One World Optimization Seminar in Vienna
The main aim of the ESI workshop is to gather speakers of the One World Optimization Seminar (https://owos.univie.ac.at/) at one place to discuss recent advances in continuous optimization. One World Optimization Seminar (OWOS) was a series of online seminars in optimization run from April 2020 until April 2022. Amidst the challenges of the pandemic, OWOS stood out as an exceptional event that played a crucial role in keeping the optimization community together, providing valuable insights and fostering collaboration among attendees.
The objectives of this workshop encompass three key topics: (i) variational and nonsmooth analysis, (ii) optimization algorithms, and (iii) applications of these methodologies in various fields.
June 3, 2024
June 4, 2024
June 5, 2024
June 6, 2024
June 7, 2024
09:00 — 09:30
Registration & Welcome
09:30 — 10:00
Terry Ralph Rockafellar (U of Washington, Seattle)
Progressive Decoupling of Dynamics in Convex Optimal Control
Progressive Decoupling of Dynamics in Convex Optimal Control
10:00 — 10:30
Ewa Bednarczuk (Polish Academy of Science, Warsaw)
Constraint qualification and the existence of multipliers for nonconvex infinite-constrained optimization problems in Banach spaces
Constraint qualification and the existence of multipliers for nonconvex infinite-constrained optimization problems in Banach spaces
10:30 — 11:00
Coffee Break
11:00 — 11:30
Jong-Shi Pang (U of Southern California, Los Angeles)
Heaviside composite optimization and complementarity constraints by a progressive integer programming method
Heaviside composite optimization and complementarity constraints by a progressive integer programming method
11:30 — 12:00
Panayotis Mertikopoulos (CNRS, Grenoble)
The Long-Run Distribution of Stochastic Gradient Descent: A Large Deviations Analysis
The Long-Run Distribution of Stochastic Gradient Descent: A Large Deviations Analysis
12:00 — 14:00
Lunch Break
14:00 — 14:30
Roberto Cominetti (U Adolfo Ibanez, Santiago de Chile)
Error bounds for mean-payoff Markov decision processes
Error bounds for mean-payoff Markov decision processes
14:30 — 15:00
Alp Yurtsever (Umeå U)
CCCP is Frank-Wolfe in disguise
CCCP is Frank-Wolfe in disguise
15:00 — 15:30
Coffee Break
15:30 — 16:00
16:00 — 16:30
Ya-Ping Hsieh (ETH Zurich)
How to Optimize a Schrödinger Bridge?
How to Optimize a Schrödinger Bridge?
16:30 — 17:00
Mert Gürbüzbalaban (Rutgers U)
High probability and risk-averse guarantees for stochastic saddle point problems
High probability and risk-averse guarantees for stochastic saddle point problems
17:30 — 21:00
Welcome Reception
09:00 — 09:30
Marc Teboulle (Tel Aviv U)
Proximal Gradient Methods for Nonsmooth Nonconvex Minimax: A Unified Convergence Analysis
Proximal Gradient Methods for Nonsmooth Nonconvex Minimax: A Unified Convergence Analysis
09:30 — 10:00
Russell Luke (U Göttingen)
Nonconvex Optimization and the Curse of Local Minima: Lessons Learned from Orbital Tomography
Nonconvex Optimization and the Curse of Local Minima: Lessons Learned from Orbital Tomography
10:00 — 10:30
Jalal Fadili (CNRS-ENSICAEN, U of Caen)
Iterative Regularization of the Deep Inverse Prior via (Inertial) Gradient Flow
Iterative Regularization of the Deep Inverse Prior via (Inertial) Gradient Flow
10:30 — 11:00
Coffee Break
11:00 — 11:30
Ya-xiang Yuan (Chinese Academy of Sciences, Beijing)
A new derivative-free method using an improved under-determined quadratic interpolation model
