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Efficient BackProp

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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Increased rates of convergence through learning rate adaptation

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Mathematical approaches to neural networks

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A scaled conjugate gradient algorithm for fast supervised learning

inferredcites →https://doi.org/10.1016/s0898-1221(96)90463-0openalex-snapshot

Advances in neural information processing systems 7

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Neural Networks for Pattern Recognition

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Computing second derivatives in feed-forward networks: a review

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Digital signal processing

inferredcites →https://doi.org/10.1142/s0129065793000031openalex-snapshot

SUPERVISED LEARNING ON LARGE REDUNDANT TRAINING SETS

inferredcites →https://doi.org/10.1162/089976698300017746openalex-snapshot

Natural Gradient Works Efficiently in Learning

inferredcites →https://doi.org/10.1162/neco.1989.1.2.281openalex-snapshot

Fast Learning in Networks of Locally-Tuned Processing Units

inferredcites →https://doi.org/10.1162/neco.1992.4.1.1openalex-snapshot

Neural Networks and the Bias/Variance Dilemma

inferredcites →https://doi.org/10.1162/neco.1992.4.2.141openalex-snapshot

First- and Second-Order Methods for Learning: Between Steepest Descent and Newton's Method

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Bibliography

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Natural Conjugate Gradient Training of Multilayer Perceptrons

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Rprop Using the Natural Gradient

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Introduction

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Deep Neural Networks

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Microarray Data Classified by Artificial Neural Networks

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OnMLM: An Online Formulation for the Minimal Learning Machine

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Automated Vibrational Signal Recognition and Playback

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Effect of Weight Initialization on Training of Sigmoidal FFANN for Back Propagation Algorithms

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Optimization Methods

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Active Contour Model in Deep Learning Era: A Revise and Review

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Image Segment Classification Using CNN

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Detecting the Most Insightful Parts of Documents Using a Regularized Attention-Based Model

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Layer-Wise Conditioning Analysis in Exploring the Learning Dynamics of DNNs

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Ensemble Kalman Filter Optimizing Deep Neural Networks: An Alternative Approach to Non-performing Gradient Descent

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Why AI Works

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Deep MCEM for Weakly-Supervised Learning to Jointly Segment and Recognize Objects Using Very Few Expert Segmentations

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Towards Certification of a Reduced Footprint ACAS-Xu System: A Hybrid ML-Based Solution

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Introduction

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Motivation and Overview of Normalization in DNNs

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A General View of Normalizing Activations

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A Framework for Normalizing Activations as Functions

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Analysis of Normalization

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Revisiting Batch Norm Initialization

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Rethinking Exponential Averaging of the Fisher

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The Effect of Normalization and Batch Normalization Layers in CNNs Models: Application to Plant Disease Classifications

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Secure Forward Aggregation for Vertical Federated Neural Networks

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The Backpropagation Algorithm

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TESSLA: Two-Stage Ensemble Scar Segmentation for the Left Atrium

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Learning Representations by Crystallized Back-Propagating Errors

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Qualitative Analysis in LIBS

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The Vanishing Empirical Variance in Randomly Initialized Deep ReLU Networks

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Convolutional Neural Networks

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Introduction

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Analysis of Normalization in Training

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Image Denoising with Rectified Linear Units

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Training Deep Neural Networks

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Deep Convolutional Neural Network for Fog Detection

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Deep Learning in the Wild

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Stochastic Learning

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Hierarchical Behavior Knowledge Space

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A Fast Semi-linear Backpropagation Learning Algorithm

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Optimal Learning Rates for Clifford Neurons

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An Incremental Learning Method for Neural Networks Based on Sensitivity Analysis

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Evaluation of Pooling Operations in Convolutional Architectures for Object Recognition

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Reinforcement Learning with Neural Networks: Tricks of the Trade

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A Hierarchical Neural Network Architecture for Classification

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Teeth/Palate and Interdental Segmentation Using Artificial Neural Networks

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Matrix Pseudoinversion for Image Neural Processing

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Online Handwriting Recognition Using Multi Convolution Neural Networks

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Big Learning and Deep Neural Networks

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Practical Recommendations for Gradient-Based Training of Deep Architectures

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Training Deep and Recurrent Networks with Hessian-Free Optimization

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10 Steps and Some Tricks to Set up Neural Reinforcement Controllers

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Action-Driven Perception for a Humanoid

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Deep Learning of Representations: Looking Forward

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Learning How to Combine Internal and External Denoising Methods

