Program for stream Nonsmooth and nonconvex optimization

WC-01: NNO 1 - Applications of nonsmooth optimization
Stream: Nonsmooth and nonconvex optimization
Room: C V
Chair(s): Alireza Kabgani

• A New Hybrid Algorithm for Multi-Objective Optimal Spatial Sampling Design
  Elaheh Lotfian, Mohsen Mohammadzadeh
• Comparing Real-World Efficiency of Primal and Dual Methods for Convex Hull Pricing
  Sofiane Tanji, yassine kamri, Mehdi Madani, François Glineur
• Parameter-free nonsmooth unadjusted Langevin algorithm
  Susan Ghaderi, Alireza Kabgani, Masoud Ahookhosh, Yves Moreau

WD-01: NNO 2 - Structured nonconvex optimization
Stream: Nonsmooth and nonconvex optimization
Room: C V
Chair(s): Puya Latafat

• Adaptive nonsmooth trust-region methods via forward-backward envelope
  Mohammad Hamed, Alexander Bodard, Masoud Ahookhosh, Panagiotis Patrinos
• Convergence of Douglas-Rachford Splitting and Primal-Dual Hybrid Gradient in the Absense of Monotonicity
  Brecht Evens, Pieter Pas, Puya Latafat, Panagiotis Patrinos
• High-order proximal-point and Moreau envelope beyond convexity
  Alireza Kabgani, Masoud Ahookhosh

WE-05: NNO 3 - Large-scale optimization
Stream: Nonsmooth and nonconvex optimization
Room: 106
Chair(s): Emanuel Laude

• Convex relaxations for large-scale manifold-valued nonconvex problems with graphical structure
  Robin Kenis
• Pac-Bayesian Learning of Optimization Algorithms
  Michael Sucker
• ResQPASS: solving huge-scale bounded-variable least squares problems
  Bas Symoens, Wim Vanroose

TA-05: NNO 4 - Non-Euclidean optimization
Stream: Nonsmooth and nonconvex optimization
Room: 106
Chair(s): Puya Latafat

• Anisotropic Proximal Gradient
  Emanuel Laude, Panagiotis Patrinos
• Non-Euclidean gradient methods: Convergence, complexity, and applications
  Masoud Ahookhosh, Susan Ghaderi, Yves Moreau
• On the Symmetry Coefficient of Bregman Functions
  Max Nilsson

TB-05: NNO 5 - Optimization and machine learning
Stream: Nonsmooth and nonconvex optimization
Room: 106
Chair(s): Silvia Villa, Cesare Molinari

• Fast convergence of Nesterov-like continuous-time dynamics on Riemannian manifolds
  Tejas Natu
• Unfolding Proximal Networks within Plug and Play algorithms: The Faster, the Better?
  Audrey Repetti

TD-05: NNO 6 - Complexity of nonconvex optimization
Stream: Nonsmooth and nonconvex optimization
Room: 106
Chair(s): Masoud Ahookhosh

• On the Rate of Convergence of the Difference-of-Convex Algorithm (DCA)
  Moslem Zamani, Hadi Abbaszadehpeivasti, Etienne De Klerk
• Yet another fast variant of Newton's method for nonconvex optimization
  Sadok Jerad, Serge Gratton, Philippe L. Toint

FB-05: NNO 7 - Second-order methods for nonsmooth optimization
Stream: Nonsmooth and nonconvex optimization
Room: 106
Chair(s): Behzad Azmi

• A second-order gradient sampling method for nonsmooth optimization
  Bennet Gebken
• Incremental Quasi-Newton methods for nonsmooth and nonconvex optimization
  Gulcin Dinc Yalcin, Frank E. Curtis
• TIkhonov regularization technique in continuous and discrete time optimization
  Mikhail Karapetyants

FC-05: NNO 8 - Nonsmooth optimization algorithms - Part I
Stream: Nonsmooth and nonconvex optimization
Room: 106
Chair(s): Masoud Ahookhosh

• Adaptive linesearch-free proximal algorithms for convex optimization under local Lipschitz continuity of the gradient
  Puya Latafat, Andreas Themelis, Lorenzo Stella, Panagiotis Patrinos
• On the nonmonotone FBS algorithm for a class of infinite-dimensional nonsmooth nonconvex problems
  Behzad Azmi, Marco Bernreuther
• Regularized smoothing for solution mappings of convex problems, with applications to two-stage stochastic programming and some hierarchical problems
  Mikhail Solodov

FD-05: NNO 9 - Nonsmooth optimization algorithms - Part II
Stream: Nonsmooth and nonconvex optimization
Room: 106
Chair(s): Moslem Zamani

• Coordinate descent for SLOPE
  Mathurin Massias
• Linearization Algorithms for Fully Composite Optimization
  Maria-Luiza Vladarean, Nikita Doikov, Martin Jaggi, Nicolas Flammarion
• Operator Splitting Based Newton-type Method for Constrained Optimization
  Titus Pinta