Ryan Marcus is a researcher who has focused on various aspects of query planning, optimization, and learning techniques in database systems. Their work often involves offline query optimization, Bayesian optimization, and adaptive consensus algorithms. They have contributed to research papers covering topics such as generalization in selectivity learning, scalability in data systems, and multi-task Bayesian optimization. Marcus has also explored adaptive Byzantine fault-tolerant consensus and hash table aggregation techniques. Their research spans across different conferences and journals, showcasing a diverse range of interests in the field of computer science.
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