Current Research Focus

• Statistical theory of unsupervised learning
• Theory of deep learning (some recent works described in this talk)
• Non-parametric methods for learning
• Machine learning on graphs

Selected projects

• Consistency of kernel clustering
• Generalisation and asymptotics of graph neural networks
• Analysis of over-parametrised neural networks
• Machine learning on ordinal data
• Testing and clustering of large networks

Codes

• Graph neural tangent kernel
• Machine learning for life cycle assessment
• Hierarchical clustering for ordinal data
• Graph two-sample testing
• Nearest neighbour search for ordinal data (also see follow-up work on random forest for ordinal data)
• Hypergraph clustering (with application to subspace clustering)