A new derivative-free method using an improved under-determined quadratic interpolation model
11:30 — 12:00
Frank Curtis (Lehigh U, Bethlehem)
Stochastic Algorithms for Constrained Continuous Optimization
Stochastic Algorithms for Constrained Continuous Optimization
12:00 — 14:00
Lunch Break
14:00 — 14:30
Michael Hintermüller (WIAS, Berlin)
Quasi-Variational Inequalities: Semismooth Newton Methods, Optimal Control, and Uncertainties
Quasi-Variational Inequalities: Semismooth Newton Methods, Optimal Control, and Uncertainties
14:30 — 15:00
Michael Ulbrich (TU Munich)
Sample Size Estimates for Risk-Neutral Semilinear PDE-Constrained Optimization
Sample Size Estimates for Risk-Neutral Semilinear PDE-Constrained Optimization
15:00 — 15:30
Coffee Break
15:30 — 16:00
09:00 — 09:30
Tom Luo (CUHK Shenzhen)
Finite Horizon Optimization
Finite Horizon Optimization
09:30 — 10:00
Edouard Pauwels (TSE, Toulouse)
Inexact subgradient algorithm with errors for semialgebraic functions
Inexact subgradient algorithm with errors for semialgebraic functions
10:00 — 10:30
Niao He (ETH Zurich)
A Hessian-Aware Stochastic Differential Equation Modelling of SGD
A Hessian-Aware Stochastic Differential Equation Modelling of SGD
10:30 — 11:00
Coffee Break
11:00 — 11:30
Shoham Sabach (Technion Haifa)
Bilevel Optimization Problems: Algorithms and Theory
Bilevel Optimization Problems: Algorithms and Theory
11:30 — 12:00
Adriana Nicolae (Babes-Bolyai U, Cluj-Napoca)
Weighted means in geodesic metric spaces
Weighted means in geodesic metric spaces
12:00 — 14:00
Lunch Break
14:00 — 14:30
Stephen Wright (U of Wisconsin-Madison)
Revisiting Inexact Fixed-Point Iterations for Min-Max Problems: Stochasticity and Structured Nonconvexity
Revisiting Inexact Fixed-Point Iterations for Min-Max Problems: Stochasticity and Structured Nonconvexity
14:30 — 15:00
Benjamin Grimmer (Johns Hopkins U, Baltimore)
Some Better Theory for Gradient Descent
Some Better Theory for Gradient Descent
15:00 — 15:30
Coffee Break
15:30 — 16:00
Anthony Man-Cho So (CU Hong Kong)
Spurious Stationarity and Hardness Results for Bregman-Type Algorithms
Spurious Stationarity and Hardness Results for Bregman-Type Algorithms
16:00 — 16:30
Pontus Giselsson (Lund U)
Automated tight Lyapunov analysis for first-order methods
Automated tight Lyapunov analysis for first-order methods
18:00 — 22:00
Workshop Dinner - Heuriger Schübel-Auer
09:00 — 09:30
Osman Güler (U of Maryland)
On the Kantorovich theory of Newton's method
On the Kantorovich theory of Newton's method
09:30 — 10:00
Coralia Carțiș (U Oxford)
Optimization of functions with low effective dimensionality
Optimization of functions with low effective dimensionality
10:00 — 10:30
10:30 — 11:00
Coffee Break
11:00 — 11:30
Peter Richtarik (KAUST, Thuwal)
The First Optimal Distributed SGD in the Presence of Data, Compute and Communication Heterogeneity
The First Optimal Distributed SGD in the Presence of Data, Compute and Communication Heterogeneity
11:30 — 12:00
Mustafa Pinar (Bilkent U, Ankara)
Sparsity Regularized Mean-Variance Portfolio Optimization
Sparsity Regularized Mean-Variance Portfolio Optimization
12:00 — 14:00
Lunch Break
14:00 — 14:30
Amir Beck (Tel Aviv U)
Exact Lipschitz Regularization of Convex Optimization Problems
Exact Lipschitz Regularization of Convex Optimization Problems
14:30 — 15:00
Szilard Csaba Laszlo (U Cluj-Napoca)
On strong convergence of inertial algorithms via Tikhonov regularization
On strong convergence of inertial algorithms via Tikhonov regularization
