Machine Learning Model

Machine learning models aim to create systems that can learn from data and make predictions or decisions without explicit programming. Current research emphasizes improving model accuracy, interpretability, and robustness, focusing on architectures like deep neural networks, decision tree ensembles, and transformer models, as well as exploring decentralized learning and techniques for mitigating biases and vulnerabilities. These advancements are crucial for diverse applications, ranging from optimizing resource management (e.g., smart irrigation) to improving healthcare diagnostics and enhancing the security and trustworthiness of AI systems.

Papers

January 10, 2022

Predictions of Reynolds and Nusselt numbers in turbulent convection using machine-learning models
Shashwat Bhattacharya, Mahendra K Verma, Arnab Bhattacharya
Machine Learning Model Human Prediction Neural Network Model Linear Convection Numerical Result Reynolds Number

January 8, 2022

Forecasting Loss of Signal in Optical Networks with Machine Learning
Wenjie Du, David Cote, Chris Barber, Yan Liu
Machine Learning Machine Learning Model Abnormal Signal Optical Network Multiple Network Prediction Loss

January 6, 2022

Machine Learning: Algorithms, Models, and Applications
Jaydip Sen, Sidra Mehtab, Rajdeep Sen, Abhishek Dutta, Pooja Kherwa, Saheel Ahmed, Pranay Berry, Sahil Khurana, Sonali Singh, David W. W Cadotte, David W. Anderson, Kalum J. Ost, Racheal S. Akinbo, Oladunni A. Daramola, Bongs Lainjo
Deep Learning Machine Learning Artificial Intelligence Machine Learning Model Full Model Financial Application Practical Algorithm

January 4, 2022

January 3, 2022

Descriptors for Machine Learning Model of Generalized Force Field in Condensed Matter Systems
Puhan Zhang, Sheng Zhang, Gia-Wei Chern
Machine Learning Model Material SCIence Force Field Novel Descriptor Electronic Structure

December 29, 2021

The impacts of various parameters on learning process and machine learning based performance prediction in online coding competitions
Hardik Patel, Purvi Koringa
Machine Learning Model New Machine Many Parameter Complex Process Competition Platform Performance Prediction Machine Learning Classifier Competition Result Online Questionnaire

December 26, 2021

The Quantum Version of Prediction for Binary Classification Problem by Ensemble Methods
Kamil Khadiev, Liliia Safina
Machine Learning Model Human Prediction Binary Classification Quantum Algorithm Ensemble Model Ensemble Method Bayesian Algorithm Quantum Version

December 25, 2021

A comparative study on machine learning models combining with outlier detection and balanced sampling methods for credit scoring
Hongyi Qian, Shen Zhang, Baohui Wang, Lei Peng, Songfeng Gao, You Song
Machine Learning Model Comparative Study Class Imbalance Outlier Detection Credit Scoring Balanced Sampling

December 23, 2021

Predi\c{c}\~ao de Incid\^encia de Les\~ao por Press\~ao em Pacientes de UTI usando Aprendizado de M\'aquina
Henrique P. Silva, Arthur D. Reys, Daniel S. Severo, Dominique H. Ruther, Flávio A. O. B. Silva, Maria C. S. S. Guimarães, Roberto Z. A. Pinto, Saulo D. S. Pedro, Túlio P. Navarro, Danilo Silva
Machine Learning Machine Learning Model Evaluation Metric Precision Recall Curve Pressure Ulcer

December 22, 2021

December 21, 2021

Explanation of Machine Learning Models Using Shapley Additive Explanation and Application for Real Data in Hospital
Yasunobu Nohara, Koutarou Matsumoto, Hidehisa Soejima, Naoki Nakashima
Machine Learning Model Inherent Interpretability Line by Line Explanation Decision Tree Feature Importance Real Data Healthcare Facility Better Interpretability

December 20, 2021

December 18, 2021

Does Explainable Machine Learning Uncover the Black Box in Vision Applications?
Manish Narwaria
Deep Learning Machine Learning Machine Learning Model High Explainability Black Box Explainable Machine Learning Vision Application

December 17, 2021

Quality of Data in Machine Learning
Antti Kariluoto, Arto Pärnänen, Joni Kultanen, Jukka Soininen, Pekka Abrahamsson
Machine Learning Machine Learning Model Raw Data Quality Issue Ensemble Model Model Accuracy Input Feature Student Data

December 16, 2021

Correlation inference attacks against machine learning models
Ana-Maria Creţu, Florent Guépin, Yves-Alexandre de Montjoye
Machine Learning Model Synthetic Data Attribute Inference Attack Model Attack

December 15, 2021

Model Stealing Attacks Against Inductive Graph Neural Networks
Yun Shen, Xinlei He, Yufei Han, Yang Zhang
Graph Neural Network Machine Learning Model Graph Data Model Stealing Attack

December 13, 2021

How to Learn when Data Gradually Reacts to Your Model
Zachary Izzo, James Zou, Lexing Ying
Machine Learning Model Full Model