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OCR2SEQ: A NOVEL MULTI-MODAL DATA AUGMENTATION PIPELINE FOR WEAK SUPERVISION
A COMPARATIVE STUDY OF STRUCTURED VERSUS UNSTRUCTURED TEXT DATA
DATA AUGMENTATION IN DEEP LEARNING
ADDRESSING HIGHLY IMBALANCED BIG DATA CHALLENGES FOR MEDICARE FRAUD DETECTION
MACHINE LEARNING ALGORITHMS FOR PREDICTING BOTNET ATTACKS IN IOT NETWORKS
COLLECTION AND ANALYSIS OF SLOW DENIAL OF SERVICE ATTACKS USING MACHINE LEARNING ALGORITHMS
A REVIEW AND ANALYSIS OF BOT-IOT SECURITY DATA FOR MACHINE LEARNING
MACHINE LEARNING ALGORITHMS FOR THE DETECTION AND ANALYSIS OF WEB ATTACKS
DEEP MAXOUT NETWORKS FOR CLASSIFICATION PROBLEMS ACROSS MULTIPLE DOMAINS
DATA COLLECTION FRAMEWORK AND MACHINE LEARNING ALGORITHMS FOR THE ANALYSIS OF CYBER SECURITY ATTACKS
INVESTIGATING MACHINE LEARNING ALGORITHMS WITH IMBALANCED BIG DATA
PREDICTING MELANOMA RISK FROM ELECTRONIC HEALTH RECORDS WITH MACHINE LEARNING TECHNIQUES
Big Data Analytics and Engineering for Medicare Fraud Detection
An Evaluation of Deep Learning with Class Imbalanced Big Data
An Exploration into Synthetic Data and Generative Aversarial Networks
Machine Learning Algorithms with Big Medicare Fraud Data
Enhancement of Deep Neural Networks and Their Application to Text Mining
An evaluation of Unsupervised Machine Learning Algorithms for Detecting Fraud and Abuse in the U.S. Medicare Insurance Program
Machine Learning Algorithms for the Analysis of Social Media and Detection of Malicious User Generated Content
Parallel Distributed Deep Learning on Cluster Computers

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