BEGIN:VCALENDAR VERSION:2.0 PRODID:researchseminars.org CALSCALE:GREGORIAN X-WR-CALNAME:researchseminars.org BEGIN:VEVENT SUMMARY:Defeng Sun (Hong Kong Polytechnic University) DTSTART:20201130T143000Z DTEND:20201130T153000Z DTSTAMP:20260423T021003Z UID:OWOS/25 DESCRIPTION:Title: Se veral Observations about Using the ALM + Semismooth Newton Method for Solv ing Large Scale Semidefinite Programming and Beyond\nby Defeng Sun (Ho ng Kong Polytechnic University) as part of One World Optimization seminar\ n\n\nAbstract\nSemidefinite Programming (SDP) has been one of the major re search fields in optimization during the last three decades and interior p oint methods (IPMs) are perhaps the most robust and efficient algorithms f or solving small to medium sized SDP problems. For large scale SDPs\, IPMs are no longer viable due to their inherent high memory requirements and c omputational costs at each iteration. In this talk\, we will summarize wh at we observed during the last 15 years or so in combining the augmented L agrangian algorithm with the semismooth Newton method for solving the dual of SDP and convex quadratic SDP of large scales. We will emphasize the i mportance of the constraint non-degeneracy in numerical implementations an d the quadratic growth condition in convergence rate analysis. Easy-to-imp lement stopping criteria for the augmented Lagrangian subproblems will als o be introduced. All these features are implemented in the publically avai lable software packages SDPNAl/SDPNAL+ and QSDPNAL.\n\nThe address and pas sword of the zoom room of the seminar are sent by e-mail on the mailinglis t of the seminar one day before each talk\n LOCATION:https://researchseminars.org/talk/OWOS/25/ END:VEVENT END:VCALENDAR