Program

WA-01: Opening session
Stream: Opening session
Room: M:A
Chair(s): Pontus Giselsson

WB-01: Plenary I - Gabriel Peyré
Stream: Plenaries
Room: M:A
Chair(s): Pontus Giselsson

• Conservation laws for gradient flows
  Gabriel Peyré

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

WC-03: Optimization in neural architectures I
Stream: Optimization in neural architectures: convergence and solution characterization
Room: M:J
Chair(s): Manish Krishan Lal, Maria-Luiza Vladarean

• Optimization dynamics of equivariant neural networks
  Axel Flinth
• Understanding neural architectures via projection onto sets of generalized bilinear constraints
  Manish Krishan Lal

WC-04: Optimization in regression, classification and learning I
Stream: Optimization in regression, classification and learning
Room: M:M
Chair(s): Paula Amaral

• Machine learning outcome prediction model-based radiotherapy treatment plan optimization using the open-source toolkit pyanno4rt
  Tim Ortkamp, Martin Frank, Oliver Jäkel, Niklas Wahl
• Use of Machine Learning techniques in predicting the course of relapsing-remitting MS in individual patients
  Raffaele Mariosa, Laura Palagi
• White box models in classification
  Paula Amaral, Rui Malha, Tiago Dias

WC-05: Optimization for learning I
Stream: Optimization for learning
Room: M:N
Chair(s): Manu Upadhyaya

• Incorporating History and Deviations in Forward-Backward Splitting
  Pontus Giselsson
• Optimal Acceleration for Minimax and Fixed-Point Problems is Not Unique
  TaeHo Yoon, Jaeyeon Kim, Jaewook Suh, Ernest Ryu
• Accelerated Algorithms For Nonlinear Matrix Decomposition With The Relu Function
  Giovanni Seraghiti, Arnaud Vandaele, Margherita Porcelli, Nicolas Gillis

WC-06: Advances in monotone inclusions and related methods
Stream: Methods for non-/monotone inclusions and their applications
Room: M:H
Chair(s): Dimitri Papadimitriou

• Warped proximal iterations for solving nonmonotone inclusions and applications
  Dimitri Papadimitriou, Cong Bang Vu
• Revisiting Inexact Fixed-Point Iterations for Min-Max Problems: Stochasticity and Structured Nonconvexity
  Ahmet Alacaoglu, Donghwan Kim, Stephen Wright
• Set-valued IFS for the Analysis of Iterative Methods in Non-Convex Optimization
  Allahkaram Shafiei

WC-07: Optimization applications I
Stream: Optimization applications
Room: M:I
Chair(s): Jacopo Maria Ricci

• Derivative-Free Optimization Applied to Hydraulic Coefficient Estimation
  Fabio Fortunato Filho, José Mario Martínez
• MAD risk parity portfolios
  Jacopo Maria Ricci, Cagin Ararat, Francesco Cesarone, Mustafa Pinar
• Efficient computation of convex hull prices with level and subgradient methods: a computational comparison of dual methods
  Sofiane Tanji, yassine kamri, François Glineur, Mehdi Madani

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

WD-03: Optimization in neural architectures II
Stream: Optimization in neural architectures: convergence and solution characterization
Room: M:J
Chair(s): Maria-Luiza Vladarean, Manish Krishan Lal

• Vanishing Gradients in Reinforcement Finetuning of Language Models
  Noam Razin
• A phase transition between positional and semantic learning in a solvable model of dot-product attention
  Hugo Cui, Freya Behrens, Florent Krzakala, Lenka Zdeborová
• On the spectral bias of two-layer linear networks
  Aditya Varre

WD-04: BARON Tutorial
Stream: Tutorials
Room: M:M
Chair(s): Yi Zhang

• BARON Tutorial
  Yi Zhang

WD-05: Optimization for learning II
Stream: Optimization for learning
Room: M:N
Chair(s): Manu Upadhyaya

