1990cited by this paper
• Experiments for isolated-word recognition with single- and two-layer perceptrons

  1990cited by this paper
• Probabilistic neural networks

  1990cited by this paper
• Training noise adaptation in attractor neural networks

  1990cited by this paper
• Inversion of multilayer nets

  1989cited by this paper
• Learning in Artificial Neural Networks: A Statistical Perspective

  1989cited by this paper
• One-class generalization in second-order backpropagation networks for image classification

  1989cited by this paper
• Syllable recognition using integrated neural networks

  1989cited by this paper
• An Improved Version of the Pseudo-Inverse Solution for Classification and Neural Networks

  1989cited by this paper
• Training with noise and the storage of correlated patterns in a neural network model

  1989cited by this paper
• Learning the hidden structure of speech.

  1988cited by this paper
• Statistical pattern recognition with neural networks: benchmarking studies

  1988cited by this paper
• Nonparametric density estimation : the L[1] view

  1987cited by this paper
• A Course in Density Estimation

  1987cited by this paper
• Learning internal representations by error propagation

  1986cited by this paper
• Experiments on Learning by Back Propagation.

  1986cited by this paper
• An Asymptotically Efficient Solution to the Bandwidth Problem of Kernel Density Estimation

  1985cited by this paper
• Non-parametric Density Estimation

  1985cited by this paper
• Consistent Cross-Validated Density Estimation

  1983cited by this paper
• The Equivalence of Weak, Strong and Complete Convergence in $L_1$ for Kernel Density Estimates

  1983cited by this paper
• On the dominance of non-parametric Bayes rule discriminant algorithms in high dimensions

  1980cited by this paper
• On the Effects of Dimension in Discriminant Analysis for Unequal Covariance Populations

  1979cited by this paper
• On the Effects of Dimension in Discriminant Analysis

  1976cited by this paper
• On the Choice of Smoothing Parameters for Parzen Estimators of Probability Density Functions

  1976cited by this paper
• Asymptotic Properties of Non-Linear Least Squares Estimators

  1969cited by this paper
• Estimation of a multivariate density

  1966cited by this paper
• On Estimation of a Probability Density Function and Mode

  1962cited by this paper
• Remarks on Some Nonparametric Estimates of a Density Function

  1956cited by this paper

• Enhancing Attention-Based Visual Processing With Noise-Boosted Activation Functions

  2026cites this paper
• Machine learning approach for enhanced estimation of phosphorus adsorption isotherm parameters

  2026cites this paper
• Regularisation in neural networks: a survey and empirical analysis of approaches

  2026cites this paper
• Should all Noises Be Treated Equally: Impact of Input Noise Variability on Neural Network Robustness

  2026cites this paper
• Detecting object hue bin in the CIECAM02 uniform color space using a multi-layer perceptron for optimal spectrum generation

  2025cites this paper
• Using machine learning to map simulated noisy and laser-limited multidimensional spectra to molecular electronic couplings

  2025cites this paper
• An interpretable operator-learning model for electric field profile reconstruction in discharges based on the EFISH method

  2025cites this paper
• Ensemble approach to deep learning seabed classification using multichannel ship noisea).

  2025cites this paper
• Noisy data-based attack: A new type of untargeted attack in Federated Learning and its countermeasures

  2025cites this paper
• Variance-Aware Noisy Training: Hardening DNNs against Unstable Analog Computations

  2025cites this paper
• Virtual sample diffusion generation method guided by large language model-generated knowledge for enhancing information completeness and zero-shot fault diagnosis in building thermal systems

  2025cites this paper
• Modelling of Initial Magnetic Curves of Non-Oriented Laminated Steels Using Artificial Neural Networks

  2025cites this paper
• Using economic value signals from primate prefrontal cortex in neuro-engineering applications

  2025influential citation
• Optimizing sample size for supervised machine learning with bulk transcriptomic sequencing: a learning curve approach

  2024cites this paper
• Photoacoustic imaging of squirrel monkey cortical responses induced by peripheral mechanical stimulation

  2024cites this paper
• Policy Gradient-Driven Noise Mask

  2024cites this paper
• Raman and Mid-Infrared Spectroscopy Coupled With Machine–Deep Learning for Adulterant Detection in Ground Turmeric

  2024cites this paper
• Methods for Optimization Problems with Markovian Stochasticity and Non-Euclidean Geometry

