Program

MA-01: Plenary 1
Stream: Plenaries
Room: B100/1001
Chair(s): Selin Ahipasaoglu

• Constrained Optimization via Frank-Wolfe Algorithms
  Sebastian Pokutta

MB-01: Advances in Large-Scale Derivative-Free Optimization
Stream: Zeroth and first-order optimization methods
Room: B100/1001
Chair(s): Francesco Rinaldi, Andrea Cristofari

• Dimensionality reduction techniques for derivative free optimization
  Coralia Cartis
• Solving 10,000-Dimensional Optimization Problems Using Inaccurate Function Values: An Old Algorithm
  Zaikun Zhang
• On the computation of the cosine measure in high dimensions.
  Scholar Sun
• A Novel Stochastic Derivative-Free Trust-Region Algorithm with Adaptive Sampling and Moving Ridge Functions
  Benjamin Rees, Christine Currie, Vuong Phan

MB-02: Optimization and applications
Stream: Nonsmooth and nonconvex optimization
Room: B100/7011
Chair(s): Morteza Rahimi, Arghya Sinha

• A Strongly Convex Framework for Image Reconstruction Using Generic Smoothing Filters
  Arghya Sinha, Kunal N. Chaudhury
• Random embeddings for global optimization: convergence results beyond isotropy
  Roy Makhlouf, Estelle Massart
• Optimization Techniques for Sparse and Structured Solutions in Big Data
  Maurine Wafula, Leah Mutanu
• Mapping Financial Well-Being: A Bayesian Spatial Clustering Analysis of Regional Economic Disparities
  Lok-Yung Wong

MB-03: First-order methods in modern optimization (Part I)
Stream: Large scale optimization: methods and algorithms
Room: B100/4011
Chair(s): Simone Rebegoldi, Andrea Sebastiani

• Learning firmly nonexpansive operators
  Jonathan Chirinos Rodriguez, Emanuele Naldi, Kristian Bredies
• Line search based stochastic gradient methods for learning applications
  Federica Porta
• Convergence rates of regularized quasi-Newton methods without strong convexity
  Shida Wang, Jalal Fadili, Peter Ochs
• LoCoDL: Communication-Efficient Distributed Optimization with Local Training and Compression
  Laurent Condat, Arto Maranjyan, Peter Richtarik

MB-05: Optimization and machine learning I
Stream: Optimization for machine learning
Room: B100/4013
Chair(s): Laurent Condat, Avetik Karagulyan

• Laplacian Regularization in Semi-Supervised Learning with Functional Data
  Zhengang Zhong
• When to Forget? Complexity Trade-offs in Machine Unlearning
  Martin Van Waerebeke, Marco Lorenzi, Gioanni Neglia, Kevin Scaman
• Searching for optimal per-coordinate stepsizes with multidimensional backtracking
  Frederik Kunstner, Victor Sanches Portella, Nick Harvey, Mark Schmidt
• Automatic recommendation of optimization methods through their worst-case complexity
  Sofiane Tanji, François Glineur

MB-06: Nonsmooth optimization: from continuous to discrete Part I
Stream: Nonsmooth and nonconvex optimization
Room: B100/7013
Chair(s): Alberto De Marchi

• Mixed-integer linearity in nonlinear optimization
  Alberto De Marchi
• Lyapunov functions and control for differential inclusions by optimization
  SIGURDUR HAFSTEIN
• Finding and exploiting quadratic underestimators for optimal value functions of nonconvex all-quadratic problems via copositive optimization
  Markus Gabl, Immanuel Bomze

MB-07: Hyperparameter Optimization for Classification
Stream: Bilevel and multilevel optimization
Room: B100/5015
Chair(s): Yaru Qian

• Bilevel hyperparameter optimization for RBF Kernel support vector machines
  Qingna Li
• A highly efficient single-loop smoothing damped Newton method for large-scale bilevel hyperparameter optimization of SVC
  Yixin Wang
• On Constraint Qualifications for MPECs with Applications to Bilevel Hyperparameter Optimization for Machine Learning
  Jiani Li
• Bilevel hyperpaGlobal relaxation-based LP-Newton method for multiple hyperparameter selection in support vector classification
  Yaru Qian

MB-08: Systematic and computer-aided analyses I: Analyses of proximal splittings methods & friends
Stream: Systematic and computer-aided analyses of optimization algorithms
Room: B100/7007
Chair(s): Aymeric Dieuleveut

• The Augmented Lagrangian Method for Infeasible Convex Optimization
  Roland Andrews
• Difference-of-convex algorithm with weakly convex functions: improved splitting technique and equivalence with proximal gradient descent
  Teodor Rotaru, Panagiotis Patrinos, François Glineur
• Forward-backward type splitting algorithms with minimal lifting I
  Anton Åkerman, Emanuele Naldi, Enis Chenchene, Pontus Giselsson
• Forward-backward type splitting algorithms with minimal lifting II
  Emanuele Naldi, Anton Åkerman, Enis Chenchene, Pontus Giselsson

MB-09: Generalized convexity and monotonicity 1
Stream: Generalized convexity and monotonicity
Room: B100/8013
Chair(s): Krzysztof Rutkowski

• Proximal Algorithms for a class of abstract convex functions
  The Hung Tran
• Lagrangian duality for generalized convex optimization problems
  Monika Syga, Ewa Bednarczuk
• On Mangasarian-Fromovitz condition in smooth inifinte programming
  Krzysztof Rutkowski, Ewa Bednarczuk, Krzysztof Leśniewski
• Similarity-based fuzzy clustering scientific articles: potentials and challenges from mathematical and computational perspectives
  Thi Huong Vu, Ida Litzel, Thorsten Koch

MB-10: Optimization, Learning, and Games I
Stream: Optimization, Learning, and Games
Room: B100/8011
Chair(s): Georgios Piliouras

• Convex Markov Games
  Ian Gemp
• The Complexity of Two-Team Polymatrix Games with Independent Adversaries
  Alexandros Hollender, Gilbert Maystre, Sai Ganesh Nagarajan
• From min-max to harmonic games: Regret, learning, and the role of optimism
  Panayotis Mertikopoulos
• Revenue Efficiency of First Price Auctions over Approximate Correlated Equilibrium
  Efstratios Skoulakis

MB-11: Optimal and stochastic optimal control 1
Stream: Optimal and stochastic optimal control
Room: B100/5017
Chair(s): Gerhard-Wilhelm Weber

• Optimal model description of finance and human factor indices
  Betül Kalaycı, Vilda Purutcuoglu, Gerhard-Wilhelm Weber
• Dynamic Programming using Average-Value-at-Risk Criteria
  Kerem Ugurlu
• Interpretable Machine Learning Approach for Nonlinear Control
  Edmondo Minisci, Giulio Avanzini
• Stochastic differential games for optimal investment problems in a Markov regime-switching jump-diffusion market
  Gerhard-Wilhelm Weber, Emel Savku

MB-12: Portfolio optimization
Stream: Applications: Finance
Room: B100/8009
Chair(s): Houduo Qi

