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

chara-podimata
Chara Podimata
MIT
christos-h-papadimitriou
Christos H. Papadimitriou
Columbia University
christos-tzamos
Christos Tzamos
University of Athens and UW Madison
constantinos-caramanis
Constantinos Caramanis
University of Texas, Austin
constantinos-daskalakis
Constantinos Daskalakis
MIT
ioannis-panageas
Ioannis Panageas
University of California, Irvine
katerina-sotiraki
Katerina Sotiraki
UC Berkeley
vasilis-syrgkanis
Vasilis Syrgkanis
Stanford University
 

The project “ARCHIMEDES Unit: Research in Artificial Intelligence, Data Science and Algorithms” with code OPS 5154714 is implemented by the National Recovery and Resilience Plan “Greece 2.0” and is funded by the European Union – NextGenerationEU.

greece2.0 eu_arch_logo_en

 

 

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