Geometry Aware Particle Swarm Sampling Permalink
Department Seminar, Level Set Meeting, UCLA
Talks and presentations
WIP, still missing some earlier talks.Dataset Distillation as Optimal Quantization Permalink
Department Seminar, Applied Math Group Seminar, Berlin, Germany
Unsupervised Training of Convex Regularizers using Maximum Likelihood Estimation Permalink
Poster, Mathematics and Image Analysis MIA’25, Paris, France
Poster presentation.
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