The Effects of Data Sampling with Deep Learning and Highly Imbalanced Big Data

A Hitchhiker’s Guide On Distributed Training Of Deep Neural Networks

(2019) Karanbir Singh Chahal et al.   JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING

Quantitative Analysis of Apache Storm Applications: The NewsAsset Case Study

(2018) José I. Requeno et al.   INFORMATION SYSTEMS FRONTIERS

A systematic study of the class imbalance problem in convolutional neural networks

(2018) Mateusz Buda et al.   NEURAL NETWORKS

Big data and analytics in healthcare: Introduction to the special section

(2016) Atreyi Kankanhalli et al.   INFORMATION SYSTEMS FRONTIERS

ImageNet Large Scale Visual Recognition Challenge

(2015) Olga Russakovsky et al.   INTERNATIONAL JOURNAL OF COMPUTER VISION

Deep learning

(2015) Yann LeCun et al.   NATURE

Variability in Medicare Utilization and Payment Among Urologists

(2015) Joan S. Ko et al.   UROLOGY

Does Medical School Training Relate to Practice? Evidence from Big Data

(2015) Keith Feldman et al.   Big Data

A comparative study of iterative and non-iterative feature selection techniques for software defect prediction

(2013) Taghi M. Khoshgoftaar et al.   INFORMATION SYSTEMS FRONTIERS

Effective detection of sophisticated online banking fraud on extremely imbalanced data

(2012) Wei Wei et al.   WORLD WIDE WEB-INTERNET AND WEB INFORMATION SYSTEMS

Learning from Imbalanced Data

(2009) Haibo He et al.   IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING

MapReduce

(2008) Jeffrey Dean et al.   COMMUNICATIONS OF THE ACM

Exploratory Undersampling for Class-Imbalance Learning

(2008) Xu-Ying Liu et al.   IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS