Ahmet Alacaoglu
Continuous optimization for machine learning, reinforcement learning and other data science problems
WID Postdocs expand the institute’s research portfolio and expertise, bringing new perspectives to bear on problems.
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Continuous optimization for machine learning, reinforcement learning and other data science problems
Designing practical, data-efficient algorithms with rigorous guarantees for statistical applications
Theoretical research on the emergence of life-like systems from chemical reaction networks
Relationship between genomes and their environments to predict organisms' fitness correlations.
Development of computational methods for inference and analysis of biological networks
Large scale and robust optimization in machine learning, min-max problems with game theory
Integrate computational and experimental models of host-pathogen interaction in bacterial infections