Talks

Some recent talks

• A majorized proximal point dual Newton algorithm for nonconvex statistical optimization problems (The Sixth International Conference on Continuous Optimization, Technical University (TU) of Berlin, Germany, August 3–8, 2019).

• Matrix Cones and Spectral Operators of Matrices (Advances in the Geometric and Analytic Theory of Convex Cones, Sungkyunkwan University, Korea, May 27–31, 2019).

• On the Relationships of ADMM and Proximal ALM for Convex Optimization Problems (Institute of Applied Physics and Computational Mathematics, Beijing, April 12, 2019).

• Sparse semismooth Newton methods and big data composite optimization (New Computing-Driven Opportunities for Optimization, Wuyishan, August 13-17, 2018).

• On the efficient computation of the projector over the Birkhoff polytope (International Symposium on Mathematical Programming 2018, Bordeaux, July 1-6, 2018).

• A block symmetric Gauss-Seidel decomposition theorem and its applications in big data nonsmooth optimization (International Workshop on Modern Optimization and Applications, AMSS, Beijing, June 16-18, 2018).

• On the Equivalence of Inexact Proximal ALM and ADMM for a Class of Convex Composite Programming(DIMACS Workshop on ADMM and Proximal Splitting Methods in Optimization, Rutgers University, June 11-13, 2018).

• A block symmetric Gauss-Seidel decomposition theorem and its applications in big data nonsmooth optimization (The Hong Kong Mathematical Society Annual General meeting 2018, May 26, 2018).

• SDPNAL+: A MATLAB software package for large-scale SDPs with a user-friendly interface (SIAM-ALA18, May 2018).

• Second order sparsity and big data optimization (October 2017).

• Error bounds and the superlinear convergence rates of the augmented Lagrangian methods (October 2017).

• Block symmetric Gauss-Seidel iteration and multi-block semidefnite programming (October 2017).

• A two-phase augmented Lagrangian approach for linear and convex quadratic semidefinite programming problems(December 2016).

• Linear rate convergence of the ADMM for multi-block convex conic programming (August 2016).

• An efficient inexact accelerated block coordinate descent method for least squares semidefinite programming (June 2015).

• Multi-stage convex relaxation approach for low-rank structured PSD matrix recovery (May 2014).

Some old talks

• An inexact accelerated proximal gradient method for large scale linearly constrained convex SDP (April 2012).

• From linear programming to matrix programming: A paradigm shift in optimization (December 2011).

• A sequential convex programming approach for rank constrained matrix optimization problems (December 2011).

• Low rank matrix optimization problems: Back to nonconvex regularizations (June 2011).

• Matrix optimization: Searching between the first and second order methods (May 2011).

• A majorized penalty approach for calibrating rank constrained correlation matrix problems (October 2010).

• An introduction to a class of matrix cone programming (July 2010).

• A majoried penalty approach for calibrating rank constrained correlation matrix problems (July 2010).

• Rank constrained matrix optimization problems (May 2010).

• An Introduction to Correlation Stress Testing (March 2010).

• An Implementable Proximal Point Algorithmic Framework for Nuclear Norm Minimization (July 2009).

• A Proximal Point Method for Matrix Least Squares Problem with Nuclear Norm Regularization (May 2009).

• A Newton-CG Augmented Lagrangian Method for Large Sacle Semidefinite Programming (based on a revised version) (March 2009).

• A Newton-CG Augmented Lagrangian Method for Large Sacle Semidefinite Programming (October 2008).

• Calibrating least squares covariance matrix problems with equality and inequality constraints (July 2008).

• The Role of Metric Projectors in Nonlinear Conic Optimization (August 2007).

• Inverse Quadratic Eigenvalue Problems (July 2006).

• Recent Developments in Nonlinear Optimization Theory (July 2006).

• A short summer school course on modern optimization theory: optimality conditions and perturbation analysis Part I Part II Part III (July 2006).