• An Optimization Study of Diversification Return Portfolios
  Houduo Qi
• Coherent risk measurement and return analysis on non-reflexive Banach space
  Hedvig Gal
• Adaptive minimum variance portfolio selection by linear shrinkage and expansion
  Xiang Zhao, Selin Ahipasaoglu, Houduo Qi

MB-13: True sparsity in Standard Quadratic Problems
Stream: Sparsity guarantee and cardinality-constrained (MI)NLPs
Room: B100/6009
Chair(s): Immanuel Bomze

• Novel and Tractable Convex Relaxations of Standard Quadratic Optimization Problems under Cardinality Constraints
  E. Alper Yildirim, Immanuel Bomze, Bo Peng, Yuzhou Qiu
• From Keynes to Markowitz and back — optimize portfolios by strict cardinality control
  Immanuel Bomze, Paula Amaral, Yuan Chen, Bo Peng
• Cardinality-Constrained Optimization for Large-Scale Portfolio
  Yuan Chen, Immanuel Bomze, Nikolaus Hautsch, Bo Peng

MC-01: Strategies to Improve Zeroth-Order Optimization Methods
Stream: Zeroth and first-order optimization methods
Room: B100/1001
Chair(s): Francesco Rinaldi, Andrea Cristofari

• Improving the robustness of zeroth-order optimization solvers
  Stefan M. Wild
• Derivative free optimization with structured random directions
  Silvia Villa, Marco Rando, Cheik Traoré, Cesare Molinari, Lorenzo Rosasco
• Enhancing finite-difference-based derivative-free optimization with machine learning
  Geovani Grapiglia, Timothé Taminiau, Estelle Massart
• A derivative-free algorithm based on resilient positive spanning sets
  Sébastien Kerleau, Clément Royer

MC-02: Matrix factorization
Stream: Nonsmooth and nonconvex optimization
Room: B100/7011
Chair(s): Atharva Awari

• Alternating Direction Method of Multipliers for Nonlinear Matrix Decompositions
  Atharva Awari, Nicolas Gillis, Arnaud Vandaele
• Instance-wise Distributionally Robust Nonnegative Matrix Factorization
  Amjad Seyedi, Nicolas Gillis
• Implicit Bias in Matrix Factorization and its Explicit Realization in a new Architecture
  Yikun Hou, Suvrit Sra, Alp Yurtsever

MC-03: First-order methods in modern optimization (Part II)
Stream: Large scale optimization: methods and algorithms
Room: B100/4011
Chair(s): Simone Rebegoldi, Andrea Sebastiani

• Optimization Techniques for Learning Multi-Index Models
  Hippolyte Labarrière, Shuo Huang, Ernesto De Vito, Lorenzo Rosasco, Tomaso Poggio
• Neural Blind Deconvolution for Poisson Data
  Alessandro Benfenati, Ambra Catozzi, Valeria Ruggiero
• Adaptively Inexact Bilevel Learning via Primal-Dual Differentiation
  Mohammad Sadegh Salehi
• Alternate Through the Epochs Stochastic Gradient for Multi-Task Neural Networks
  Stefania Bellavia, Francesco Della Santa, Alessandra Papini

MC-05: Optimization and machine learning II
Stream: Optimization for machine learning
Room: B100/4013
Chair(s): Laurent Condat

• Stabilized Proximal-Point Methods for Federated Optimization
  Xiaowen Jiang, Anton Rodomanov, Sebastian Stich
• A primal-dual algorithm for variational image reconstruction with learned convex regularizers
  Hok Shing Wong
• Entropic Mirror Descent for Linear Systems: Polyak’s Stepsize and Implicit Bias
  Alexander Posch, Yura Malitsky

MC-06: Nonsmooth optimization: from continuous to discrete Part II
Stream: Nonsmooth and nonconvex optimization
Room: B100/7013
Chair(s): Alberto De Marchi

• Paley graphs, stable sets and the exact subgraph hierarchy: Bad and good news
  Elisabeth Gaar, Dunja Pucher
• A modified proximal point algorithm involving generalized nonexpansive mappings
  Izhar Uddin
• Combining Gradient Information and Primitive Directions for High-Performance Mixed-Integer Optimization
  Pierluigi Mansueto, Matteo Lapucci, Giampaolo Liuzzi, Stefano Lucidi

MC-07: Bilevel Optimization in Data Science
Stream: Bilevel and multilevel optimization
Room: B100/5015
Chair(s): Samuel Ward

• Bi-level optimization in machine learning: instances, acceleration and implicit bias
  Zhanxing Zhu
• Adversarial training under restricted data manipulation using pessimistic bilevel optimisation
  David Benfield
• An Exploratory Study on Clustering Models under Perturbations Based on a Bilevel Optimization Framework
  Yutong Zheng
• Mathematical programs with complementarity constraints and application to hyperparameter tuning for nonlinear support vector machines
  Samuel Ward

MC-08: Systematic and computer-aided analyses II: Systematic algorithmic design approaches
Stream: Systematic and computer-aided analyses of optimization algorithms
Room: B100/7007
Chair(s): François Glineur

• Exact Verification of First-Order Methods via Mixed-Integer Linear Programming
  Vinit Ranjan, Jisun Park, Stefano Gualandi, Andrea Lodi, Bartolomeo Stellato
• Tight Analysis of Second-Order Optimization Methods via Interpolation of generalized Hessian Lipschitz Univariate Functions
  François Glineur, Nizar Bousselmi, Julien Hendrickx, Anne Rubbens
• Forward-backward algorithms with deviations
  Sebastian Banert

MC-09: Generalized convexity and monotonicity 2
Stream: Generalized convexity and monotonicity
Room: B100/8013
Chair(s): Vuong Phan

• Douglas--Rachford-based splitting for generalized DC programming with applications to signal recovery
  Minh N. Dao
• Robust Regression and Outlier Detection with DC Programming
  Marah-Lisanne Thormann, Vuong Phan, Alain Zemkoho
• Hilbert direct integrals of monotone operators
  Nhut Minh Bui
• Curve Based Convex Functions and its Optimality 
  Qamrul Hasan Ansari

MC-10: Optimization, Learning, and Games II
Stream: Optimization, Learning, and Games
Room: B100/8011
Chair(s): Antonios Varvitsiotis

• Robust Generalized Nash Equilibria
  Mauro Passacantando, Sara Mattia
• A Stable-Set Bound and Maximal Numbers of Nash Equilibria in Bimatrix Games
  Constantin Ickstadt
• Sum-of-squares for Optimal Transport: The Gromov Wasserstein Problem
  Yong Sheng Soh
• Inducing Cooperation in Social Dilemmas
  Stefanos Leonardos

MC-11: Advances in conic optimization
Stream: Conic Optimization
Room: B100/5017
Chair(s): Miguel Anjos

