Academic Articles & Research Papers

Foundations of Machine Learning

Foundations of Machine LearningSoon we will embark on a theoretical study of AdaBoost in order to understand its properties, particularly its ability as a learning algorithm to generalize, that is, to make accurate predictions on data not s...

Introduction to Machine Learning, Neural Networks, and Deep Learning.

Purpose: To present an overview of current machine learning methods and their use in medical research, focusing on select machine learning techniques, best practices, and deep learning. Methods: A systematic literature search in PubMed was ...

Automated shape-based clustering of 3D immunoglobulin protein structures in chronic lymphocytic leukemia

Abstract Background Although the etiology of chronic lymphocytic leukemia (CLL), the most common type of adult leukemia, is still unclear, strong evidence implicates antigen involvement in disease ontogeny and evolution. Primary and 3D stru...

Design, framework and benchmark of safety monitors for black-box classifiers

Abstract The last decade has seen a surging opportunity for developing autonomous systems (e.g., fully autonomous driving, computer-guided robotic surgery, mobile robots for inspections and surveillance, and manufacturing robots) to relieve...

Machine learning-assisted three-dimensional mapping of the facial soft tissues in Saudi Arabian adults with skeletal class I relationship

OBJECTIVES: This study aimed to evaluate facial soft-tissue features in adults with skeletal Class I relationships using three-dimensional (3D) imaging and machine learning to identify sex-specific anthropometric patterns and provide refere...

Unlocking pseudocapacitors prolonged electrode fabrication via ultra-short laser pulses and machine learning

Summary: Pseudocapacitors outperform lithium-ion batteries in terms of charging rate and power density. However, their electrode manufacturing procedures are prolonged and environmentally unfriendly, posing a research challenge. To address ...

A metaheuristic with a neural surrogate function for Word Sense Disambiguation

Word Sense Disambiguation (WSD) is one of the earliest problems in natural language processing which aims to determine the correct sense of words in context. The semantic information provided by WSD systems is highly beneficial to many task...

Synergistic multi-altimeter for estimating water level in the coastal zone of Beibu Gulf using SEL, ALES + and BFAST algorithms

Accurately monitoring and predicting the large-scale dynamic changes of water levels in coastal zones is essential for its protection, restoration and sustainable development. However, there has been a challenge for achieving this goal usin...

Analysis of EMC Factors on Electronic Devices Using PLS-SEM Method: A Case Study in Vietnam

Electronic equipment is indispensable in the industrial 4.0 era. Electromagnetic Compatibility issues with electronic devices are increasingly concerning. The phenomenon of electromagnetic field compatibility is getting higher and higher. T...

Machine learning for real-time aggregated prediction of hospital admission for emergency patients

Abstract Machine learning for hospital operations is under-studied. We present a prediction pipeline that uses live electronic health-records for patients in a UK teaching hospital’s emergency department (ED) to generate short-term, probabi...

Non-linear and probabilistic state discretization functions for enhanced discrete reinforcement learning: Application on wind turbine pitch control

Discrete reinforcement learning (RL) offers interpretability advantages compared to continuous reinforcement learning. Neural networks used in continuous RL behave like black boxes that do not show an obvious relationship between the system...

Applications of Machine Learning in Cancer Prediction and Prognosis

Machine learning is a branch of artificial intelligence that employs a variety of statistical, probabilistic and optimization techniques that allows computers to "learn" from past examples and to detect hard-to-discern patterns from large, ...

Machine learning and radiology

Machine learning in geosciences and remote sensing

Learning incorporates a broad range of complex procedures. Machine learning (ML) is a subdivision of artificial intelligence based on the biological learning process. The ML approach deals with the design of algorithms to learn from machine...

A Review on Fairness in Machine Learning

An increasing number of decisions regarding the daily lives of human beings are being controlled by artificial intelligence and machine learning (ML) algorithms in spheres ranging from healthcare, transportation, and education to college ad...

Python 3 for Machine Learning

This book is designed to provide the reader with basic Python 3 programming concepts related to machine learning. The first four chapters provide a fast-paced introduction to Python 3, NumPy, and Pandas. The fifth chapter introduces the fun...

Machine learning models and bankruptcy prediction

Optimization, and Machine Learning

Foundations of Machine Learning

A new edition of a graduate-level machine learning textbook that focuses on the analysis and theory of algorithms. This book is a general introduction to machine learning that can serve as a textbook for graduate students and a reference fo...

MATLAB Machine Learning

This book is a comprehensive guide to machine learning with worked examples in MATLAB. It starts with an overview of the history of Artificial Intelligence and automatic control and how the field of machine learning grew from these. It prov...