• Compressed Gradient Descent with Matrix Stepsizes for Non-Convex Optimization
  Hanmin Li, Avetik Karagulyan, Peter Richtarik
• Optimization flows landing on the Stiefel manifold: continuous-time flows, deterministic and stochastic algorithms
  Bin Gao, P.-A. Absil
• Is maze-solving parallelizable?
  Romain Cosson

WD-06: Linear Programming
Stream: Methods for non-/monotone inclusions and their applications
Room: M:H
Chair(s): Dimitri Papadimitriou

• Fundamental properties of absolute value linear programming problems
  Milan Hladík
• Intensity Modulated Radiotherapy Planning through Linear Programming under uncertainties
  Nicole Cristina Cassimiro de Oliveira, Aurelio Oliveira
• New techniques for finding MIP formulations for combinatorial disjunctive constraints
  Peter Dobrovoczki, Tamas Kis

WD-07: Optimization applications II
Stream: Optimization applications
Room: M:I
Chair(s): Edoardo Cesaroni

• SIMP-Based Topology Optimization Of 3D Magnetic Circuits With Mechanical Constraints
  Zakaria HOUTA, Nicolas LEBBE, Thomas HUGUET, Frédéric MESSINE
• Enhancing Cost-Optimal Operation of Offshore Hydrogen-Based Power-to-X System
  Nikola Mößner
• Formulation of an ML-based model for the Assessment of Maximum Sprint Capability in Elite Soccer Players
  Edoardo Cesaroni

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

WE-03: Structured sparse optimization
Stream: Variational analysis: theory and algorithms
Room: M:J
Chair(s): Xiaoqi Yang

• Mix Sparse Optimization: Theory and Applications
  Yaohua Hu
• Efficient Low-rank Identification via Accelerated Iteratively Reweighted Nuclear Norm Minimization
  Hao Wang
• An Inexact Projected Regularized Newton Method for Fused Zero-norms Regularization Problems
  Yuqia Wu, Shaohua Pan, Xiaoqi Yang
• Projectional coderivatives with applications
  Xiaoqi Yang

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

WE-05: Randomized optimization algorithms part 1/2
Stream: Randomized optimization algorithms
Room: M:N
Chair(s): Laurent Condat

• An Inexact Restoration based algorithm with random models for unconstrained noisy optimization
  Simone Rebegoldi, Benedetta Morini
• An Optimal Structured Zeroth-order Algorithm for Non-smooth Optimization
  Cesare Molinari
• Random Newton-type Iterations with Application to Electronic Structure Determination
  Titus Pinta
• A variable metric proximal stochastic gradient method with dynamical variance reduction
  Andrea Sebastiani, Pasquale Cascarano, Giorgia Franchini, Erich Kobler, Federica Porta

WE-06: Higher-order Methods in Mathematical Programming I
Stream: Challenges in nonlinear programming
Room: M:H
Chair(s): Mathias Staudigl

• Spectral Preconditioning for Gradient Methods on Graded Non-convex Functions
  Nikita Doikov
• Barrier Algorithms for Constrained Non-Convex Optimization
  Pavel Dvurechensky, Mathias Staudigl
• Accelerated cubic regularized quasi-newton methods
  Dmitry Kamzolov
• Relaxation Approaches for Nonlinear Sparse Optimization Problems
  Steffensen Sonja

WE-07: Optimization applications III
Stream: Optimization applications
Room: M:I
Chair(s): Atanu Maji

• A homotopy continuation method for flowsheet optimization
  David Mogalle, Tobias Seidel, Michael Bortz, Karl-Heinz Küfer
• An integrated optimization-simulation system for the repair sequence problem of electricity distribution networks
  Atanu Maji, Anna Livia Croella, Laura Palagi, Alberto Tofani
• Financial optimization routine for hybrid distributed power generation with battery storage system
  Paulo Rotella Junior, Arthur Leandro Guerra Pires, Luiz Celio Souza Rocha, Karel Janda
• The Bin Packing Problem with Setups: properties and formulations
  Fabio Ciccarelli, Roberto Baldacci, Stefano Coniglio, Fabio Furini

