Academic Articles & Research Papers

MVPA-Light: A Classification and Regression Toolbox for Multi-Dimensional Data

MVPA-Light is a MATLAB toolbox for multivariate pattern analysis (MVPA). It provides native implementations of a range of classifiers and regression models, using modern optimization algorithms. High-level functions allow for the multivaria...

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...

Machine learning models and bankruptcy prediction

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...

Perspectives in machine learning for wildlife conservation

Inexpensive and accessible sensors are accelerating data acquisition in animal ecology. These technologies hold great potential for large-scale ecological understanding, but are limited by current processing approaches which inefficiently d...

A Topical Review of Graph Embedding in Graph Neural Networks

Graph embeddings map graph-structured data into vector spaces for machine learning tasks. In Graph Neural Networks (GNNs), these embeddings are computed through message passing and support tasks such as node classification, link prediction ...

Feature-driven static analysis for learning-based android malware detection: A review

The extensive embrace of Android has amplified malware risks, resulting in a need for better detection methods. This article investigates the area of static analysis, which analyses applications without execution by examining code and manif...

Determinants of Tourism Demand Using Machine Learning Techniques

The purpose of the current study was to determine factors affecting tourism demand using machine learning techniques. The results of different linear regression and random forest models on both the train and test sets were compared using RM...

Rapid Deployment of Deep Learning-Based Condition Monitoring for Rotating Machines

Rotating machines are extremely common in many industries, and their maintenance involves substantial costs and labor. Most recent studies aiming to automate fault diagnosis have focused on deep learning, but industry adoption has been slow...

Evaluation of PCA with variable selection for cluster typological domains

Abstract The modeling of mineral deposits has been improved over the years with the incorporation of mineralogical and metallurgical information obtained from drilling samples that make up the pillars for the construction of resource models...

Unsupervised Machine Learning for Improved Delaunay Triangulation

Physical oceanography models rely heavily on grid discretization. It is known that unstructured grids perform well in dealing with boundary fitting problems in complex nearshore regions. However, it is time-consuming to find a set of unstru...

Adversarial machine learning

In this paper (expanded from an invited talk at AISEC 2010), we discuss an emerging field of study: adversarial machine learning---the study of effective machine learning techniques against an adversarial opponent. In this paper, we: give a...

Machine Learning and Its Applications to Biology

The term machine learning refers to a set of topics dealing with the creation and evaluation of algorithms that facilitate pattern recognition, classification, and prediction, based on models derived from existing data. Two facets of mechan...

Classification of bioactive peptides: A systematic benchmark of models and encodings

Bioactive peptides are short amino acid chains possessing biological activity and exerting physiological effects relevant to human health. Despite their therapeutic value, their identification remains a major problem, as it mainly relies on...

Probabilistic daily runoff forecasting in high-altitude cold regions using a hybrid model combining DBO and transformer variants

Study Area: The Tailan River Basin in the Aksu region and the Yulong Kashi River in the Hotan River Basin of Xinjiang are located at respective geographical coordinates of 80°21'44'' to 81°10'14'' E, 40°41'41'' to 42°15'13'' N, and 77.25° t...

A Novel End-to-End Corporate Credit Rating Model Based on Self-Attention Mechanism

In traditional financial analysis discriminant analyses with statistic methods are considered as primary and widely applied corporate credit rating bases in which human impact plays an essential role. Machine learning approaches enormously ...

Co-optimization of therapeutic antibody affinity and specificity using machine learning models that generalize to novel mutational space

Optimising antibody properties such as affinity can be detrimental to other key properties. Here the authors use machine learning to simplify the identification of antibodies with co-optimal levels of affinity and specificity for a clinical...

Machine learning in chemoinformatics and drug discovery

Chemoinformatics is an established discipline focusing on extracting, processing and extrapolating meaningful data from chemical structures. With the rapid explosion of chemical 'big' data from HTS and combinatorial synthesis, machine learn...

Improving the Robustness of Odour Recognition with Odour-Image Data Fusion in Open-Air Settings

Odour recognition with low-cost gas sensors is challenging in open-air settings due to the non-specificity of the sensors and environmental variability. This can be mitigated by incorporating additional information into the classification p...

Using Soft Voting Classifier of Machine Learning Algorithms for Earthquake Prediction

Earthquakes are among the most dangerous natural disasters that can cause major losses to buildings and threaten human lives. The research community is very interested in the topic of earthquakes because they occur suddenly and predicting t...