Neural Network Classifier

Neural network classifiers are computational models designed to categorize data into predefined classes, aiming for high accuracy and efficiency. Current research emphasizes improving interpretability, understanding generalization behavior (including phenomena like benign overfitting and neural collapse), and developing methods for uncertainty quantification and efficient computation of explainability metrics. These advancements are significant for various applications, ranging from medical diagnosis and text analysis to image recognition and more, driving progress in both theoretical understanding and practical deployment of these powerful tools.

Papers

October 13, 2024

Sharper Guarantees for Learning Neural Network Classifiers with Gradient Methods
Hossein Taheri, Christos Thrampoulidis, Arya Mazumdar
Gradient Descent NCD Method Deep Network Natural Gradient Gradient Method Neural Network Classifier Data Dependent

May 11, 2024

Interpretable global minima of deep ReLU neural networks on sequentially separable data
Thomas Chen, Patricia Muñoz Ewald
Neural Network Weight Matrix Global Minimum Separable Data Neural Network Classifier

April 6, 2024

The Identification and Categorization of Anemia Through Artificial Neural Networks: A Comparative Analysis of Three Models
Mohammed A. A. Elmaleeh
Neural Network Full Model Person Identification Simple Classifier Neural Network Classifier Anemia Degree

January 10, 2024

Closed-Form Interpretation of Neural Network Classifiers with Symbolic Gradients
Sebastian Johann Wetzel
Neural Network Symbolic Regression Deep Regression Neural Network Classifier Closed Form

January 8, 2024

Universal Consistency of Wide and Deep ReLU Neural Networks and Minimax Optimal Convergence Rates for Kolmogorov-Donoho Optimal Function Classes
Hyunouk Ko, Xiaoming Huo
Neural Network Simple Classifier Convergence Rate ReLU Network Logistics System Neural Network Classifier Kolmogorov Complexity Universal Consistency

November 22, 2023

Explaining high-dimensional text classifiers
Odelia Melamed, Rich Caruana
High Dimensional High Explainability Explainability Method Dimensional Input Neural Network Classifier Explainability Tool

September 26, 2023

On Excess Risk Convergence Rates of Neural Network Classifiers
Hyunouk Ko, Namjoon Suh, Xiaoming Huo
Neural Network Supervised Learning Convergence Rate Classification Problem Neural Network Classifier

September 9, 2023

Towards Understanding Neural Collapse: The Effects of Batch Normalization and Weight Decay
Leyan Pan, Xinyuan Cao
Mixed Effect Cross Entropy Loss Batch Normalization Neural Collapse Neural Network Classifier Weight Decay

May 11, 2023

COCKATIEL: COntinuous Concept ranKed ATtribution with Interpretable ELements for explaining neural net classifiers on NLP tasks
Fanny Jourdan, Agustin Picard, Thomas Fel, Laurent Risser, Jean Michel Loubes, Nicholas Asher
Inherent Interpretability Transformer Model NLP Task Neural Network Classifier Explainability Problem Concept Attribution Interpretability Benefit NLP Classification Task

March 11, 2023

Efficient Computation of Shap Explanation Scores for Neural Network Classifiers via Knowledge Compilation
Leopoldo Bertossi, Jorge E. Leon
Explainable AI Black Box Binary Neural Network Efficient Computation Neural Network Classifier SHAP Score Knowledge Compilation SHAP Clustering Classifier Circuit

March 10, 2023

Uncertainty quantification in neural network classifiers -- a local linear approach
Magnus Malmström, Isaac Skog, Daniel Axehill, Fredrik Gustafsson
Neural Network Uncertainty Quantification MNIST Canadian Institute for Advanced Neural Network Classifier Multiple Classifier Neural Network Parameter Probability Mass Function

October 1, 2022

NeuroEvo: A Cloud-based Platform for Automated Design and Training of Neural Networks using Evolutionary and Particle Swarm Algorithms
Philip Schroeder
Neural Network Evolutionary Algorithm Particle Swarm Optimization Automated Design Neural Network Classifier Cloud Platform