15:00 — 15:30
Coffee Break
15:30 — 16:00
Patrick Combettes (NC State U, Raleigh)
The geometry of monotone operator splitting
The geometry of monotone operator splitting
16:00 — 16:30
Mathias Staudigl (U of Mannheim)
A conditional gradient homotopy method with applications to Semidefinite Programming
A conditional gradient homotopy method with applications to Semidefinite Programming
09:00 — 09:30
Boris Mordukhovich (Wayne State U, Detroit)
Semi-Newton Method in Difference Programming
Semi-Newton Method in Difference Programming
09:30 — 10:00
Ernest Ryu (Seoul National U)
Toward a grand unified theory of accelerations in optimization and machine learning
Toward a grand unified theory of accelerations in optimization and machine learning
10:00 — 10:30
Ting Kei Pong (PolyU, Hong Kong)
Kurdyka-Łojasiewicz exponent for a class of Hadamard-difference-parameterized models
Kurdyka-Łojasiewicz exponent for a class of Hadamard-difference-parameterized models
10:30 — 11:00
Coffee Break
11:00 — 11:30
Wotao Yin (Alibaba Group, Bellevue)
Sum-of-Minimum Model: Joint Optimization of Specialized Models for Heterogeneous Data
Sum-of-Minimum Model: Joint Optimization of Specialized Models for Heterogeneous Data
11:30 — 12:00
Ion Necoara (U Politehnica Bucharest)
Coordinate descent methods beyond separability and smoothness
Coordinate descent methods beyond separability and smoothness
12:00 — 14:00
Lunch Break
14:00 — 14:30
Jonathan Eckstein (Rutgers U)
"DEFBAL" -- a Connection between the ADMM and Forward-Backward methods
"DEFBAL" -- a Connection between the ADMM and Forward-Backward methods
14:30 — 15:00
Pierre-Cyril Aubin-Frankowksi (TU Wien)
Alternating minimization and gradient descent with c(x,y) cost
Alternating minimization and gradient descent with c(x,y) cost
15:00 — 15:30
Coffee Break
15:30 — 16:00
Sorin-Mihai Grad (ENSTA Paris)
A fresh look at algorithms for solving smooth multiobjective optimization problems
A fresh look at algorithms for solving smooth multiobjective optimization problems
16:00 — 16:30
Masoud Ahookhosh (U Antwerpen)
High-order Moreau envelope in the nonconvex setting: Framework and algorithms
High-order Moreau envelope in the nonconvex setting: Framework and algorithms
Organizers
| Name | Affiliation |
|---|---|
| Radu Ioan Bot | University of Vienna |
| Yurii Malitskyi | University of Vienna |
Attendees
| Name | Affiliation |
|---|---|
| Masoud Ahookhosh | University of Antwerpen |
| Pierre-Cyril Aubin-Frankowksi | TU Wien |
| Behzad Azmi | Universität Konstanz |
| Amir Beck | Tel Aviv University |
| Ewa Bednarczuk | Polish Academy of Sciences |
| Matúš Benko | Johannes Kepler Universität |
| Immanuel Bomze | University of Vienna |
| Coralia Carțiș | University of Oxford |
| Enis Chenchene | University of Vienna |
| Patrick Combettes | North Carolina State University |
| Roberto Cominetti | University Adolfo Ibanez |
| Robert Csetnek | University of Vienna |
| Frank Curtis | Lehigh University |
| Daniel De Vicente | University of Vienna |
| Jonathan Eckstein | Rutgers University |
| Jalal Fadili | CNRS-ENSICAEN-Université Caen |
| Markus Gabl | University of Vienna |
| Pontus Giselsson | Lund University |
| Sorin-Mihai Grad | École nationale supérieure de techniques avancées |
| Benjamin Grimmer | Johns Hopkins University |
| Osman Güler | University of Maryland |
| Mert Gürbüzbalaban | Rutgers University |
| Niao He | ETH Zurich |
| Michael Hintermüller | Weierstrass Institute Berlin |
| Ya-Ping Hsieh | ETH Zurich |