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

WF-03: Splitting algorithms
Stream: Variational analysis: theory and algorithms
Room: M:J
Chair(s): Francisco Javier Aragón Artacho

• A splitting method for computing Wasserstein Barycenters
  Welington de Oliveira, Daniel Mimouni, Malisani Paul, Jiamin Zhu
• Regularity of sets under a reformulation in a product space of reduced dimension
  Rubén Campoy
• First-order splitting methods for decentralized optimization
  Felipe Atenas, Matthew Tam, Minh N. Dao
• The Boosted Double-Proximal Subgradient Algorithm for Nonconvex Optimization
  Francisco Javier Aragón Artacho

WF-04: Multiobjective Optimization I
Stream: Multiobjective optimization
Room: M:M
Chair(s): Radu Strugariu

• On an open problem related to the Gale's example in conic linear programming
  Constantin Zalinescu
• Conic cancellation laws and applications
  Marius Durea
• Sharp solutions for nonsmooth optimization problems under generalized convexity
  Radu Strugariu
• Solving vector optimization problems with ADMM
  Daniel Hernandez Escobar, Joakim da Silva, Jens Sjölund

WF-05: Randomized optimization algorithms part 2/2
Stream: Randomized optimization algorithms
Room: M:N
Chair(s): Egor Shulgin, Laurent Condat

• Sketch-and-Project Meets Newton Method: Global O(1/k^2) Convergence with Low-Rank Updates
  Slavomír Hanzely
• TAMUNA: Doubly-Accelerated Distributed Optimization with Local Training, Compression, and Partial Participation
  Laurent Condat
• Unveiling the Power of Adaptive Methods Over SGD: A Parameter-Agnostic Perspective
  Xiang Li

WF-06: Stochastic Gradient Methods: Bridging Theory and Practice
Stream: Challenges in nonlinear programming
Room: M:H
Chair(s): Simon Weissmann

• Stochastic Optimization under Hidden Convexity
  Ilyas Fatkhullin, Niao He, Yifan Hu
• On Almost Sure Convergence Rates for Stochastic Gradient Methods
  Sara Klein
• Optimal sampling for stochastic and natural gradient descent
  Robert Gruhlke, Philipp Trunschke, Anthony Nouy
• Stochastic gradient methods and tame geometry
  Johannes Aspman, Jiri Nemecek, Vyacheslav Kungurtsev, Fabio V. Difonzo, Jakub Marecek

WF-07: Regularization methods for Machine Learning and Inverse Problems
Stream: Optimization for Inverse Problems and Machine Learning
Room: M:I
Chair(s): Emanuele Naldi

• On the Bredies-Chenchene-Lorenz-Naldi algorithm
  Shambhavi Singh
• An optimal structured zeroth-order algorithm for non-smooth optimization
  Marco Rando, Cesare Molinari, Lorenzo Rosasco, Silvia Villa
• On learning the optimal regularization parameter in inverse problems
  Jonathan Chirinos Rodriguez
• Adaptive Bregman-Kaczmarz: An Approach to Solve Linear Inverse Problems with Independent Noise Exactly
  LIONEL TONDJI

TA-01: Plenary II - Amir Beck
Stream: Plenaries
Room: M:A
Chair(s): Giancarlo Bigi

• New results on the multi-dimensional linear discriminant analysis problem
  Amir Beck

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

TB-03: In memory of Georg Still - part 1
Stream: In memory of Georg Still
Room: M:J
Chair(s): Oliver Stein

• On the weakest constraint qualification for sharp local minimizers
  Oliver Stein, Maximilian Volk
• Copositive and semi-infinite optimization
  Mirjam Duer
• A reflection on the work of Georg Still on semi-infinite linear optimization
  Etienne De Klerk

TB-04: Optimization in regression, classification and learning II
Stream: Optimization in regression, classification and learning
Room: M:M
Chair(s): Paula Amaral

