Supervised Machine Learning

Supervised machine learning focuses on training models to predict outcomes based on labeled data, aiming to build accurate and reliable predictive systems. Current research emphasizes improving model robustness to real-world data distribution shifts, exploring the limitations of using privileged information during training, and enhancing model interpretability through techniques like global sensitivity analysis and SHAP values. These advancements are crucial for various applications, from medical diagnostics and materials science to cybersecurity and social media analysis, improving decision-making across diverse fields.

Papers

June 18, 2023

Can predictive models be used for causal inference?
Maximilian Pichler, Florian Hartig
Causal Inference Predictive Model Causal Learning Supervised Machine Learning Causal Feature Independent Variable Collinearity

May 31, 2023

Assessing the Generalizability of a Performance Predictive Model
Ana Nikolikj, Gjorgjina Cenikj, Gordana Ispirova, Diederick Vermetten, Ryan Dieter Lang, Andries Petrus Engelbrecht, Carola Doerr, Peter Korošec, Tome Eftimov
Predictive Model Stronger Generalizability Supervised Machine Learning Performance Prediction Algorithm Performance

May 23, 2023

Understanding and Improving Optimization in Predictive Coding Networks
Nick Alonso, Jeff Krichmar, Emre Neftci
Neural Network Scientific Inference Back Propagation Human Understanding Predictive Coding Memory Efficient Supervised Machine Learning Optimization Strategy

April 27, 2023

A Supervised Machine Learning Approach to Operator Intent Recognition for Teleoperated Mobile Robot Navigation
Evangelos Tsagkournis, Dimitris Panagopoulos, Giannis Petousakis, Grigoris Nikolaou, Rustam Stolkin, Manolis Chiou
Human Robot Interaction Robot Teleoperation Supervised Machine Learning Human Robot Teaming

April 13, 2023

Supervised Machine Learning for Breast Cancer Risk Factors Analysis and Survival Prediction
Khaoula Chtouki, Maryem Rhanoui, Mounia Mikram, Kamelia Amazian, Siham Yousfi
Machine Learning Machine Learning Approach Survival Prediction Supervised Machine Learning Meta Dataset Cancer Survival Prediction Breast Cancer Risk

March 27, 2023

Defect detection using weakly supervised learning
Vasileios Sevetlidis, George Pavlidis, Vasiliki Balaska, Athanasios Psomoulis, Spyridon Mouroutsos, Antonios Gasteratos
Supervised Learning Simple Classifier Defect Detection Supervised Machine Learning Supervised Counterpart

March 3, 2023

Who could be behind QAnon? Authorship attribution with supervised machine-learning
Florian Cafiero, Jean-Baptiste Camps
Authorship Attribution Supervised Machine Learning Authorship Verification Linguistic Landscape

February 21, 2023

Classification with Trust: A Supervised Approach based on Sequential Ellipsoidal Partitioning
Ranjani Niranjan, Sachit Rao
Classification Code Simple Classifier Appropriate Trust Supervised Machine Learning Exploratory Data Analysis Supervised Approach Classification Rule Sequential Classifier

February 9, 2023

Machine Learning Capability: A standardized metric using case difficulty with applications to individualized deployment of supervised machine learning
Adrienne Kline, Joon Lee
Machine Learning Financial Application Case Relevance Supervised Machine Learning Item Response Theory Benchmark Data

January 26, 2023

A Benchmark Study by using various Machine Learning Models for Predicting Covid-19 trends
D. Kamelesun, R. Saranya, P. Kathiravan
Machine Learning Human Prediction Covid 19 Support Vector Machine Benchmark Study Supervised Machine Learning

January 9, 2023

Online Fake Review Detection Using Supervised Machine Learning And BERT Model
Abrar Qadir Mir, Furqan Yaqub Khan, Mohammad Ahsan Chishti
BERT Model Word Embeddings Support Vector Machine Supervised Machine Learning Fake Review Fake Review Detection

November 16, 2022

Exploring Supervised Machine Learning for Multi-Phase Identification and Quantification from Powder X-Ray Diffraction Spectra
Jaimie Greasley, Patrick Hosein
Supervised Machine Learning Dataset Augmentation X Ray Diffraction Powder X Ray Diffraction