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Embodied Language Understanding with a Multiple Timescale Recurrent Neural Network

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No-Prop-fast - A High-Speed Multilayer Neural Network Learning Algorithm: MNIST Benchmark and Eye-Tracking Data Classification

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Training Neural Networks with Implicit Variance

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Pushing Stochastic Gradient towards Second-Order Methods – Backpropagation Learning with Transformations in Nonlinearities

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Learning Sparse Features with an Auto-Associator

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Incremental Weighted Naive Bays Classifiers for Data Stream

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Zeitreihenanalyse mit Neuronalen Netzen

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Deep Learning in Diagnosis of Brain Disorders

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Application of Neural Network for Human Actions Recognition

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A New Pruning Method to Train Deep Neural Networks

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Fault Diagnosis of Bearings with Variable Rotational Speeds Using Convolutional Neural Networks

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Unsupervised Deep Learning in Character Recognition

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Recurrent ANNs for Failure Predictions on Large Datasets of Italian SMEs

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The Use of Convolutional Neural Networks in Invariant Image Recognition

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Keyword Spotting with Neural Networks Used for Image Classification

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Review and Comparison of Commonly Used Activation Functions for Deep Neural Networks

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Towards Recognition of Normal Versus Pneumonia Infected Patients Using Deep Neural Network Technique

inferred← citeshttps://doi.org/10.1007/978-981-15-9509-7_20openalex-snapshot

Image Classification Using Machine Learning Techniques for Traffic Signal

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Varidation of Indoor Localization Method by CNN Using RSSI

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Efficient Training Convolutional Neural Networks on Edge Devices with Gradient-Pruned Sign-Symmetric Feedback Alignment

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Simplifying Graph Neural Kernels: from Stacking Layers to Collapsed Structure

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DiffGen: Optimizing I/O Trace Generation with Differentiated Modeling Techniques

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Learning and Understanding Neuromorphic Computing by Converting Convolution Neural Networks into Spiking Neural Networks

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Artificial Neural Networks and Discrete Choice Models: Comparing and Contrasting

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Combining complex Langevin dynamics with score-based and energy-based diffusion models

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Surrogate gradient methods for data-driven foundry energy consumption optimization

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Gradient-based smoothing parameter estimation for neural P-splines

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The presence of a latent factor in gasoline and diesel prices co-movements

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Physics-informed neural networks for geoid modeling

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EDM: a enhanced diffusion models for image restoration in complex scenes

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Multiscale modeling of viscoelastic shell structures with artificial neural networks

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An improved optimization technique using Deep Neural Networks for digit recognition

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Dynamically pre-trained deep recurrent neural networks using environmental monitoring data for predicting PM2.5

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CUDA-based parallelization of a bio-inspired model for fast object classification

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An improved dynamic sampling back-propagation algorithm based on mean square error to face the multi-class imbalance problem

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Convolutional neural network-based multimodal image fusion via similarity learning in the shearlet domain

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Neural network applications in fault diagnosis and detection: an overview of implementations in engineering-related systems

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Reliable detection of compressed and encrypted data

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Empirical validation of ELM trained neural networks for financial modelling

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A novel N-degree mittag-leffler sigmoidal activation function for deep learning algorithms

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Spawning tasks from chitchatting - reinforcement learning-based policy

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TriPhy-GF—A Triple-Physics-Constrained Graph Neural Network for Accurate and Efficient Microseismic Event Localization in Coal Mines

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Is natural variability really natural? The case of Atlantic Multidecadal Oscillation investigated by a neural network model

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Effective deep learning-based multi-modal retrieval

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Labelling logical structures of document images using a dynamic perceptive neural network

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Predicting the average size of blasted rocks in aggregate quarries using artificial neural networks

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Call classification using recurrent neural networks, support vector machines and finite state automata

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Mitigation of the ground reflection effect in real-time locating systems based on wireless sensor networks by using artificial neural networks

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Automated histological classification of whole-slide images of gastric biopsy specimens

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Learning Time-Scales in Two-Layers Neural Networks

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A review of adaptive online learning for artificial neural networks

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Deep reinforcement learning in computer vision: a comprehensive survey

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Convergence analysis of convex incremental neural networks

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Knowledge transfer in SVM and neural networks

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A novel activation function for multilayer feed-forward neural networks

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Learning flat representations with artificial neural networks

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A real-time solar flare forecasting system with deep learning methods

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Deep learning for time series classification: a review

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InceptionTime: Finding AlexNet for time series classification

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