• Memetic Differential Evolution Methods for Semi-Supervised Clustering
  Pierluigi Mansueto, Fabio Schoen
• Solving Kernel Ridge Regression with Gradient Descent for a Non-Constant Kernel
  Oskar Allerbo
• Matrix-wise L0-constrained Sparse Nonnegative Least Squares
  Nicolas Nadisic, Arnaud Vandaele, Jeremy Cohen, Nicolas Gillis

TB-05: Optimization for learning III
Stream: Optimization for learning
Room: M:N
Chair(s): Max Nilsson

• MAST: Model-Agnostic Sparsified Training
  Egor Shulgin, Peter Richtarik
• Online Learning and Information Exponents: The Importance of Batch size & Time/Complexity Tradeoffs
  Stephan Ludovic
• Compressed and distributed least-squares regression: convergence rates with applications to Federated Learning
  Constantin Philippenko, Aymeric Dieuleveut

TB-06: Advances in Semi-Definite Programming
Stream: Challenges in nonlinear programming
Room: M:H
Chair(s): Pavel Dvurechensky

• A conditional gradient homotopy method with applications to Semidefinite Programming
  Mathias Staudigl, Pavel Dvurechensky, Shimrit Shtern
• SDP Relaxations for Training ReLU Activation Neural Networks
  Karthik Prakhya, TOLGA BIRDAL, Alp Yurtsever
• Learning quantum Hamiltonians at any temperature in polynomial time with Chebyshev and bit complexity
  Ales Wodecki, Jakub Marecek

TB-07: Global optimization I
Stream: Global optimization
Room: M:I
Chair(s): Sonia Cafieri

• Improved branch-and-bound for integer D-Optimality
  Jon Lee
• On Model Generation and Decomposition for Global Optimization and Machine Learning using the Generate-and-Solve Approach
  Ivo Nowak
• Complex geometrical test for optimality conditions in Interval Branch and Bound method
  Boglárka G.-Tóth, Mihály Gencsi

TC-02: Developments in interior point methods
Stream: Developments in interior point methods
Room: M:O
Chair(s): Martin Skovgaard Andersen, Utkarsh Detha

• Pushing the limits of interior methods for nonlinear optimization
  Anders Forsgren, Pim Heeman
• Clarabel: An interior point solver for conic optimization
  Yuwen Chen
• A low-rank error correction technique for improving approximate factorisation preconditioners
  Andreas Bock

TC-03: In memory of Georg Still - part 2
Stream: In memory of Georg Still
Room: M:J
Chair(s): Mirjam Duer

• A generic analysis for multi-leader-disjoint followers games:  bilevel problems first
  Gemayqzel Bouza Allende
• Genericity and stability in linear conic programming
  Bolor Jargalsaikhan, Mirjam Duer, Georg Still
• Two methods for the maximization of homogeneous polynomials over the simplex
  Faizan Ahmed

TC-04: Multiobjective Optimization II
Stream: Multiobjective optimization
Room: M:M
Chair(s): Firdevs Ulus

• Adapting the DMulti-MADS algorithm to mixed-integer multiobjective derivative-free optimization
  Ludovic Salomon, Sébastien Le Digabel, Christophe Tribes
• Numerical tests of a global solver for optimistic semivectorial bilevel problems
  Daniel Hoff, Gabriele Eichfelder
• Weight Space Decomposition for Multiobjective Linear Programming in the Context of Equitable Optimization
  Firdevs Ulus, Ozlem Karsu

TC-05: Recent advances in bilevel optimization I
Stream: Bilevel optimization: strategies for complex decision-making
Room: M:N
Chair(s): Alp Yurtsever

• Computing synthetic controls using bilevel optimization
  Pekka Malo
• Smooth over-parametrized solvers for sparse optimisation
  Clarice Poon

TC-06: Stochastic methods and applications
Stream: Methods for non-/monotone inclusions and their applications
Room: M:H
Chair(s): Feifei Hu

• Optimization for a car sharing systems using a queueing network with correlated arrival flows and moving servers
  CHESOONG KIM
• Stochastic optimal power flow problem using interior point methods with block structure
  Aurelio Oliveira, Catalina Jaramillo Villalba
• Gradient Descent for Noisy Optimization
  Feifei Hu

