Machine Learning Foundations
DESCRIPTION
We study the foundations of Machine Learning and Statistics. We study existing methods and models, and develop new ones, targeting challenging learning modalities. We develop techniques that address important challenges, including learning from data that are high-dimensional, contain biases, or are corrupted, and addressing fairness, incentive and reliability issues that arise at model deployment.
RESEARCHERS
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Chara Podimata
MIT
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Christos H. Papadimitriou
Columbia University
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Christos Tzamos
University of Athens and UW Madison
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Constantinos Caramanis
University of Texas, Austin
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Constantinos Daskalakis
MIT
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Ioannis Panageas
University of California, Irvine
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Katerina Sotiraki
Yale University
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Konstantinos Tsakalidis
University of Liverpool
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Vasileios Nakos
National and Kapodistrian University of Athens
![vasilis-syrgkanis](/images/avatars/vasilis_syrgkanis.png#joomlaImage://local-images/avatars/vasilis_syrgkanis.png?width=250&height=250)