Program for stream Conic optimization: theory, algorithms and applications

WC-02: Conic and Semidefinite Optimization
Stream: Conic optimization: theory, algorithms and applications
Room: M:O
Chair(s): Miguel Anjos

• Learning to Relax Nonconvex Quadratically Constrained Quadratic Programs
  Burak Kocuk, Buket Özen
• Beyond Traditional PCA: The Two-Step-SDP Algorithm for Data Analysis
  Eloisa Macedo
• Semidefinite liftings for the complex cut polytope
  Miguel Anjos, Lennart Sinjorgo, Renata Sotirov

WD-02: Conic and polynomial optimization
Stream: Conic optimization: theory, algorithms and applications
Room: M:O
Chair(s): Immanuel Bomze

• Uncertain standard quadratic optimization under distributional assumptions: a chance-constrained epigraphic approach
  Immanuel Bomze, Daniel de Vicente
• On Tractable Convex Relaxations of Standard Quadratic Optimization Problems under Sparsity Constraints
  Bo Peng, Immanuel Bomze, Yuzhou Qiu, E. Alper Yildirim
• New results for sparse conic reformulations
  Markus Gabl

WE-02: Recent advances in computer-aided analyses of optimization algorithms I
Stream: Conic optimization: theory, algorithms and applications
Room: M:O
Chair(s): Adrien Taylor, Manu Upadhyaya

• Last-Iterate Convergence of Extragradient-based Methods
  Eduard Gorbunov, Adrien Taylor, Samuel Horvath, Nicolas Loizou, Gauthier Gidel
• Automated tight Lyapunov analysis for first-order methods
  Manu Upadhyaya, Sebastian Banert, Adrien Taylor, Pontus Giselsson
• Second-order interpolation conditions for univariate functions, towards a tight analysis of second-order optimization methods
  Anne Rubbens, Nizar Bousselmi, Julien Hendrickx, François Glineur
• Analysis of Second-Order Methods via non-convex Performance Estimation
  Nizar Bousselmi, Anne Rubbens, Julien Hendrickx, François Glineur

WF-02: Recent advances in computer-aided analyses of optimization algorithms II
Stream: Conic optimization: theory, algorithms and applications
Room: M:O
Chair(s): Adrien Taylor, Manu Upadhyaya

• Exact worst-case convergence rates of gradient descent: a complete analysis for all constant stepsizes over nonconvex and convex functions
  Teodor Rotaru, François Glineur, Panagiotis Patrinos
• A Linear-Quadratic Program for Estimating Performance of Convex Optimization Algorithm
  Ashkan Panahi
• On the convergence rate of the difference-of-convex algorithm (DCA)
  Hadi Abbaszadehpeivasti
• Non-expansiveness for frugal resolvent splitting methods, using PEP
  Anton Åkerman, Emanuele Naldi, Enis Chenchene, Sebastian Banert, Pontus Giselsson

TB-02: Solver-based optimization algorithms
Stream: Conic optimization: theory, algorithms and applications
Room: M:O
Chair(s): Yassine Kamri

• Numerical design of optimized first-order methods
  Yassine Kamri, Julien Hendrickx, François Glineur
• Minimization of a sum of pointwise minimum of finite collections of convex functions.
  Guillaume Van Dessel, François Glineur

TD-02: Recent advances in computer-aided analyses of optimization algorithms III
Stream: Conic optimization: theory, algorithms and applications
Room: M:O
Chair(s): Adrien Taylor, Manu Upadhyaya

• Provable non-accelerations of the heavy-ball method
  Aymeric Dieuleveut, Adrien Taylor, Baptiste Goujaud
• Provable non-accelerations of the heavy-ball method
  Baptiste Goujaud, Adrien Taylor, Aymeric Dieuleveut
• Exact convergence rates of the last iterate in subgradient methods
  François Glineur, Moslem Zamani
• Algorithms with learned deviations
  Sebastian Banert