• Efficient moment hierarchy for quadratic programming using moment cones
  Shengding Sun, Fatma Kilinc-Karzan
• Obtuse almost-equiangular sets
  Bram Bekker
• A Positive Semidefinite Safe Approximation of Multivariate Distributionally Robust Constraints Determined by Simple Functions
  Jan Rolfes, Jana Dienstbier, Frauke Liers

MC-12: Robust optimisation and its applications
Stream: Applications: AI, uncertainty management and sustainability
Room: B100/8009
Chair(s): Belen Martin Barragan

• Solving a convex quadratic maximization problem appearing in some distributionally robust problem
  Mathis Azema, Wim van Ackooij, vincent leclere
• Counterfactual explanations under uncertainty
  Antonio Navas-Orozco, Emilio CARRIZOSA
• A robust variant to the smart predict-then-optimize approach.
  Belen Martin Barragan, Aakil Caunhye, Xuefei Lu
• Beyond One‑Hot Labels: KL‑Divergence Training with Empirical Distributions for Faster Optimization
  Arman Bolatov

MC-13: Cardinality control in optimization problems for Data Science
Stream: Sparsity guarantee and cardinality-constrained (MI)NLPs
Room: B100/6009
Chair(s): E. Alper Yildirim

• An Efficient Network-aware Direct Search Method for Influence Maximization
  Matteo Bergamaschi, Francesco Rinaldi, Francesco Tudisco, Sara Venturini
• Strict cardinality control in feature selection for linear Support Vectors: a scalable conic decomposition approach
  Laura Palagi, Immanuel Bomze, Federico D’Onofrio, Bo Peng
• Exact sparsity control for multiclass linear Support Vector Machines
  Pedro Duarte Silva, Immanuel Bomze, Laura Palagi, Bo Peng, Marta Monaci, Federico D'Onofrio

MD-01: Derivative-Free Optimization Methods for challenging applications: Handling Nonsmoothness and Constraints
Stream: Zeroth and first-order optimization methods
Room: B100/1001
Chair(s): Francesco Rinaldi, Andrea Cristofari

• Derivative-free Penalty-IPM for nonsmooth constrained optimization
  Andrea Brilli, Youssef Diouane, Sébastien Le Digabel, Giampaolo Liuzzi, Christophe Tribes
• Complexity of a Riemannian Direct-search algorithm
  Bastien Cavarretta, Clément Royer, Florian Yger, Florentin Goyens
• TRFD: A derivative-free trust-region method based on finite differences for composite nonsmooth optimization
  Dânâ Davar, Geovani Grapiglia
• On the Pareto-efficient points of Simple Constrained Multiobjective Problems
  Dimo Brockhoff

MD-02: Optimization in machine Learning
Stream: Nonsmooth and nonconvex optimization
Room: B100/7011
Chair(s): Alireza Kabgani, Lorenzo Ciarpaglini

• Provable Reduction in Communication Rounds for Non-Smooth Convex Federated Learning
  Karlo Palenzuela, Ali Dadras, Alp Yurtsever
• Revisiting LocalSGD and SCAFFOLD: Improved Rates and Missing Analysis
  Ruichen Luo, Sebastian Stich, Samuel Horvath, Martin Takac
• Convex Formulations For Training Two-Layer ReLU Neural Networks
  Karthik Prakhya, TOLGA BIRDAL, Alp Yurtsever
• Exploring Step Size Adaptation in Large-Scale Deep Learning Optimization
  Lorenzo Ciarpaglini, Laura Palagi, Diego Scuppa, Marco Sciandrone

MD-03: Variational Methods in Set and Vector Optimization
Stream: Multiobjective and Vector Optimization
Room: B100/4011
Chair(s): Radu Strugariu

• Subdifferential conditions for sharp and approximate solutions in nonsmooth optimization
  Marius Durea
• Optimality conditions for nondominated and approximate solutions in vector optimization with variable domination structure
  Radu Strugariu
• On Derivative-Free Methods for Solving Set-based Robust Counterparts to Uncertain Multiobjective Optimization Problems
  Christian Günther

MD-05: Relaxed Smoothness and Convexity Assumptions in Optimization for Machine Learning
Stream: Optimization for machine learning
Room: B100/4013
Chair(s): Eduard Gorbunov

• Loss Landscape Characterization of Neural Networks without Over-Parametrization
  Rustem Islamov
• Methods for Convex (L0,L1)-Smooth Optimization: Clipping, Acceleration, and Adaptivity
  Eduard Gorbunov
• Optimizing $(L_0, L_1)$-Smooth Functions by Gradient Methods
  Anton Rodomanov, Daniil Vankov, Angelia Nedich, Lalitha Sankar, Sebastian Stich
• A Third-Order Perspective on Newton’s Method and its Application in Federated Learning
  Slavomír Hanzely

MD-06: Smoothing techniques for nonsmooth optimization
Stream: Nonsmooth and nonconvex optimization
Room: B100/7013
Chair(s): Olivier Fercoq

• Second-order proximal-gradient methods for avoiding nonsmooth strict saddle points
  Alexander Bodard, Masoud Ahookhosh, Panagiotis Patrinos
• A Proximal Variable Smoothing for Nonsmooth Minimization of the Sum of Three Functions Including Weakly Convex Composite Function
  Keita Kume, Isao Yamada
• Analyzing the speed of convergence in nonsmooth optimization via the Goldstein epsilon-subdifferential
  Bennet Gebken
• Minimizing the smoothed gap to solve saddle point problems
  Olivier Fercoq

MD-07: Methods for simple and nonsmooth bilevel optimization
Stream: Bilevel and multilevel optimization
Room: B100/5015
Chair(s): Sebastian Lämmel

• A Simple Algorithm for Simple Bilevel Programming
  Joydeep Dutta
• Approximation and exact penalization in simple bilevel variational problems
  Riccardo Tomassini, Giancarlo Bigi
• Anomalies of the Scholtes regularization for mathematical programs with complementarity constraint
  Sebastian Lämmel, Vladimir Shikhman

MD-08: Systematic and computer-aided analyses III: noisy gradient methods and fixed-point algorithms
Stream: Systematic and computer-aided analyses of optimization algorithms
Room: B100/7007
Chair(s): Baptiste Goujaud, François Glineur

• Tight analyses of first-order methods with error feedback
  Daniel Berg Thomsen
• On fundamental proof structures in first-order optimization
  Aymeric Dieuleveut, Baptiste Goujaud, Adrien Taylor
• An invariance theory for complete characterization of exact optimal fixed-point algorithm family
  TaeHo Yoon, Ernest Ryu, Benjamin Grimmer
• Performance Estimation framework for a range of stochastic first-order methods.
  Anne Rubbens, Julien Hendrickx

MD-09: Generalized convexity and monotonicity 3
Stream: Generalized convexity and monotonicity
Room: B100/8013
Chair(s): Felipe Lara

• On an alternative to convexity of the values in set-valued analysis: from theory to applications
  Annagiulia Pezzola, Didier Aussel, Rossana Riccardi, Domenico Scopelliti
• Fixed-time convergent second-order time-varying dynamical systems
  Lien Nguyen
• On finite termination of quasi-Newton methods on quadratic problems
  Aban Ansari-Önnestam, Anders Forsgren