| David Alexander Hulett | University of Vienna |
| Mikhail Karapetyants | University of Vienna |
| Szilard Csaba Laszlo | University Cluj-Napoca |
| Guoyin Li | University of New South Wales, Sydney |
| Russell Luke | University of Göttingen |
| Tom Luo | Chinese University of Hong Kong, Shenzhen |
| Panayotis Mertikopoulos | French National Centre for Scientific Research |
| Boris Mordukhovich | Wayne State University |
| Ion Necoara | University Politehnica Bucharest |
| Rossen Nenov | Acoustics Research Institute |
| Adriana Nicolae | Babes-Bolyai University |
| Jong-Shi Pang | University of Southern California |
| Edouard Pauwels | Toulouse School of Economics |
| Bo Peng | University of Vienna |
| Mustafa Pinar | Bilkent University |
| Ting Kei Pong | Hong Kong Polytechnic University |
| Alexander Posch | University of Vienna |
| Peter Richtarik | King Abdullah University of Science and Technology |
| Terry Ralph Rockafellar | University of Washington |
| Ernest Ryu | Seoul National University |
| Shoham Sabach | Technion Haifa |
| Hermann Schichl | University of Vienna |
| Chiara Schindler | University of Vienna |
| Michael Sedlmayer | University of Vienna |
| Anthony Man-Cho So | The Chinese University of Hong Kong |
| Mathias Staudigl | Universitaet Mannheim |
| Adrien Taylor | INRIA Paris |
| Marc Teboulle | Tel Aviv University |
| Buris Tongnoi | University of Vienna |
| Michael Ulbrich | Technical University of Munich |
| Stephen Wright | University of Wisconsin-Madison |
| Wotao Yin | Alibaba Group |
| Ya-xiang Yuan | Chinese Academy of Sciences |
| Alp Yurtsever | Umeå University |
Terry Ralph Rockafellar (U of Washington, Seattle): Progressive Decoupling of Dynamics in Convex Optimal Control
June 3, 2024 09:30 — 10:00
June 3, 2024 09:30 — 10:00
Ewa Bednarczuk (Polish Academy of Science, Warsaw): Constraint qualification and the existence of multipliers for nonconvex infinite-constrained optimization problems in Banach spaces
June 3, 2024 10:00 — 10:30
June 3, 2024 10:00 — 10:30
Jong-Shi Pang (U of Southern California, Los Angeles): Heaviside composite optimization and complementarity constraints by a progressive integer programming method
June 3, 2024 11:00 — 11:30
June 3, 2024 11:00 — 11:30
Panayotis Mertikopoulos (CNRS, Grenoble): The Long-Run Distribution of Stochastic Gradient Descent: A Large Deviations Analysis
June 3, 2024 11:30 — 12:00
June 3, 2024 11:30 — 12:00
Roberto Cominetti (U Adolfo Ibanez, Santiago de Chile): Error bounds for mean-payoff Markov decision processes
June 3, 2024 14:00 — 14:30
June 3, 2024 14:00 — 14:30
Adrien Taylor (INRIA Paris): Computer-aided Lyapunov analyses & counter-examples to the convergence of first-order optimization algorithms
June 3, 2024 15:30 — 16:00
June 3, 2024 15:30 — 16:00
Mert Gürbüzbalaban (Rutgers U): High probability and risk-averse guarantees for stochastic saddle point problems
June 3, 2024 16:30 — 17:00
June 3, 2024 16:30 — 17:00
Marc Teboulle (Tel Aviv U): Proximal Gradient Methods for Nonsmooth Nonconvex Minimax: A Unified Convergence Analysis
June 4, 2024 09:00 — 09:30
June 4, 2024 09:00 — 09:30
Russell Luke (U Göttingen): Nonconvex Optimization and the Curse of Local Minima: Lessons Learned from Orbital Tomography
June 4, 2024 09:30 — 10:00
June 4, 2024 09:30 — 10:00
Jalal Fadili (CNRS-ENSICAEN, U of Caen): Iterative Regularization of the Deep Inverse Prior via (Inertial) Gradient Flow
June 4, 2024 10:00 — 10:30
June 4, 2024 10:00 — 10:30
