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Frontiers in Big Data is delighted to present the Reviews in Big Data series of article collections.

Reviews in Machine Learning and Artificial Intelligence will publish high-quality scholarly review papers on key topics across the field. It aims to highlight recent advances in ...

Frontiers in Big Data is delighted to present the Reviews in Big Data series of article collections.

Reviews in Machine Learning and Artificial Intelligence will publish high-quality scholarly review papers on key topics across the field. It aims to highlight recent advances in the field, whilst emphasizing important directions and new possibilities for future inquiries. We anticipate the research presented will promote discussion in the big data community and translate to best practice applications in the research community and policy settings, as well as stimulating understanding and future research.

The Reviews in Machine Learning and Artificial Intelligence collection welcomes full-length and mini-review articles, across the full section scope. New articles will be added to this collection as they are published.

Topics of particular interest, include, but are not limited to:
• Adversarial machine learning
• Robustness and reliability of machine learning systems
• Computer vision
• Image recognition
• Combinatorial optimization
• Meta-heuristic algorithms

Keywords: adversarial machine learning, robust machine learning, reliable machine learning, image recognition, meta heuristic algorithms, machine learning, artificial intelligence, big data, #CollectionSeries


Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

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