Program for stream Large-scale optimization

WE-04: Large-scale optimization I
Stream: Large-scale optimization
Room: M:M
Chair(s): Max Nilsson

• A divergence-based condition to ensure quantile improvement in black-box global optimization
  Thomas Guilmeau, Emilie Chouzenoux, Víctor Elvira
• Low rank of the matrix LASSO under RIP with consequences for fast large-scale algorithms
  Andrew McRae
• Computing Augustin Information via Hybrid Geodesically Convex Optimization
  Guan-Ren Wang

FB-04: Large-scale optimization II
Stream: Large-scale optimization
Room: M:M
Chair(s): Anton Åkerman

• An interior proximal gradient method for nonconvex optimization
  Alberto De Marchi, Andreas Themelis
• Krasnoselskii-Mann Iterations: Inertia, Perturbations and Approximation
  Daniel Cortild, Juan Peypouquet
• A Fast Optimistic Method for Monotone Variational Inequalities
  Michael Sedlmayer, Dang-Khoa Nguyen, Radu Ioan Bot

FC-04: Large-scale optimization III
Stream: Large-scale optimization
Room: M:M
Chair(s): Anton Åkerman

• A unified Euler--Lagrange system for analyzing continuous-time accelerated gradient methods
  Mitsuru Toyoda, Akatsuki Nishioka, Mirai Tanaka
• An optimal lower bound for smooth convex functions
  Mihai I. Florea
• Coordinate Descent Algorithm for Nonlinear Matrix Decompositions with the ReLU function
  Atharva Awari