TC-07: Global optimization II / MINLP
Stream: Global optimization
Room: M:I
Chair(s): Sonia Cafieri

• Solving MINLPs to Global Optimality with FICO Xpress Solver
  Tristan Gally
• Global optimization of continuous and discrete nonlinear programs with BARON
  Yi Zhang, Nikolaos Sahinidis
• On computing upper bounds in nonlinear problems involving disjunctive constraints
  Sonia Cafieri, Marcel Mongeau

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

TD-03: Variational techniques and subdifferentials
Stream: Variational analysis: theory and algorithms
Room: M:J
Chair(s): Abderrahim Hantoute

• Lagrange duality on DC evenly convex optimization problems via a generalized conjugation scheme
  Maria Dolores Fajardo, Jose Vidal-Nunez
• Smoothing Effect of Epi-convergence and Inf-convolution in Optimization
  Mohammed Ibrahim Abdelkayoum Ghitri, Abderrahim Hantoute
• Robust and continuous metric subregularity in the radius of stability context
  Jesús Camacho
• Discretization and reduction in finite and infinite convex optimization
  Abderrahim Hantoute

TD-04: Multiobjective Optimization III
Stream: Multiobjective optimization
Room: M:M
Chair(s): Gabriela Kovacova

• Circuits in a Box: Multi-Objective Optimization for Analog Electronic Circuits
  Christopher Schneider
• Robust multi-objective stochastic control
  Gabriela Kovacova, Igor Cialenco
• Playing the Budget-Constrained Multi-Battle Contest with Randomized Strategies for Maximizing Winning Probabilities
  Chien-Hsin Chen, Po-An Chen, Wing-Kai Hon

TD-05: Nonsmooth optimization algorithms
Stream: Nonsmooth and nonconvex optimization algorithms
Room: M:N
Chair(s): Susan Ghaderi

• A feasible directions method for nonconvex optimization over linear constraints with a nonsmooth concave regularizer
  Nadav Hallak, Amir Beck
• Spectral and nuclear norms of order three tensors: Complexity and computation
  Zhening Li
• High-order Moreau envelope in nonsmooth convex setting: L-smoothness and inexact gradient method
  Alireza Kabgani, Masoud Ahookhosh
• Scaled gradient methods under convexity and local smoothness
  Susan Ghaderi, Yves Moreau, Masoud Ahookhosh

TD-06: Stochastic methods
Stream: Methods for non-/monotone inclusions and their applications
Room: M:H
Chair(s): Tony Stillfjord

• Almost sure convergence of stochastic Hamiltonian descent methods
  Måns Williamson
• A gradient-free optimisation algorithm
  Ettore Fincato
• Analysis of a class of stochastic component-wise soft-clipping schemes
  Tony Stillfjord, Måns Williamson, Monika Eisenmann

TD-07: Accelerated methods in modern optimization
Stream: Optimization for Inverse Problems and Machine Learning
Room: M:I
Chair(s): Enis Chenchene

• Near-optimal Closed-loop Method via Lyapunov Damping for Convex Optimization
  Camille Castera, Severin Maier, Peter Ochs
• Inertial methods beyond minimizer uniqueness
  Hippolyte Labarrière
• Variance reduction techniques for stochastic proximal point algorithms
  Cheik Traoré

TE-01: Plenary III - Gabriele Eichfelder EUROPT Fellow
Stream: Plenaries
Room: M:A
Chair(s): Giancarlo Bigi, Pontus Giselsson, Oliver Stein

• Multiobjective optimization, uncertainty, and a bit of set optimization
  Gabriele Eichfelder

FA-01: Plenary IV - Sebastian Stich
Stream: Plenaries
Room: M:A
Chair(s): Alp Yurtsever

• A Universal Framework for Federated (Convex) Optimization
  Sebastian Stich

FB-02: First-order methods for multi-level and multi-objective optimization
Stream: Advances in first-order optimization
Room: M:O
Chair(s): Brecht Evens