  2024cites this paper
• Rolling the dice for better deep learning performance: A study of randomness techniques in deep neural networks

  2024cites this paper
• Data Augmentation for Multivariate Time Series Classification: An Experimental Study

  2024cites this paper
• Loss of plasticity in deep continual learning

  2024cites this paper
• Spatial Extrapolation of Early Room Impulse Responses with Noise-Robust Physics-Informed Neural Network

  2024cites this paper
• Harnessing the Power of Noise: A Survey of Techniques and Applications

  2024cites this paper
• Optimized injection of noise in activation functions to improve generalization of neural networks

  2024cites this paper
• Robustness enhancement in neural networks with alpha-stable training noise

  2024cites this paper
• Performance investigation of channel estimation for intelligent reflecting surface assisted wireless communications using neural network

  2024cites this paper
• Cooperative coevolutionary differential evolution with linkage measurement minimization for large-scale optimization problems in noisy environments

  2023cites this paper
• Balancing Logit Variation for Long-Tailed Semantic Segmentation

  2023cites this paper
• The Paradox of Noise: An Empirical Study of Noise-Infusion Mechanisms to Improve Generalization, Stability, and Privacy in Federated Learning

  2023cites this paper
• Deep Learning of Quasar Lightcurves in the LSST Era

  2023cites this paper
• How good can a simple artificial neural network predict the medium reorganization energy and the free energy gap from a steady-state fluorescence spectrum?

  2023cites this paper
• Integrating modeled environmental variability into neural network training for underwater source localization.

  2023cites this paper
• Learning Provably Robust Estimators for Inverse Problems via Jittering

  2023cites this paper
• Robustness Enhancement in Neural Networks with Alpha-Stable Training Noise

  2023cites this paper
• TextManiA: Enriching Visual Feature by Text-driven Manifold Augmentation

  2023cites this paper
• A comprehensive assessment benchmark for rigorously evaluating deep learning image classifiers

  2023cites this paper
• Evaluating the Robustness of Machine Reading Comprehension Models to Low Resource Entity Renaming

  2023cites this paper
• Estimating the common agricultural policy milestones and targets by neural networks.

  2023cites this paper
• Maintaining Plasticity in Deep Continual Learning

  2023cites this paper
• Comprehensive Assessment of the Performance of Deep Learning Classifiers Reveals a Surprising Lack of Robustness

  2023cites this paper
• On the Effectiveness of Activation Noise in Both Training and Inference for Generative Classifiers

  2023cites this paper
• A Modular Deep Learning Architecture for Voice Pathology Classification

  2023cites this paper
• A machine learning approach to color space Euclidisation

  2023cites this paper
• Improving signal fidelity for deep learning‐based seismic interference noise attenuation

  2022cites this paper
• Absolute convergence and error thresholds in non-active adaptive sampling

  2022cites this paper
• Noise Injection Node Regularization for Robust Learning

  2022cites this paper
• Effect of Batch Normalization on Noise Resistant Property of Deep Learning Models

  2022cites this paper
• Probabilistically Robust Learning: Balancing Average- and Worst-case Performance

  2022cites this paper
• Robust Probabilistic Time Series Forecasting

  2022cites this paper
• Noise-modulated neural networks for selectively functionalizing sub-networks by exploiting stochastic resonance

  2021cites this paper
• Noise-Boosted Backpropagation Learning of Feedforward Threshold Neural Networks for Function Approximation

  2021cites this paper
• Two-Stage Approach to Parameter Estimation of Differential Equations Using Neural ODEs

  2021cites this paper
• Pure Noise to the Rescue of Insufficient Data: Improving Imbalanced Classification by Training on Random Noise Images

  2021cites this paper
• Combining acoustic features and medical data in deep learning networks for voice pathology classification

  2021cites this paper
• A Comparative Study of Machine Learning Methods for Predicting the Evolution of Brain Connectivity from a Baseline Timepoint

  2021cites this paper
• Comprehensive Analysis of Multiple Cohort Datasets Deciphers the Utility of Germline Single-Nucleotide Polymorphisms in Prostate Cancer Diagnosis

  2021cites this paper
• Adaptive Noisy Data Augmentation for Regularized Construction of Undirected Graphical Models

