Dates: 27th and 28th of November, 2021
Location: Online via Zoom.
Registration: Please register here. (it is free.)
Some of the slides are available for downloading. Please check the program below.
Jacek Gondzio (University of Edinburgh)
Florian Jarre (HHU Düsseldorf)
Tomonari Kitahara (Kyushu University)
Masakazu Kojima (Chuo University)
Bruno F. Lourenço (ISM)
Tom Luo (CUHK-Shenzhen)
Shinji Mizuno (Tokyo Institute of Technology)
Renato Monteiro (Georgia Tech)
Keiichi Morikuni (University of Tsukuba)
Masakazu Muramatsu (UEC)
Gábor Pataki (UNC at Chapel Hill)
Kunio Tanabe (ISM)
Mirai Tanaka (ISM)
Tamás Terlaky (Lehigh University)
Takashi Tsuchiya (GRIPS)
Levent Tunçel (University of Waterloo)
László Végh (London School of Economics)
Yinyu Ye (Stanford University)
Akiko Yoshise (University of Tsukuba)
Yin Zhang (CUHK-Shenzhen)
All times below are Tokyo Time (UTC+09)
For time zone conversions, see this link:
10:00: Renato Monteiro. Complexity of a Dampened Proximal ADMM for Linearly-constrained Nonseparable Nonconvex Composite Optimization
10:40: Tom Luo. Learning to maximize a convex quadratic function with application to intelligent reflection surface for wireless communication
11:20: Yinyu Ye. Recent Developments of Online Linear Programming
13:50: Mirai Tanaka: A gradient method for multilevel optimization [Slides]
14:30: Kunio Tanabe: My Personal Experience in Modelling and Algorithm of Optimization for the Learning Machines PLRM/dPLRM
15:30: Bruno F. Lourenço: Completely solving general SDPs [Slides]
16:10: Masakazu Kojima: A geometric analysis of strong duality in conic optimization [Slides]
17:10: Keiichi Morikuni: Implementation of interior-point methods for LP using Krylov methods preconditioned by inner iterations [Slides]
17:50: Jacek Gondzio: Krylov-based Solvers for Interior Point Methods [Slides]
10:00: Levent Tunçel: A biased view of primal-dual interior-point algorithms for convex optimization and some recent developments
10:40: Gábor Pataki: How do exponential size solutions arise in semidefinite programming?
11:20: Tamás Terlaky: Quantum Interior Point Methods for LO and Conic Linear Optimization
13:50: Tomonari Kitahara: A bound for the number of iterations by the simplex method with the steepest-edge rule
14:30: Akiko Yoshise: Evaluating approximations of the semidefinite cone with trace normalized distance [Slides]
15:30: Yin Zhang : Distributed (Sparse) PCA: Seeking Consensus on a Subspace
16:10: Shinji Mizuno: Approximation algorithms for a single-machine scheduling problem with a non-renewable resource
17:00: Florian Jarre: On a very simple analysis of higher order liftings for binary problems
17:40: László Végh: On a scaling-invariant layered least squares interior point method
18:40: Masakazu Muramatsu: A simple SDP example having different duality gaps during FRA [Slides]
19:20: Takashi Tsuchiya: A new look at duality theory for singular SDPs and its implication to convergence of infeasible interior-point algorithms [Slides]
Bruno F. Lourenço (Institute of Statistical Mathematics)
Keiichi Morikuni (University of Tsukuba)
Mirai Tanaka (Institute of Statistical Mathematics)