• Adaptivity in convex optimization beyond minimization
  Puya Latafat, Andreas Themelis, Silvia Villa, Panagiotis Patrinos
• Relying on first-order methods to deal with utility functions-based scalarization in multi-objective optimization
  Lorenzo Lampariello, Simone Sagratella, Valerio Giuseppe Sasso, Vladimir Shikhman

FB-03: In memory of Georg Still - part 3
Stream: In memory of Georg Still
Room: M:J
Chair(s): Oliver Stein

• Parametric optimisation applied to a fitting problem in finance
  Ralf Werner, Dirk Banholzer, Joerg Fliege
• Parametric stationary point sets need MFCQ for stably being topological manifolds
  Harald Guenzel, Daniel Hernandez Escobar, Jan-J Ruckmann
• Global aspects of the continuous reformulation for cardinality-constrained optimization problems
  Vladimir Shikhman, Sebastian Lämmel

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

FB-05: Recent advances in bilevel optimization II
Stream: Bilevel optimization: strategies for complex decision-making
Room: M:N
Chair(s): Alp Yurtsever

• Interior point method based on the optimal value function for bilevel optimization problems
  Yasushi Narushima, Seima Yamamoto
• Asymmetric data-driven interdiction problems with cost uncertainty: a distributionally robust optimization approach
  Sergei Ketkov
• Hyperparameter optimization for kernel-regularized system identification
  Lujing Chen, Martin Skovgaard Andersen, Tianshi Chen

FB-06: Higher-order Methods in Mathematical Programming II
Stream: Challenges in nonlinear programming
Room: M:H
Chair(s): Marianna E.-Nagy

• Analysis of the primal-dual central path for nonlinear semidefinite optimization without the nondegeneracy condition
  Takayuki Okuno
• Developing Extended Memoryless Optimization Algorithms Based on the Ellipsoid Norms
  Saman Babaie-Kafaki
• On a Unified Analysis of Kernel-based Interior Point Algorithms
  Marianna E.-Nagy, Zsolt Darvay, Goran Lesaja, Petra Renáta Rigó, Anita Varga

FC-02: Algorithms for Variational inequalities and equilibria
Stream: Advances in first-order optimization
Room: M:O
Chair(s): Emanuel Laude

• Recent advances in first-order methods for weak Minty variational inequalities
  Thomas Pethick, Ioannis Mavrothalassitis, Volkan Cevher
• Progressive decoupling of linkage problems beyond elicitable monotonicity
  Brecht Evens, Puya Latafat, Panagiotis Patrinos
• Projected solutions for quasi-equilibria
  Giancarlo Bigi

FC-03: In memory of Georg Still - part 4
Stream: In memory of Georg Still
Room: M:J
Chair(s): Mirjam Duer

• How to avoid the normal cone in the subdifferential calculus?
  Marco A. López-Cerdá
• New results on copositive optimization obtained via linear semi-infinite optimization theory
  Miguel Goberna, Andrea Ridolfi, Virginia N. Vera de Serio
• Some sincere thoughts of thanks about Professor Georg Still, our friend
  Gerhard-Wilhelm Weber

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

FC-05: Recent advances in bilevel optimization III
Stream: Bilevel optimization: strategies for complex decision-making
Room: M:N
Chair(s): Alp Yurtsever, Ahmet Alacaoglu

• General single-loop splitting methods for bilevel optimization
  Ensio Suonperä, Tuomo Valkonen
• An adaptively inexact first-order method for bilevel learning
  Mohammad Sadegh Salehi, Matthias J. Ehrhardt, Lindon Roberts
• Adaptive bilevel optimisation
  Kimon Antonakopoulos, Shoham Sabach, Luca Viano, Mingyi Hong, Volkan Cevher

FC-07: Optimization mosaics
Stream: Optimization in regression, classification and learning
Room: M:I
Chair(s): Paula Amaral, Sebastian Lämmel

• Relaxations for the elementary shortest path problem
  Regina Schmidt, Mirjam Duer
• Extended convergence analysis of the Scholtes-type regularization for cardinality-constrained optimization problems
  Sebastian Lämmel, Vladimir Shikhman