July 8, 2022

Neuroimaging Feature Extraction using a Neural Network Classifier for Imaging Genetics
Cédric Beaulac, Sidi Wu, Erin Gibson, Michelle F. Miranda, Jiguo Cao, Leno Rocha, Mirza Faisal Beg, Farouk S. Nathoo
Feature Extraction Disease Prediction Neural Network Classifier Gene Disease Association

June 8, 2022

Neural Collapse: A Review on Modelling Principles and Generalization
Vignesh Kothapalli
Neural Network Strong Generalization Narrative Review Neural Collapse Neural Network Classifier Layer Output Nearest Centroid

May 27, 2022

Geometer: Graph Few-Shot Class-Incremental Learning via Prototype Representation
Bin Lu, Xiaoying Gan, Lina Yang, Weinan Zhang, Luoyi Fu, Xinbing Wang
Graph Drawing Class Incremental Learning Node Classification Real World Graph Neural Network Classifier Evolving Graph Shot Class Incremental Learning Prototype Representation

May 24, 2022

Multilevel sentiment analysis in arabic
Ahmed Nassar, Ebru Sezer
Implicit Sentiment Neural Network Classifier Arabic Sentiment Analysis Document Level Sentiment

May 23, 2022

What is Your Metric Telling You? Evaluating Classifier Calibration under Context-Specific Definitions of Reliability
John Kirchenbauer, Jacob Oaks, Eric Heim
Neural Architecture Calibration Performance North Star Metric Neural Network Classifier Classifier Calibration Contextual Structure

April 8, 2022

Biometric identification by means of hand geometry and a neural net classifier
Marcos Faundez-Zanuy, Guillermo Mar Navarro Mérida
Neural Network Multiple Meaning Biometric Identification Neural Network Classifier Biometric Authentication System Hand Geometry Resolution Scanner

April 6, 2022

Last Layer Re-Training is Sufficient for Robustness to Spurious Correlations
Polina Kirichenko, Pavel Izmailov, Andrew Gordon Wilson
Native Robustness Spurious Correlation Spurious Feature Neural Network Classifier Last Layer Retraining

April 4, 2022

Efficient, Uncertainty-based Moderation of Neural Networks Text Classifiers
Jakob Smedegaard Andersen, Walid Maalej
High Efficiency Content Moderation Text Classifier Neural Network Classifier Neural Text Classification F1 Score

Neural Network Classifier

Papers

Sharper Guarantees for Learning Neural Network Classifiers with Gradient Methods

Interpretable global minima of deep ReLU neural networks on sequentially separable data

The Identification and Categorization of Anemia Through Artificial Neural Networks: A Comparative Analysis of Three Models

Closed-Form Interpretation of Neural Network Classifiers with Symbolic Gradients

Universal Consistency of Wide and Deep ReLU Neural Networks and Minimax Optimal Convergence Rates for Kolmogorov-Donoho Optimal Function Classes

Explaining high-dimensional text classifiers

On Excess Risk Convergence Rates of Neural Network Classifiers

Towards Understanding Neural Collapse: The Effects of Batch Normalization and Weight Decay

COCKATIEL: COntinuous Concept ranKed ATtribution with Interpretable ELements for explaining neural net classifiers on NLP tasks

Efficient Computation of Shap Explanation Scores for Neural Network Classifiers via Knowledge Compilation

Uncertainty quantification in neural network classifiers -- a local linear approach

NeuroEvo: A Cloud-based Platform for Automated Design and Training of Neural Networks using Evolutionary and Particle Swarm Algorithms

Neuroimaging Feature Extraction using a Neural Network Classifier for Imaging Genetics

Neural Collapse: A Review on Modelling Principles and Generalization

Geometer: Graph Few-Shot Class-Incremental Learning via Prototype Representation

Multilevel sentiment analysis in arabic

What is Your Metric Telling You? Evaluating Classifier Calibration under Context-Specific Definitions of Reliability

Biometric identification by means of hand geometry and a neural net classifier

Last Layer Re-Training is Sufficient for Robustness to Spurious Correlations

Efficient, Uncertainty-based Moderation of Neural Networks Text Classifiers