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Theory and algorithms    

• Learning from data streams, non-stationary data, spatiotemporal data
• Active, semi-supervised, and unsupervised learning 
• Embeddings, sparsity, and high-dimensionality
• Privacy-preserving machine learning

Applications

• Climate science: 
• Sustainability: energy, environment, agriculture
• Finance