FD-02: Deterministic and stochastic optimization beyond Euclidean geometry
Stream: Advances in first-order optimization
Room: M:O
Chair(s): Adrien Taylor, Hadrien Hendrikx

• Horospherically Convex Optimization on Hadamard Manifolds
  Christopher Criscitiello, Jungbin Kim
• Implicit Regularisation of Mirror Flow on Separable Classification Problems
  Radu-Alexandru Dragomir
• ACCELERATED BREGMAN DIVERGENCE OPTIMIZATION WITH SMART: AN INFORMATION GEOMETRIC POINT OF VIEW
  Stefania Petra
• Investigating Variance Definitions for Stochastic Mirror Descent with Relative Smoothness
  Hadrien Hendrikx

FD-03: Variational techniques in optimization
Stream: Variational analysis: theory and algorithms
Room: M:J
Chair(s): Juan Enrique Martínez-Legaz

• The Geometry of Sparsity-Inducing Balls
  Michel De Lara
• Parameter identification in PDEs by the solution of monotone inclusion problems
  Pankaj Gautam, Markus Grasmair
• Closed convex sets that are both Motzkin decomposable and generalized Minkowski sets
  Juan Enrique Martínez-Legaz, Cornel Pintea

FD-04: Optimal control and stochastic optimal control - theory, methods and applications 1
Stream: Optimal control and stochastic optimal control - theory, methods and applications
Room: M:M
Chair(s): Gerhard-Wilhelm Weber

• Analysis of Finance-Human Factor Interactions Using Various Indicators
  Betül Kalaycı, Vilda Purutcuoglu, Gerhard-Wilhelm Weber
• Regime-switching models via stochastic optimal control & robust control theory, with applications in finance and insurance
  Gerhard-Wilhelm Weber, Emel Savku, Ioannis Baltas, Athanasios Yannacopoulos
• Calibration and Higher Lower Partial Moments of Skew Elliptical Distributions
  Kerem Ugurlu

FD-05: Structured nonsmooth optimization
Stream: Nonsmooth and nonconvex optimization algorithms
Room: M:N
Chair(s): Alireza Kabgani

• The Boosted Difference of Convex Functions Algorithm for Value-at-Risk Constrained Portfolio Optimization
  Marah-Lisanne Thormann, Vuong Phan, Alain Zemkoho
• Weak subgradients and radial epiderivatives: calculus and optimization
  Refail Kasimbeyli
• Trust-region methods for relatively smooth weakly convex optimization
  Mohammad Hamed, Masoud Ahookhosh
• Subgradient Methods for Minimizing Paraconvex Functions
  Morteza Rahimi, Masoud Ahookhosh

FD-06: Difference and decomposition methods
Stream: Methods for non-/monotone inclusions and their applications
Room: M:H
Chair(s): Dânâ Davar

• Douglas-Rachford DC methods for generalized DC programming
  AVINASH DIXIT
• Revisiting Frank-Wolfe for Nonconvex Problems
  Hoomaan Maskan, Suvrit Sra, Alp Yurtsever
• Penalty Decomposition methods for convex and nonconvex market equilibrium models
  Giulio Scarponi, Marco Sciandrone
• A derivative-free trust-region method based on finite differences for composite nonsmooth optimization
  Dânâ Davar, Geovani Grapiglia

FD-07: Optimal Transport for Machine Learning and Inverse Problems
Stream: Optimization for Inverse Problems and Machine Learning
Room: M:I
Chair(s): Cheik Traoré

• Gradient flows and kernelization in the Hellinger-Kantorovich (a.k.a. Wasserstein-Fisher-Rao) space
  Jia-Jie Zhu
• Learning Total-Variation Regularization Parameters via Weak Optimal Transport
  Enis Chenchene, Kristian Bredies
• An Optimal Transport-based approach to Total-Variation regularization for the Diffusion MRI problem
  Rodolfo Assereto
• Application of the Opial property in Wasserstein spaces to inexact JKO schemes
  Emanuele Naldi