MD-10: Interactions between optimization and machine learning
Stream: Zeroth and first-order optimization methods
Room: B100/8011
Chair(s): Cesare Molinari, Silvia Villa

• From learning to optimize to learning optimization algorithms
  Camille Castera, Peter Ochs
• The Surprising Agreement Between Convex Optimization Theory and Learning-Rate Scheduling for Large Model Training
  Fabian Schaipp, Alexander Hägele, Adrien Taylor, Umut Simsekli, Francis Bach
• Greedy learning to optimise with convergence guarantees
  Patrick Fahy, Mohammad Golbabaee, Matthias J. Ehrhardt
• Learning from data via overparameterization
  Cesare Molinari, Silvia Villa, Lorenzo Rosasco, Cristian Vega, Hippolyte Labarrière

MD-11: Applications of conic optimization
Stream: Conic Optimization
Room: B100/5017
Chair(s): Miguel Anjos

• The application of SDP-based relaxation for the nordic day-ahead energy market
  Shudian Zhao, Jan Kronqvist
• Aggregated Formulations and Relaxations of the Stable Set Polytope
  Haobang Zhou, Akshay Gupte, E. Alper Yildirim
• Hybrid scalarization for multi-objective semi definite polynomial optimization
  SUJEET KUMAR SINGH

MD-12: Applications of optimisation under uncertainty
Stream: Applications: AI, uncertainty management and sustainability
Room: B100/8009
Chair(s): Nicole Cristina Cassimiro de Oliveira

• Phase recovery from masked phaseless antenna measurements
  Sakirudeen Abdulsalaam, Adrien Guth, Holger Rauhut, Dirk Heberling
• Controlled stochastic processes for simulated annealing
  Vincent Molin, Axel Ringh
• Robust treatment planning in proton therapy
  Nicole Cristina Cassimiro de Oliveira, Aurelio Oliveira, Juliana Campos de Freitas

MD-13: Recent advances in optimization problems with cardinality constraints
Stream: Sparsity guarantee and cardinality-constrained (MI)NLPs
Room: B100/6009
Chair(s): Laura Palagi

• Critical Point Theory for Sparse Huber Recovery
  Deniz Akkaya, Mustafa Pinar
• Combinatorial, conic and linear bounds for expansions in a graph
  Akshay Gupte
• Margin Optimal Regression Trees
  Ilaria Ciocci, Marta Monaci, Laura Palagi

TA-01: Plenary 2
Stream: Plenaries
Room: B100/1001
Chair(s): Laura Palagi

• Bayesian optimization for mixed feature spaces using tree kernels and graph kernels
  Ruth Misener

TB-01: Zeroth-Order Optimization Methods for Stochastic and Noisy Problems
Stream: Zeroth and first-order optimization methods
Room: B100/1001
Chair(s): Francesco Rinaldi, Andrea Cristofari

• Unifying Trust-region Algorithms with Adaptive Sampling for Nonconvex Stochastic Optimization
  Sara Shashaani, Yunsoo Ha
• Direct Search Methods for Stochastic Zeroth-Order Problems
  Francesco Rinaldi, Andrea Cristofari
• Analysis of derivative-free algorithms on noisy problems
  Alexandre Chotard, Anne Auger
• Derivative-Free Constrained Optimization in Hydraulics: Augmented Lagrangian Method with BOBYQA
  Fabio Fortunato Filho, José Mario Martínez

TB-02: Infinite-dimensional optimization - Part I
Stream: Nonsmooth and nonconvex optimization
Room: B100/7011
Chair(s): Behzad Azmi

• Asymptotic behavior of penalty dynamics for constrained variational inequalities
  Siqi Qu, Mathias Staudigl, Juan Peypouquet
• Inertial dynamics with vanishing Tikhonov regularization for multiobjective optimization
  Konstantin Sonntag

TB-03: Theoretical and algorithmic advances in large scale nonlinear optimization and applications Part 1
Stream: Large scale optimization: methods and algorithms
Room: B100/4011
Chair(s): Stefania Bellavia, Benedetta Morini

• Fully stochastic trust-region methods with Barzilai-Borwein steplengths
  Benedetta Morini, Mahsa Yousefi, Stefania Bellavia
• prunAdag: an adaptive pruning-aware gradient method
  Giovanni Seraghiti, Margherita Porcelli, Philippe L. Toint
• An acceleration strategy for gradient methods in convex quadratic programming
  Gerardo Toraldo, Serena Crisci, Anna De Magistris, Valentina De Simone
• Corrective Frank-Wolfe: Unifying and Extending Correction Steps
  Jannis Halbey, Seta Rakotomandimby, Mathieu Besançon, Sebastian Pokutta

TB-04: Stochastic and Deterministic Global Optimization
Stream: Global optimization
Room: B100/5013
Chair(s): Dmitri Kvasov, Eligius M.T. Hendrix

• Global Optimization Algorithm through High-Resolution Sampling
  Daniel Cortild, Claire Delplancke, Nadia Oudjane, Juan Peypouquet
• ɛ-subdifferential methods for global DC optimization
  Adil Bagirov
• On global optimization of some nonlinear problems involving disjunctive constraints
  Sonia Cafieri, Marcel Mongeau, Sebastien Bourguignon, Gwenaël Samain
• Benchmarking tools for global optimization
  Dmitri Kvasov, Yaroslav Sergeyev

TB-05: Randomized Optimization algorithms I
Stream: Optimization for machine learning
Room: B100/4013
Chair(s): Laurent Condat

• Scalable Second-Order Optimization Algorithms for Minimizing Low-Rank Functions
  Edward Tansley, Coralia Cartis, Zhen Shao
• Distributed Optimization with Communication Compression
  Yuan Gao, Sebastian Stich
• Stochastic Gradient Descent without Variance Assumption: A Tight Lyapunov Analysis
  Lucas Ketels, Daniel Cortild, Guillaume Garrigos, Juan Peypouquet
• Communication-Efficient Algorithms for Federated Learning and Weakly Coupled Games
  Sebastian Stich, Ali Zindari, Parham Yazdkhasti, Anton Rodomanov, Tatjana Chavdarova

TB-06: Advances in nonsmooth optimization
Stream: Nonsmooth and nonconvex optimization
Room: B100/7013
Chair(s): Alireza Kabgani, Vladimir Shikhman

• Monotone and nonmonotone linearized block coordinate descent methods for nonsmooth composite optimization problems
  Yassine Nabou, Lahcen EL BOURKHISSI, Sebastian Stich, Tuomo Valkonen
• Global convergence of a second-order augmented Lagrangian method under an error bound condition
  Renan William Prado, Gabriel Haeser, Roberto Andreani, Maria Laura Schuverdt, Leonardo Delarmelina Secchin
• NON-EUCLIDEAN PROXIMAL METHODS FOR CONVEX-CONCAVE SADDLE-POINT PROBLEMS
  Eyal Cohen, Shoham Sabach, Marc Teboulle
• Stationarity in nonsmooth optimization between geometrical motivation and topological relevance
  Vladimir Shikhman