Ya-xiang Yuan (Chinese Academy of Sciences, Beijing): A new derivative-free method using an improved under-determined quadratic interpolation model
June 4, 2024 11:00 — 11:30
June 4, 2024 11:00 — 11:30
Frank Curtis (Lehigh U, Bethlehem): Stochastic Algorithms for Constrained Continuous Optimization
June 4, 2024 11:30 — 12:00
June 4, 2024 11:30 — 12:00
Michael Hintermüller (WIAS, Berlin): Quasi-Variational Inequalities: Semismooth Newton Methods, Optimal Control, and Uncertainties
June 4, 2024 14:00 — 14:30
June 4, 2024 14:00 — 14:30
Michael Ulbrich (TU Munich): Sample Size Estimates for Risk-Neutral Semilinear PDE-Constrained Optimization
June 4, 2024 14:30 — 15:00
June 4, 2024 14:30 — 15:00
Behzad Azmi (U Konstanz): Nonmonotone Forward-Backward Splitting Method for a Class of Infinite-Dimensional Nonsmooth Nonconvex Problems
June 4, 2024 15:30 — 16:00
June 4, 2024 15:30 — 16:00
Edouard Pauwels (TSE, Toulouse): Inexact subgradient algorithm with errors for semialgebraic functions
June 5, 2024 09:30 — 10:00
June 5, 2024 09:30 — 10:00
Niao He (ETH Zurich): A Hessian-Aware Stochastic Differential Equation Modelling of SGD
June 5, 2024 10:00 — 10:30
June 5, 2024 10:00 — 10:30
Shoham Sabach (Technion Haifa): Bilevel Optimization Problems: Algorithms and Theory
June 5, 2024 11:00 — 11:30
June 5, 2024 11:00 — 11:30
Stephen Wright (U of Wisconsin-Madison): Revisiting Inexact Fixed-Point Iterations for Min-Max Problems: Stochasticity and Structured Nonconvexity
June 5, 2024 14:00 — 14:30
June 5, 2024 14:00 — 14:30
Coralia Carțiș (U Oxford): Optimization of functions with low effective dimensionality
June 6, 2024 09:30 — 10:00
June 6, 2024 09:30 — 10:00
Peter Richtarik (KAUST, Thuwal): The First Optimal Distributed SGD in the Presence of Data, Compute and Communication Heterogeneity
June 6, 2024 11:00 — 11:30
June 6, 2024 11:00 — 11:30
Mustafa Pinar (Bilkent U, Ankara): Sparsity Regularized Mean-Variance Portfolio Optimization
June 6, 2024 11:30 — 12:00
June 6, 2024 11:30 — 12:00
Szilard Csaba Laszlo (U Cluj-Napoca): On strong convergence of inertial algorithms via Tikhonov regularization
June 6, 2024 14:30 — 15:00
June 6, 2024 14:30 — 15:00
Boris Mordukhovich (Wayne State U, Detroit): Semi-Newton Method in Difference Programming
June 7, 2024 09:00 — 09:30
June 7, 2024 09:00 — 09:30
Ernest Ryu (Seoul National U): Toward a grand unified theory of accelerations in optimization and machine learning
June 7, 2024 09:30 — 10:00
June 7, 2024 09:30 — 10:00
Ting Kei Pong (PolyU, Hong Kong): Kurdyka-Łojasiewicz exponent for a class of Hadamard-difference-parameterized models
June 7, 2024 10:00 — 10:30
June 7, 2024 10:00 — 10:30
Wotao Yin (Alibaba Group, Bellevue): Sum-of-Minimum Model: Joint Optimization of Specialized Models for Heterogeneous Data
June 7, 2024 11:00 — 11:30
June 7, 2024 11:00 — 11:30
Ion Necoara (U Politehnica Bucharest): Coordinate descent methods beyond separability and smoothness
June 7, 2024 11:30 — 12:00
June 7, 2024 11:30 — 12:00
Sorin-Mihai Grad (ENSTA Paris): A fresh look at algorithms for solving smooth multiobjective optimization problems
June 7, 2024 15:30 — 16:00
June 7, 2024 15:30 — 16:00
Masoud Ahookhosh (U Antwerpen): High-order Moreau envelope in the nonconvex setting: Framework and algorithms
June 7, 2024 16:00 — 16:30
June 7, 2024 16:00 — 16:30
At a glance
- Type:
- Workshop
- When:
- June 3, 2024 — June 7, 2024
- Where:
- ESI Boltzmann Lecture Hall
- Organizer(s):
-
Radu Ioan Bot (U of Vienna)
Yurii Malitskyi (U of Vienna)