November 4, 2022

Impact Learning: A Learning Method from Features Impact and Competition
Nusrat Jahan Prottasha, Saydul Akbar Murad, Abu Jafar Md Muzahid, Masud Rana, Md Kowsher, Apurba Adhikary, Sujit Biswas, Anupam Kumar Bairagi
Machine Learning Competition Platform Supervised Machine Learning Traditional Machine Learning Learning Method Feature Influence

October 10, 2022

Risk Automatic Prediction for Social Economy Companies using Camels
Joseph Gallego-Mejia, Daniela Martin-Vega, Fabio Gonzalez
Random Forest Predictive Model Risk Prediction Supervised Machine Learning Electric SHEEP

August 15, 2022

WiFi Based Distance Estimation Using Supervised Machine Learning
Kahraman Kostas, Rabia Yasa Kostas, Francisco Zampella, Firas Alsehly
Supervised Machine Learning Distance Function Wi Fi Signal Quality WiFi Visual Spatial Distancing

July 20, 2022

Journal Impact Factor and Peer Review Thoroughness and Helpfulness: A Supervised Machine Learning Study
Anna Severin, Michaela Strinzel, Matthias Egger, Tiago Barros, Alexander Sokolov, Julia Vilstrup Mouatt, Stefan Müller
Peer Review Supervised Machine Learning Short Paper Helpfulness Score Journal Impact Factor

July 9, 2022

Supervised Machine Learning for Effective Missile Launch Based on Beyond Visual Range Air Combat Simulations
Joao P. A. Dantas, Andre N. Costa, Felipe L. L. Medeiros, Diego Geraldo, Marcos R. O. A. Maximo, Takashi Yoneyama
Machine Learning Machine Learning Model Supervised Machine Learning Air Combat Resampling Technique

May 9, 2022

Few-shot Mining of Naturally Occurring Inputs and Outputs
Mandar Joshi, Terra Blevins, Mike Lewis, Daniel S. Weld, Luke Zettlemoyer
Natural Language Large Corpus Abstractive Summarization Structured Output Dense Retrieval Rich Input Supervised Machine Learning

April 27, 2022

Performance and Interpretability Comparisons of Supervised Machine Learning Algorithms: An Empirical Study
Alice J. Liu, Arpita Mukherjee, Linwei Hu, Jie Chen, Vijayan N. Nair
Neural Network System Performance Empirical Study Random Forest Predictive Performance Supervised Machine Learning Predictive Distribution Scikit Learn

April 6, 2022

The 2021 Urdu Fake News Detection Task using Supervised Machine Learning and Feature Combinations
Muhammad Humayoun
Fake News Fake News Detection Supervised Machine Learning Urdu Language Contextual Lemmatization Feature Combination

Supervised Machine Learning

Papers

Can predictive models be used for causal inference?

Assessing the Generalizability of a Performance Predictive Model

Understanding and Improving Optimization in Predictive Coding Networks

A Supervised Machine Learning Approach to Operator Intent Recognition for Teleoperated Mobile Robot Navigation

Supervised Machine Learning for Breast Cancer Risk Factors Analysis and Survival Prediction

Defect detection using weakly supervised learning

Who could be behind QAnon? Authorship attribution with supervised machine-learning

Classification with Trust: A Supervised Approach based on Sequential Ellipsoidal Partitioning

Machine Learning Capability: A standardized metric using case difficulty with applications to individualized deployment of supervised machine learning

A Benchmark Study by using various Machine Learning Models for Predicting Covid-19 trends

Online Fake Review Detection Using Supervised Machine Learning And BERT Model

Exploring Supervised Machine Learning for Multi-Phase Identification and Quantification from Powder X-Ray Diffraction Spectra

Impact Learning: A Learning Method from Features Impact and Competition

Risk Automatic Prediction for Social Economy Companies using Camels

WiFi Based Distance Estimation Using Supervised Machine Learning

Journal Impact Factor and Peer Review Thoroughness and Helpfulness: A Supervised Machine Learning Study

Supervised Machine Learning for Effective Missile Launch Based on Beyond Visual Range Air Combat Simulations

Few-shot Mining of Naturally Occurring Inputs and Outputs

Performance and Interpretability Comparisons of Supervised Machine Learning Algorithms: An Empirical Study

The 2021 Urdu Fake News Detection Task using Supervised Machine Learning and Feature Combinations