TB-07: Nonsmooth Bilevel Optimization
Stream: Bilevel and multilevel optimization
Room: B100/5015
Chair(s): Shangzhi Zeng

• A new problem qualification for Lipschitzian optimization problems
  Andreas Fischer, Isabella Käming, Alain Zemkoho
• Solving Bilevel Optimization Problems using Finite Elements and Reduced Order Methods
  Floriane Mefo Kue
• Nonsmooth Implicit Differentiation: Deterministic and Stochastic Convergence Rates
  Saverio Salzo
• Alternating Gradient-Type Algorithm for Bilevel Optimization with Inexact Lower-Level Solutions via Moreau Envelope-based Reformulation
  Shangzhi Zeng

TB-08: Systematic and computer-aided analyses IV: Online & distributed gradient methods
Stream: Systematic and computer-aided analyses of optimization algorithms
Room: B100/7007
Chair(s): Manu Upadhyaya, Baptiste Goujaud

• Constructive approach to worst-case analysis and algorithm design in online convex optimization
  Julien Weibel
• A Linear Parameter-Varying framework for the analysis of time-varying optimization algorithms.
  Fabian Jakob, Andrea Iannelli
• Computer-Aided Analysis of Decentralized Online Optimization Algorithms
  Erwan Meunier, Julien Hendrickx

TB-09: Variational Analysis I
Stream: Variational analysis: theory and algorithms
Room: B100/8013
Chair(s): Fernando García Castaño

• The Douglas-Rachford algorithm with variable stepsizes as a relocated fixed-point iteration
  Felipe Atenas, Heinz Bauschke, Minh N. Dao, Matthew Tam
• A Speed Restart Scheme for an Inertial System with Hessian-Driven Damping and Three Constant Coefficients
  Huiyuan Guo, Juan Jose Maulen, Juan Peypouquet
• Forward-backward algorithms devised by graphs
  Francisco Javier Aragón Artacho, Rubén Campoy, César López Pastor

TB-10: First order methods: new perspectives for machine learning
Stream: Large scale optimization: methods and algorithms
Room: B100/8011
Chair(s): Cesare Molinari, Silvia Villa, Lorenzo Rosasco

• Convergence Analysis of Nonlinear Parabolic PDE Models with Neural Network Terms Trained with Gradient Descent
  Konstantin Riedl, Justin Sirignano, Konstantinos Spiliopoulos
• Randomized trust-region method for non-convex mimimization
  Radu-Alexandru Dragomir
• Perspectives on the analysis and design of optimization algorithms: Lyapunov analyses and counter-examples
  Adrien Taylor
• Accelerated Gradient Methods via Inertial Systems with Hessian-driven Damping
  Juan Peypouquet

TB-11: Advances in Manifold Optimization
Stream: Riemannian Manifold and Conic Optimization
Room: B100/5017
Chair(s): Yukuan Hu

• Infeasible Optimization on Manifolds: the Landing Approach
  P.-A. Absil
• The Distributionally Robust Optimization Model of Sparse Principal Component Analysis
  Xin Liu
• A Unified Constrained Saddle Dynamics for Index-1 Saddle Point Search on Riemannian Submanifolds
  Yukuan Hu
• Exploring Energy Landscapes: Stochastic Methods for Index‑1 Saddle Points on Riemannian Submanifolds
  Panos Parpas

TB-12: Optimisation under uncertainty in the power sector
Stream: Applications: AI, uncertainty management and sustainability
Room: B100/8009
Chair(s): Hongyu Zhang

• Hybrid residential systems with battery storage: multi-objective optimization of self-sufficiency and economic viability
  Paulo Rotella Junior, Arthur Leandro Guerra Pires, Rafael Miranda, Luiz Celio Souza Rocha, Karel Janda
• Renewable Energy Communities with Peer-to-Peer Exchange: a chance-constraint approach
  Santo Saraceno, Elisabetta Allevi, Giorgia Oggioni, Rossana Riccardi, Abdel Lisser
• Data-driven dynamic scenario generation using Benders decomposition with adaptive oracles
  Hongyu Zhang, Ken McKinnon , Andrew Reeves

TB-13: Numerical Methods and Applications I
Stream: Numerical Methods and Applications
Room: B100/6009
Chair(s): Stefan Schwarze

• The improvement function in branch-and-bound methods
  Stefan Schwarze, Oliver Stein, Peter Kirst, Marc Rodestock
• LP relaxations for the elementary shortest path problem
  Regina Schmidt, Mirjam Duer
• Convergence Analysis of Modified Cubic-Regularized Newton Method
  Vladislav Ryspayev
• On the Spectral Projected Gradient Method for the Molecular Distance Geometry Problem
  Mariana da Rosa

TC-01: First-Order Methods for Structured Optimization and Sampling
Stream: Zeroth and first-order optimization methods
Room: B100/1001
Chair(s): Cesare Molinari, Silvia Villa

• Constrained sampling with Primal-Dual Langevin Monte Carlo
  Luiz Chamon
• A Fast Extra-Gradient Method with Flexible Anchoring
  Enis Chenchene, Radu Ioan Bot
• Risk-averse guarantees for stochastic min-max problems
  Yassine Laguel, Mert Gürbüzbalaban, Necdet Serhat Aybat, Yasa Syed

TC-02: Infinite-dimensional optimization - Part II
Stream: Nonsmooth and nonconvex optimization
Room: B100/7011
Chair(s): Behzad Azmi

• A Fast Iterative Method for Variational Inequality and Classification Problems
  Lateef Jolaoso
• An Interior-Proximal Point Method for Nonsmooth, Nonconvex PDE-Constrained Problems with State Constraints
  Behzad Azmi, Alberto De Marchi

TC-03: Theoretical and algorithmic advances in large scale nonlinear optimization and applications Part 2
Stream: Large scale optimization: methods and algorithms
Room: B100/4011
Chair(s): Stefania Bellavia, Benedetta Morini

• Advanced Techniques for Portfolio Optimization Under Uncertainty
  Valentina De Simone
• Inexact derivative-free methods for constrained bilevel optimization with applications to machine learning
  Marco Viola, Matteo Pernini, Gabriele Sanguin, Francesco Rinaldi
• Three Alternating Projection Methods for Matrix Completion
  Mattia Silei, Stefania Bellavia, Simone Rebegoldi
• Bi- and Multi-Level Optimization Strategies for Sparse and Interpretable Learning in NMF
  Laura Selicato

TC-04: Global Optimization advances
Stream: Global optimization
Room: B100/5013
Chair(s): Eligius M.T. Hendrix, Sonia Cafieri

• On polytopal branch and bound
  Eligius M.T. Hendrix, Boglárka G.-Tóth, Leocadio G. Casado, Frédéric MESSINE
• A branch-and-bound algorithm for nonconvex Nash equilibrium problems
  Peter Kirst, Stefan Schwarze, Oliver Stein
• Global and Robust Optimisation for Non-Convex Quadratically Constrained Quadratic Programs
  Asimina Marousi, Vassilis Charitopoulos