  2021cites this paper
• Adieu recurrence? End-to-end speech emotion recognition using a context stacking dilated convolutional network

  2021cites this paper
• Prediction and identification of physical systems by means of Physically-Guided Neural Networks with meaningful internal layers

  2021cites this paper
• Advances in Electron Microscopy with Deep Learning

  2021cites this paper
• Adversarial Robustness with Semi-Infinite Constrained Learning

  2021cites this paper
• Interval Deep Learning for Uncertainty Quantification in Safety Applications

  2021cites this paper
• Over-the-Air Federated Learning From Heterogeneous Data

  2020cites this paper
• Improving ECG Classification Using Generative Adversarial Networks

  2020cites this paper
• Deep learning in electron microscopy

  2020cites this paper
• P-Hydra: Bridging Transfer Learning And Multitask Learningtitle

  2020cites this paper
• Data augmentation based malware detection using convolutional neural networks

  2020cites this paper
• Do ideas have shape? Plato's theory of forms as the continuous limit of artificial neural networks

  2020cites this paper
• A noise injection strategy for graph autoencoder training

  2020cites this paper
• Do ideas have shape? Idea registration as the continuous limit of artificial neural networks

  2020cites this paper
• Categorical Perception: A Groundwork for Deep Learning

  2020cites this paper
• Towards Robust Medical Image Segmentation on Small-Scale Data with Incomplete Labels

  2020cites this paper
• An Empirical Analysis of Backward Compatibility in Machine Learning Systems

  2020cites this paper
• Noise can speed backpropagation learning and deep bidirectional pretraining

  2020cites this paper
• Computer Model Calibration with Time Series Data using Deep Learning and Quantile Regression

  2020influential citation
• Anti-noise diffractive neural network for constructing an intelligent imaging detector array.

  2020cites this paper
• Data pre-processing effect on ANN-based prediction intervals construction of the evaporation process at different climate regions in Iran

  2020cites this paper
• Identification of state functions by physically-guided neural networks with physically-meaningful internal layers

  2020cites this paper
• Introduction to Neural Networks

  2020cites this paper
• Solving Inverse Problems With Deep Neural Networks – Robustness Included?

  2020cites this paper
• Advances in Neural Networks – ISNN 2020: 17th International Symposium on Neural Networks, ISNN 2020, Cairo, Egypt, December 4–6, 2020, Proceedings

  2020cites this paper
• A Diffractive Neural Network with Weight-Noise-Injection Training

  2020cites this paper
• Improved Noise and Attack Robustness for Semantic Segmentation by Using Multi-Task Training with Self-Supervised Depth Estimation

  2020cites this paper
• A machine learning approach for efficient multi-dimensional integration

  2020cites this paper
• “Identity Bracelets” for Deep Neural Networks

  2020cites this paper
• Is Spiking Secure? A Comparative Study on the Security Vulnerabilities of Spiking and Deep Neural Networks

  2019cites this paper
• Diagnostics of Water-Ethanol Solutions by Raman Spectra with Artificial Neural Networks: Methods to Improve Resilience of the Solution to Distortions of Spectra

  2019cites this paper
• Fault tolerance of neural networks in adversarial settings

  2019cites this paper
• Application of artificial neural networks to X‐ray fluorescence spectrum analysis

  2019cites this paper
• Noise Regularization for Conditional Density Estimation

  2019influential citation
• Black-Box Adversarial Attacks for Deep Neural Networks and Spiking Neural Networks

  2019cites this paper
• Training on Synthetic Noise Improves Robustness to Natural Noise in Machine Translation

  2019cites this paper
• Development of Near-Field Source Localization Method using Convolutional Neural Network

  2019cites this paper
• The Effect of the Normalization Method Used in Different Sample Sizes on the Success of Artificial Neural Network Model

  2019cites this paper
• Newborn jaundice determination by reflectance spectroscopy using multiple polynomial regression, neural network, and support vector regression

  2019cites this paper
• Data Augmentation in Training CNNs: Injecting Noise to Images

  2019cites this paper
• Model validation using mutated training labels: An exploratory study

  2019cites this paper
• Conditional Density Estimation with Neural Networks: Best Practices and Benchmarks

  2019cites this paper
• Adversarial Risk via Optimal Transport and Optimal Couplings

  2019cites this paper
• The significance of artificial intelligence in drug delivery system design.

  2019cites this paper