Unsupervised Training of Convex Regularizers using Maximum Likelihood Estimation Permalink
Poster, Mathematics and Image Analysis MIA25, Paris, France
Poster presentation.
Talks and presentations
WIP, still missing some earlier talks.Data-Driven Geometry for Convex Optimization
Group seminar, ETH Zurich Optimization and Decision Intelligence group, Zurich
Blessing of dimensionality using low-dimensional data
PhD symposium talk, GSK.ai, London, UK
Noise-Free Sampling Algorithms via Regularized Wasserstein Proximals Permalink
Mini-symposium Talk, SIAM Conference on Imaging Science 2024, Atlanta, GA
Data-Driven Geometry for Convex Optimization Permalink
Workshop Talk, Big Data Inverse Problems Workshop, Edinburgh, UK
Deterministic Sampling with Wasserstein Proximals Permalink
Poster, Workshop on Optimal Transport: From Theory to Applications, Berlin, Germany
Poster presentation. Poster pitch can be found here
Data-driven Optimization via Mirror Descent
Department Seminar, Oxford-CUHK Joint Seminar Series, Oxford, UK (Online)
Part of the joint seminar series with City University of Hong Kong and Mathematical Institute at University of Oxford.
Data-Driven Convex Optimization via Mirror Descent
Mini-symposium Talk, ICIAM 2023, Tokyo, Japan
Learned Mirror Descent/Accelerating Plug-and-Play
Department Seminar, Level Set Meeting, Los Angeles, CA
Data-driven Mirror Descent with Acceleration and Robustness
Talk, GSK.ai PhD Symposium, Stevenage, UK