TC-05: Randomized Optimization algorithms II
Stream: Optimization for machine learning
Room: B100/4013
Chair(s): Laurent Condat

• Derivative-free stochastic bilevel optimization for inverse problems
  Mathias Staudigl, Simon Weissmann, Tristan van Leeuwen
• Proximal splitting algorithms in nonlinear spaces
  Russell Luke
• SPAM: Stochastic Proximal Point Method with Momentum Variance Reduction for Non-convex Cross-Device Federated Learning
  Avetik Karagulyan
• A Stochastic Newton-type Method for Non-smooth Optimization
  Titus Pinta

TC-06: Structured nonsmooth optimization -- Part I
Stream: Nonsmooth and nonconvex optimization
Room: B100/7013
Chair(s): Karl Welzel

• Equivalence between Linear Convergence and Error Bounds for Optimization Algorithms
  Kira van Treek, Javier Peña, Juan Vera, Luis Zuluaga
• Blockwise DC Programming
  Hoomaan Maskan, Pouria Fatemi, Alp Yurtsever, Suvrit Sra
• Presolve techniques for quasi-convex chance constraints with finite-support low-dimensional uncertainty
  Guillaume Van Dessel, François Glineur
• Local convergence of adaptively regularized tensor methods
  Karl Welzel, Coralia Cartis, Raphael Hauser, Yang Liu

TC-07: Mixed-Integer Bilevel Optimization
Stream: Bilevel and multilevel optimization
Room: B100/5015
Chair(s): Abdellah Bulaich Mehamdi

• A Bilevel Critical Node Detection Problem
  Ashwin Arulselvan
• On a class of interdiction problems with partition matroids: complexity and polynomial-time algorithms
  Sergei Ketkov
• Bi-Level Optimization for Electricity Pricing: Links with the Rochet-Choné Model
  Abdellah Bulaich Mehamdi, Wim van Ackooij, Luce Brotcorne, Stephane Gaubert, Quentin Jacquet

TC-08: Systematic and computer-aided analyses V: Tools for systematic studies of first-order algorithms
Stream: Systematic and computer-aided analyses of optimization algorithms
Room: B100/7007
Chair(s): Manu Upadhyaya, Adrien Taylor

• Data-driven Analysis of First-order Methods via Distributionally Robust Optimization
  Jisun Park, Vinit Ranjan, Bartolomeo Stellato
• Computer-aided analysis of relatively inexact gradient descent in smooth convex optimization
  Pierre Vernimmen, François Glineur
• AutoLyap: A Python package for computer-assisted Lyapunov analyses for first-order methods
  Manu Upadhyaya, Adrien Taylor, Sebastian Banert, Pontus Giselsson

TC-09: Variational Analysis II
Stream: Variational analysis: theory and algorithms
Room: B100/8013
Chair(s): Miguel Angel Melguizo Padial

• Bilevel variational inequalities and its applications
  Aviv Gibali
• On the variational inequality approach to Network Games
  Fabio Raciti
• Inexactness in Variational Problems
  Lorenzo Lampariello, Giancarlo Bigi, Simone Sagratella, Valerio Giuseppe Sasso
• Henig Proper Efficient Points: Existence and Density Beyond Convexity
  Fernando García Castaño, Miguel Angel Melguizo Padial

TC-10: Continuous Multi-Objective Optimization: Algorithms and Complexity Analyses
Stream: Multiobjective and Vector Optimization
Room: B100/8011
Chair(s): Pierluigi Mansueto

• On the convergence of outer approximation algorithms for convex vector optimization problems
  Firdevs Ulus, Cagin Ararat, Muhammad Umer
• Effective Front-Descent Algorithms with Convergence Guarantees
  Matteo Lapucci, Pierluigi Mansueto, Davide Pucci
• Worst-case complexity analysis of a-posteriori methods for multi-objective optimization
  Giampaolo Liuzzi, Andrea Cristofari, Marianna De Santis, Stefano Lucidi
• Worst-case Complexity in Continuous Multi-Objective Optimization
  Rohollah Garmanjani

TC-11: Advances in Manifold and Conic Optimization
Stream: Riemannian Manifold and Conic Optimization
Room: B100/5017
Chair(s): Panos Parpas

• Conjectures in Real Algebra and Polynomial Optimization through High Precision Semidefinite Programming
  Michal Kocvara, Lorenzo Baldi
• Riemannian Optimization on Nonnegative Matrix Factorizations: chordal, oblique and more
  Man Shun Andersen Ang, Flavia Esposito
• Second-order differential operators, stochastic differential equations and Brownian motions on embedded manifolds
  DU NGUYEN, Stefan Sommer
• Faster Randomized Methods for Orthogonality Constrained Problems
  Boris Shustin, Haim Avron

TC-12: Optimization for sustainable energy systems
Stream: Applications: AI, uncertainty management and sustainability
Room: B100/8009
Chair(s): Miguel Anjos

• Optimal management of electric vehicle fleets: An optimistic bilevel optimization model
  Eleni Michaelidou, Miguel Anjos
• A Stochastic Optimization Model for the Water Pump Scheduling Problem with Demand Response in Large and High Altitude Water Supply Systems
  Miguel Anjos
• A stochastic programming model for planning CO2 transport infrastructure
  Lihan Zhang

TD-01: Plenary 3 (EUROPT Lecture)
Stream: Plenaries
Room: B100/1001
Chair(s): Giancarlo Bigi, Immanuel Bomze

• Contextual Stochastic Bilevel Optimization
  Daniel Kuhn

WA-01: Plenary 4
Stream: Plenaries
Room: B100/1001
Chair(s): Alain Zemkoho

• Non-Smooth Optimization on Stiefel Manifold and Beyond
  Anthony So

WB-01: Advances in stochastic and non-euclidean first order methods
Stream: Zeroth and first-order optimization methods
Room: B100/1001
Chair(s): Cesare Molinari, Silvia Villa

• Non-monotone stochastic line search without overhead for training neural networks
  Andrea Cristofari, Leonardo Galli, Stefano Lucidi
• On the convergence of stochastic Bregman proximal gradient algorithms with biased gradient estimators
  Thomas Guilmeau, Emilie Chouzenoux, Víctor Elvira
• Riemannian gradient descent improves parameter-efficient fine-tuning
  Bingcong Li
• General Tail Bounds for Non-Smooth Stochastic Mirror Descent
  Andrea Paudice, Khaled Eldowa

WB-02: High-order and tensor methods
Stream: Nonsmooth and nonconvex optimization
Room: B100/7011
Chair(s): Wenqi Zhu

• Efficient Adaptive Regularized Tensor Methods
  Yang Liu, Karl Welzel, Coralia Cartis, Raphael Hauser, Wenqi Zhu
• A low-rank augmented Lagrangian method for doubly nonnegative relaxations of mixed-binary quadratic programs
  Tianyun Tang
• On Global Rates for Regularization Methods Based on Secant Derivative Approximations
  Sadok Jerad, Coralia Cartis
• Beyond Second Order Methods for Nonconvex Optimization
  Wenqi Zhu

