Academic Articles & Research Papers

Optimization Strategies in Quantum Machine Learning: A Performance Analysis

This study presents a comprehensive comparison of multiple optimization algorithms applied to a quantum classification model, utilizing the Cleveland dataset. Specifically, the research focuses on three prominent optimizers—COBYLA, L-BFGS-B...

Deep quantum neural networks on a superconducting processor

Abstract Deep learning and quantum computing have achieved dramatic progresses in recent years. The interplay between these two fast-growing fields gives rise to a new research frontier of quantum machine learning. In this work, we report a...

Expressibility and trainability of parametrized analog quantum systems for machine learning applications

Parametrized quantum evolution is the main ingredient in variational quantum algorithms for near-term quantum devices. In digital quantum computing, it has been shown that random parametrized quantum circuits are able to express complex dis...

Ensembles machine learning for short duration rainfall intensity forecasting

Abstract This study introduces an ensemble machine learning (EML) framework to enhance short-duration rainfall-intensity prediction under limited-data conditions. By integrating multiple base learners within a stacking architecture, the pro...

Tamarind health assessment dataset: Images of shelled, unshelled, and mixed tamarind podsMendeley Data

This data paper provides image dataset that includes 8432 high-quality images of Tamarindus indica [1] (tamarind), categorized into six types: Shelled Healthy Single, Shelled Healthy Multiple, Unshelled Healthy Single, Unshelled Healthy Mul...

Machine Learning in Computer Vision

During last few years the computer applications have gone dramatic transformation from simple data processing to machine learning, thanks to the availability and accessibility of huge volume of data collected through sensors and internet. T...

Machine learning in construction: From shallow to deep learning

The development of artificial intelligence technology is currently bringing about new opportunities in construction. Machine learning is a major area of interest within the field of artificial intelligence, playing a pivotal role in the pro...

Introduction to Machine Learning with Python: A Guide for Data Scientists

Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teac...

A few useful things to know about machine learning

Tapping into the "folk knowledge" needed to advance machine learning applications....

GAUSSIAN PROCESSES FOR MACHINE LEARNING

Gaussian processes (GPs) are natural generalisations of multivariate Gaussian random variables to infinite (countably or continuous) index sets. GPs have been applied in a large number of fields to a diverse range of ends, and very many dee...

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...

Machine Learning in Materials Science

This chapter addresses the role that data-driven approaches, especially machine learning methods, are expected to play in materials research in the immediate future. Machine learning, an important part of artificial intelligence, has made m...

Introduction to machine learning

The machine learning approach is to train an algorithm using a dataset for which the people do know the outcome, and then apply this algorithm in the future to make a prediction when they don't know the outcome. In this chapter, the authors...

Machine learning applications in epilepsy

Machine learning leverages statistical and computer science principles to develop algorithms capable of improving performance through interpretation of data rather than through explicit instructions. Alongside widespread use in image recogn...

Machine Learning Mastery

This chapter delves into the core principles of machine learning, offering practical insights for effective data processing. From foundational concepts to advanced techniques, the narrative unfolds as a comprehensive guide for harnessing th...

Machine learning applications in genetics and genomics

Fairness in multimodal machine learning applications in clinical decision support: a systematic review.