2025
2023
2022
2021
2016
- Optimization and Machine Learning Seminar - How does generalization behave under suitable model capacities in modern machine learning? From deterministic equivalence to function spaces
- Optimization and Machine Learning Seminar - Rates for least squares using over-parameterized neural networks
- Optimization and Machine Learning Seminar - Hybrid projection methods for solution decomposition in large-scale Bayesian inverse problems
- HKU Number Theory Days 2025 on June 24-27, 2025
- Frontiers of Mathematics Lecture - From microscopic to macroscopic scale equations: mean field, hydrodynamic and graph limits
- Analysis and PDE Seminar - Some unconventional PDE problems from photonics
- Analysis and PDE Seminar - table singularity formation for the inviscid Primitive equations
- Analysis and PDE Seminar - Entropic Dispersion and the Heat Death of the Universe
- Analysis and PDE Seminar - Global well-posedness for the Muskat problem with surface tension
- Optimization and Machine Learning Seminar - Beyond Second Order Methods for Nonconvex Optimization
- Analysis and PDE Seminar - On the rigidity and existence of self-similar type solutions to the steady Navier-Stokes Equations
- Optimization and Machine Learning Seminar - On Generalization and Implicit Rank Restriction in Deep Matrix Completion and Neural Networks
2023
2022
- Optimization and Machine Learning Seminar - Lyapunov Stability of the Subgradient Method with Constant Step Size
- Optimization and Machine Learning Seminar - A Penalty Relaxation Method for Image Processing Using Euler's Elastica Model [Change of Venue]
- Optimization and Machine Learning Seminar - Riemannian Proximal Gradient Methods
- Optimization and Machine Learning Seminar - Nonnegativity, Sparsity and Polynomial Optimization
- Optimization and Machine Learning Seminar - Learning operators using deep neural networks for diverse applications
- Optimization and Machine Learning Seminar - Quadratic error bound of the smoothed gap and the restarted averaged primal-dual hybrid gradient
- Optimization and Machine Learning Seminar - Sum-of-squares hierarchies for polynomial optimization and the Christoffel-Darboux kernel
- Colloquium - An inexact projected gradient method with rounding and lifting by nonlinear programming for solving rank-one semidefinite relaxation of polynomial optimization
- Colloquium - Nash Equilibrium Problems
- Optimization and Machine Learning Seminar - Non-convex Bayesian Learning via Stochastic Gradient Markov Chain Monte Carlo
- Optimization and Machine Learning Seminar - Phase Diagram for Some Hyperparameters in Two-layer Neural Networks
- Optimization and Machine Learning Seminar - Mean field theory in Inverse Problems: from Bayesian inference to overparameterization of networks
- Optimization and Machine Learning Seminar - Data-driven reduced-order modeling for nonlinear dynamic multiscale problems
2021
- Optimization and Numerical Analysis Seminar - Sparse polynomial optimization
- Colloquium - Complexity of proximal augmented Lagrangian type methods for solving nonconvex composite optimization problems with nonlinear convex constraints
- Colloquium - Nonsmooth differentiation in deep learning: a mathematical approach
2016