WB-03: Recent Advances in Line-Search Based Optimization
Stream: Large scale optimization: methods and algorithms
Room: B100/4011
Chair(s): Matteo Lapucci

• Line Search Methods are Sharpness-Aware and Operate at the Edge of Stability
  Leonardo Galli
• A Gradient Method with Momentum for Riemannian Manifolds
  Diego Scuppa, Filippo Leggio, Marco Sciandrone
• A Variable Dimension Sketching Strategy for Nonlinear Least-Squares
  Greta Malaspina, Stefania Bellavia, Benedetta Morini
• Stochastic line-search-based optimization for training overparameterized models: convergence conditions and effective approaches to leverage momentum
  Davide Pucci, Matteo Lapucci

WB-04: Optimization and learning for estimation problems
Stream: Optimization for machine learning
Room: B100/5013
Chair(s): Laurent Condat

• Multilevel Plug-and-Play Image Restoration
  Nils Laurent, Julian Tachella, Elisa Riccietti, Nelly Pustelnik
• Anomaly Detection Using the Cloud of Spheres Classification Method
  Paula Amaral, Tiago Dias
• Learning Proximal Neural Networks at Equilibrium Without Jacobian
  Leo Davy, Nelly Pustelnik, Luis Briceño-Arias
• Resource-Constrained Plug-and-Play Imaging: a block proximal heavy ball approach
  Andrea Sebastiani, Federica Porta, Simone Rebegoldi

WB-05: Recent advances in min-max optimization
Stream: Optimization for machine learning
Room: B100/4013
Chair(s): Ali Kavis, Aryan Mokhtari

• Steering Towards Success: Efficient Methods for Nonconvex-Nonconcave Minimax Problems
  Pontus Giselsson, Anton Åkerman, Max Nilsson, Manu Upadhyaya, Sebastian Banert
• A Universally Optimal Primal-Dual Method for Minimizing Heterogeneous Compositions
  Benjamin Grimmer
• Parameter-free second-order methods for min-max optimization
  Ali Kavis, Ruichen Jiang, Qiujiang Jin, Sujay Sanghavi, Aryan Mokhtari

WB-06: Structured nonsmooth optimization -- Part II
Stream: Nonsmooth and nonconvex optimization
Room: B100/7013
Chair(s): Behzad Azmi

• Douglas-Rachford splitting algorithm for projected solution of quasi variational inequality with non-self constraint map
  Maede Ramazannejad
• On the relation between approximate and exact stationarity in disjunctive optimization
  Isabella Käming, Patrick Mehlitz
• Constrained Optimization in the Presence of Noise
  Figen Oztoprak
• A sharp augmented Lagrangian-based method for solving constrained DC optimization
  Sona Taheri

WB-07: Theory and methods for bilevel optimization
Stream: Bilevel and multilevel optimization
Room: B100/5015
Chair(s): Kuang Bai

• Stability analysis for two-level value functions and application to numerically solve a pessimistic bilevel program
  Alain Zemkoho
• Bilevel programming via set-valued optimization
  Kuntal Som
• Lifting and Penalisation approach for Mathematical Program with Vanishing Constraints
  Anand Kumar, K. S. Mallikarjuna Rao
• Directional combined approach for bilevel programs
  Kuang Bai

WB-08: Theoretical advances in nonconvex optimization
Stream: Large scale optimization: methods and algorithms
Room: B100/7007
Chair(s): Annette Dumas, Clément Royer

• Continuized Nesterov Acceleration to improve convergence speed in non convex optimization
  Julien Hermant, Jean-François Aujol, Charles Dossal, Aude Rondepierre
• Complexity of Newton-type methods with quadratic regularization for nonlinear least squares
  Iskander LEGHERABA, Clément Royer
• Cubic regularized Newton methods with stochastic Hessian evaluations and momentum-based variance reduction
  Yiming Yang
• Algorithms for nonconvex optimization on measure spaces.
  Annette Dumas, Clément Royer

WB-09: Variational Analysis III
Stream: Variational analysis: theory and algorithms
Room: B100/8013
Chair(s): Francisco Javier Aragón Artacho

• Geometry and the complexity of first-order methods for Lipschitz optimization
  Adrian Lewis
• Inner approximations of convex sets and intersections of projectionally exposed cones
  Vera Roshchina
• Nonlinear Separation of Coradiant Sets: Optimality Conditions for Approximate Solutions
  Miguel Angel Melguizo Padial, Fernando García Castaño
• Nonsmooth optimization techniques for computing projected quasi-equilibria
  Giancarlo Bigi

WB-10: Global Multi-Objective Optimization
Stream: Multiobjective and Vector Optimization
Room: B100/8011
Chair(s): Pierluigi Mansueto

• An unconstrained method for nonconvex Pareto front approximation
  Ina Lammel, Karl-Heinz Küfer
• Local Upper Bounds for General Ordering Cones
  Gabriele Eichfelder, Firdevs Ulus
• Multi-Objective branch-and-bound algorithms for binary (non-convex) quadratic problems
  Yue Zhang, Marianna De Santis, Pierre Fouilhoux, Lucas Létocart

WB-11: Interior point methods and applications - Part I
Stream: Interior point methods and applications
Room: B100/5017
Chair(s): Jordi Castro

• Proximal Augmented Lagrangian Regularization: A Primal-Dual Modular Interior-Point QP Solver.
  Jeremy Bertoncini, Alberto De Marchi, Matthias Gerdts
• Polynomial worst-case complexity for quasi-Newton Interior Point Methods
  Francisco Sobral, Jacek Gondzio
• Proximal Stabilized Interior Point Methods and Applications
  Stefano Cipolla, Fabio Durastante, Jacek Gondzio, Beatrice Meini, Filippo Zanetti
• Comparison of Interior-point and active set quadratic programming for regularised column generation
  Wim Vanroose, Sebastian Van Thienen

WB-12: Chemical and Energy Systems Optimization
Stream: Applications: AI, uncertainty management and sustainability
Room: B100/8009
Chair(s): Gabriel Patron, Lavinia Ghilardi

• Complementarity-based modelling for sustainable dynamic gas network operation
  Lavinia Ghilardi
• Risk-constrained two-stage demand response scheduling for green hydrogen production
  Gabriel Patron
• Distillation column optimization: A formal method using stage-to stage computations and distributed streams
  Tobias Seidel

WC-01: Advances in Multiobjective and Bilevel Optimization without Derivatives
Stream: Zeroth and first-order optimization methods
Room: B100/1001
Chair(s): Francesco Rinaldi, Andrea Cristofari

• A Direct Multisearch Approach (DMS) for Many-Objective Derivative-Free Optimization
  Everton Silva, Ana Luisa Custodio
• Exploring Polynomial Models in the Search Step of Direct Multisearch
  Marta Pozzi, Everton Silva, Ana Luisa Custodio
• Derivative-Free Bilevel Optimization with Inexact Lower-Level Solutions
  Edoardo Cesaroni, Giampaolo Liuzzi, Stefano Lucidi

WC-02: Systematic and computer-aided analyses VI: Systematic approaches to the analyses of proximal and higher-order methods
Stream: Systematic and computer-aided analyses of optimization algorithms
Room: B100/7011
Chair(s): Manu Upadhyaya, Baptiste Goujaud

• SDP performance estimation for the boosted DCA
  Etienne De Klerk, Hadi Abbaszadehpeivasti
• A unified Lyapunov analysis for first and second order methods attached to bilevel optimization
  David Alexander Hulett, Radu Ioan Bot, Enis Chenchene, Robert Csetnek
• Designing Monotone Operator Splitting Algorithms with Steering Vectors
  Max Nilsson, Sebastian Banert, Pontus Giselsson

WC-03: Acceleration Methods in Optimization
Stream: Large scale optimization: methods and algorithms
Room: B100/4011
Chair(s): Vuong Phan, yingxin zhou

• Anderson acceleration with adaptive relaxation for convergent fixed-point iterations
  Nicolas Lepage-Saucier
• Anderson Acceleration for Primal-Dual Hybrid Gradient
  yingxin zhou, Stefano Cipolla, Vuong Phan
• Accelerating Convergence of MPGP Algorithm
  Jakub Kruzik, David Horak

WC-04: Large Scale Optimization for Statistical Learning
Stream: Optimization for machine learning
Room: B100/5013
Chair(s): Selin Ahipasaoglu

• Spatial branch-and-bound methods for solving the k-Hyperplane clustering
  Stefano Coniglio, Montree Jaidee
• Solving the Optimal Experiment Design with Mixed-Integer Convex Methods
  Deborah Hendrych, Mathieu Besançon, Sebastian Pokutta
• A column generation approach to exact experimental design
  Selin Ahipasaoglu, Stefano Cipolla, Jacek Gondzio

WC-05: Recent Advances in Stochastic Optimization
Stream: Optimization for machine learning
Room: B100/4013
Chair(s): Chuan He

• Almost sure convergence rates for stochastic gradient methods
  Simon Weissmann
• A Hessian-Aware Stochastic Differential Equation for Modelling SGD
  Xiang Li
• Complexity guarantees for risk-neutral generalized Nash equilibrium problems
  Meggie Marschner, Mathias Staudigl
• Stochastic first-order methods can leverage arbitrarily higher-order smoothness for acceleration
  Chuan He

WC-06: Structured nonsmooth optimization -- Part III
Stream: Nonsmooth and nonconvex optimization
Room: B100/7013
Chair(s): Bastien Massion, Alireza Kabgani

• Linear Convergence Rate in Convex Setup is Possible! Gradient Descent Method Variants under (L0,L1)-Smoothness
  Aleksandr Lobanov
• Primal-Dual Coordinate Descent for Nonconvex-Nonconcave Saddle Point Problems Under the Weak MVI Assumption
  Iyad WALWIL, Olivier Fercoq
• A full splitting algorithm for structured difference-of-convex programs
  Rossen Nenov
• An accelerated projected gradient descent for Grassmannian frame computation
  Bastien Massion, Estelle Massart

WC-07: Numerical Methods and Applications II
Stream: Numerical Methods and Applications
Room: B100/5015
Chair(s): Brendan Ames

• Extensions of Consensus-Based Methods
  Sara Veneruso, Michael Herty, Lorenzo Pareschi
• A Hybrid Conjugate Gradient-Like Algorithm for Solving Nonlinear Equations and Image Restoration
  Supak Phiangsungnoen
• Finding a planted clique hidden among many dense subgraphs
  Brendan Ames

WC-08: Advances in non-convex optimization
Stream: Optimization for machine learning
Room: B100/7007
Chair(s): Radu-Alexandru Dragomir

• Benign landscapes for synchronization on spheres via normalized Laplacian matrices
  Andrew McRae
• Diagonal linear networks and the regularization path of the LASSO
  Raphael Berthier
• Long-time convergence of a consensus-based optimization method
  Victor Priser, Pascal Bianchi, Radu-Alexandru Dragomir
• Simplicity Bias of Two-Layer Networks beyond Linearly Separable Data
  Nikola Konstantinov

WC-09: Generalized convexity and monotonicity 4
Stream: Generalized convexity and monotonicity
Room: B100/8013
Chair(s): Minh N. Dao

• Capra-Cutting Plane Method Applied to Sparse Optimization
  Seta Rakotomandimby, Adrien Le Franc, Jean-Philippe Chancelier, Michel De Lara
• Evaluation of Multi-agent algorithms in Multi-objective Environments with Weighted Sum Method
  Carlos Ignacio Hernández Castellanos, José Olivas Díaz
• Linear Convergence of the Proximal Point Algorithm Beyond Convexity
  Felipe Lara

WC-10: Computational Aspects in Multiobjective Optimization
Stream: Multiobjective and Vector Optimization
Room: B100/8011
Chair(s): Felix Neussel

• Stochastic approximation in convex multiobjective optimization
  Elena Molho, Carlo Alberto De Bernardi, Enrico Miglierina, Jacopo Somaglia
• Benchmarking Nonlinear Multi-Objective Optimizers in Julia
  Manuel Berkemeier
• Parametrized convex MINLP: Warm-starting with Outer Approximation for Sequence of MINLPs
  Erik Tamm, Gabriele Eichfelder, Jan Kronqvist
• On image space transformations in multiobjective optimization
  Felix Neussel, Oliver Stein

WC-11: Interior point methods and applications - Part II
Stream: Interior point methods and applications
Room: B100/5017
Chair(s): Stefano Cipolla

• A tailored, matrix free interior point method for fast optimization on gas networks
  Rowan Turner, Lars Schewe, John Pearson
• An interior point approach for multi horizon risk averse stochastic optimization.
  Jordi Castro, Laureano F. Escudero, Juan Francisco Monge
• A higher-order extrapolation interior-point method for nonlinear optimization
  Pim Heeman, Anders Forsgren
• Low-Rank Semidefinite Programming for Symmetric Tensor Decomposition: An Experimental Study
  Yassine Koubaa

WC-12: Optimisation under uncertainty for sustainability
Stream: Applications: AI, uncertainty management and sustainability
Room: B100/8009
Chair(s): Parisa Ahani

• Optimization of Dynamic Service Systems with Adaptive Resource Allocation and Pricing Strategies Based on Random Environments and Customer Feedback
  CHESOONG KIM
• Efficient Design of Water Distribution Networks: An Approximation and a Heuristic
  Nitish Dumoliya, Ashutosh Mahajan
• Optimizing decision-making framework under uncertainty for fleet replacement problem
  Parisa Ahani, Maria Isabel Gomes

WD-01: Closing
Stream: Plenaries
Room: B100/1001
Chair(s): Alain Zemkoho, Giancarlo Bigi, Selin Ahipasaoglu