AutoML with Bayesian Optimizations for Big Data Management

Neural Architecture Search Survey: A Computer Vision Perspective

(2023) Jeon-Seong Kang et al.   SENSORS

Modelling and Analysis of Neuro Fuzzy Employee Ranking System in the Public Sector

(2023) Konstantinos C. Giotopoulos et al.   Algorithms

AutoML: state of the art with a focus on anomaly detection, challenges, and research directions

(2022) Maroua Bahri et al.   International Journal of Data Science and Analytics

A tutorial on automatic hyperparameter tuning of deep spectral modelling for regression and classification tasks

(2022) Dário Passos et al.   CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS

Machine Learning-Based Boosted Regression Ensemble Combined with Hyperparameter Tuning for Optimal Adaptive Learning

(2022) Joseph Isabona et al.   SENSORS

High Per Parameter: A Large-Scale Study of Hyperparameter Tuning for Machine Learning Algorithms

(2022) Moshe Sipper   Algorithms

TinyML for Ultra-Low Power AI and Large Scale IoT Deployments: A Systematic Review

(2022) Nikolaos Schizas et al.   Future Internet

A review of neural architecture search

(2021) Dilyara Baymurzina et al.   NEUROCOMPUTING

Framework for personalized prediction of treatment response in relapsing remitting multiple sclerosis

(2020) E. Stühler et al.   BMC Medical Research Methodology

A review of feature selection methods in medical applications

(2019) Beatriz Remeseiro et al.   COMPUTERS IN BIOLOGY AND MEDICINE

A survey of machine learning techniques for food sales prediction

(2018) Grigorios Tsoumakas   ARTIFICIAL INTELLIGENCE REVIEW

Optimal Subsampling for Large Sample Logistic Regression

(2017) HaiYing Wang et al.   JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION

Machine Learning for Predictive Maintenance: A Multiple Classifier Approach

(2015) Gian Antonio Susto et al.   IEEE Transactions on Industrial Informatics

Dual-source discrimination power analysis for multi-instance contactless palmprint recognition

(2015) Lu Leng et al.   MULTIMEDIA TOOLS AND APPLICATIONS

Local case-control sampling: Efficient subsampling in imbalanced data sets

(2014) William Fithian et al.   ANNALS OF STATISTICS

A scalable bootstrap for massive data

(2014) Ariel Kleiner et al.   JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY

Improving rail network velocity: A machine learning approach to predictive maintenance

(2014) Hongfei Li et al.   TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES

Weighted Support Vector Machine Usingk-Means Clustering

(2013) Sungwan Bang et al.   COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION

Sample size selection in optimization methods for machine learning

(2012) Richard H. Byrd et al.   MATHEMATICAL PROGRAMMING

PalmHash Code vs. PalmPhasor Code

(2012) Lu Leng et al.   NEUROCOMPUTING

Stability selection

(2010) Nicolai Meinshausen et al.   JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY

Machine learning algorithms for damage detection under operational and environmental variability

(2010) Eloi Figueiredo et al.   STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL