Control Theory and Optimization

Control Theory and Optimization

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Claudia Schillings: Bayesian data assimilation and filtering - lecture 2

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Claudia Schillings: Bayesian data assimilation and filtering - lecture 2

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Control Theory and Optimization

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  1. 1 Jean-Bernard Lasserre: The moment-LP and moment-SOS approaches
  2. 2 Stephan Volkwein: POD a-posteriori error estimation for PDE constrained optimization
  3. 3 Luc Robbiano : A spectral inequality for the bi-Laplace operator
  4. 4 Olivier Glass : Control of the motion of a set of particles
  5. 5 Giuseppe Buttazzo : Dirichlet-Neumann shape optimization problems
  6. 6 Jean-Michel Coron : Linear transformations for the stabilization of nonlinear PDE
  7. 7 Arnaud Münch : Inverse problems for linear PDEs using mixed formulations
  8. 8 Frank Morgan: Isoperimetry with density
  9. 9 Filippo Gazzola: A minimaxmax problem for improving the torsional stability of rectangular plates
  10. 10 Susanna Terracini : Regularity of the optimal sets for spectral functionals
  11. 11 Cristina Trombetti: On the stability of the Bossel-Daners inequality
  12. 12 Ilaria Fragalà: Some new inequalities for the Cheeger constant
  13. 13 Yves Achdou: Numerical methods for mean field games - Introduction to the system of PDEs and...
  14. 14 Yves Achdou: Numerical methods for mean field games - Monotone finite difference schemes
  15. 15 Yves Achdou: Numerical methods for mean field games - Variational MFG and related algorithms for...
  16. 16 René Aïd: Capacity expansion games with application to competition in power generation investments
  17. 17 René Carmona: Mean field games with major and minor players
  18. 18 Jean-David Benamou: Dynamic formulations of Optimal Transportation and variational MFGs
  19. 19 Plamen Turkedjiev: Least squares regression Monte Carlo for approximating BSDES and semilinear PDES
  20. 20 Stefano De Marco: Some asymptotic results about American options and volativity
  21. 21 Mathieu Laurière: Mean field type control with congestion
  22. 22 Alexander Schrijver: The partially disjoint paths problem
  23. 23 Tatiana Toro: Parametrizing with Guy
  24. 24 Jan Obłój: Pathwise or quasi-sure towards dynamic robust framework for pricing and hedging
  25. 25 Grégoire Loeper: Reconstruction by optimal transport: applications in cosmology and finance
  26. 26 Philippe Moireau: Data Assimilation: a deterministic vision, theory and applications. Lecture 2
  27. 27 Philippe Moireau: Data Assimilation: a deterministic vision, theory and applications. Lecture 1
  28. 28 Marcelo Pereyra: Bayesian inference and mathematical imaging - Lecture 2: Markov chain Monte Carlo
  29. 29 Marcelo Pereyra: Bayesian inference and mathematical imaging - Lecture 3
  30. 30 Marcelo Pereyra: Bayesian inference and mathematical imaging - Lecture 4: mixture...
  31. 31 Marcelo Pereyra: Bayesian inference and mathematical imaging - Lecture 1: Bayesian analysis...
  32. 32 Pierre Cardaliaguet: (In)efficiency in mean field games
  33. 33 Filippo Santambrogio: Equilibria and regularity in Mean Field Games with density penalization or...
  34. 34 Peter E. Caines: Graphon Mean Field Games and the GMFG Equations
  35. 35 Lenka Zdeborova: Algorithms in high-dimensional non-convex landscapes
  36. 36 Quentin Berthet: Learning with differentiable perturbed optimizers
  37. 37 Edouard Pauwels: What does back propagation compute?
  38. 38 Irène Waldspurger: Rank optimality for the Burer-Monteiro factorization
  39. 39 Joseph Salmon: The smoothed multivariate square-root Lasso: an optimization lens on concomitant...
  40. 40 Allesandro Lazaric: Reinforcement learning - lecture 3
  41. 41 Allesandro Lazaric: Reinforcement learning - lecture 4
  42. 42 Allesandro Lazaric: Reinforcement learning - lecture 3
  43. 43 Allesandro Lazaric: Reinforcement learning - lecture 2
  44. 44 Allesandro Lazaric: Reinforcement learning - lecture 1
  45. 45 Teasing poster: Mathematics, Signal Processing and Learning
  46. 46 Laurent Oudre: Machine learning meets signal processing - lecture 2
  47. 47 Laurent Oudre: Machine learning meets signal processing - lecture 1
  48. 48 Enrique Zuazua: Model predictive and random batch methods for a guide problem
  49. 49 Michael Herty: Stabilization of random kinetic equations
  50. 50 Giuseppe Buttazzo: Upper and lower bounds for some shape functionals
  51. 51 Pierre Cardaliaguet: Mean Field Games - Lecture 1
  52. 52 Pierre Cardaliaguet: Mean Field Games - Lecture 2
  53. 53 Pierre Cardaliaguet: Mean Field Games - Lecture 3
  54. 54 Dylan Possamaï: Principal Agent Modelling - lecture 1
  55. 55 Dylan Possamaï: Principal Agent Modelling - lecture 2
  56. 56 Dylan Possamaï: Principal Agent Modelling - lecture 3
  57. 57 Claudia Schillings: Bayesian data assimilation and filtering - lecture 2
  58. 58 Kirsten Morris: Decay of port-Hamiltonian systems with boundary dissipation
  59. 59 Stefano Stramigioli: Dual field port-Hamiltonian systems
  60. 60 Paul Kotyczka: Discrete-time port-Hamiltonian systems and control
  61. 61 Mats Gustafsson: Bandwidth bounds based on Herglotz-Nevanlinna functions and optimization
  62. 62 Jake Scott: Incorporating ecological epistasis into evolutionary control of cancer
  63. 63 Kristin Swanson: Every patient deserves their own equation: Sex, drugs and radiomics of brain Cancer
  64. 64 Enrique Zuazua: Optimal design of sensors and actuators
  65. 65 Karine Beauchard: Obstructions to small time local controllability
  66. 66 Jinchao Xu: A Mathematical Introduction to Deep Learning
  67. 67 Giacomo Dimarco: Numerical methods and uncertainty quantificationfor kinetic equations - lecture 2
  68. 68 Giacomo Dimarco: Numerical methods and uncertainty quantificationfor kinetic equations - lecture 1
  69. 69 Lénaïc Chizat: Trajectory inference with Schrödinger bridges - lecture 1
  70. 70 Lénaïc Chizat: Trajectory inference with Schrödinger bridges - lecture 2
  71. 71 Lénaïc Chizat: Trajectory inference with Schrödinger bridges - lecture 3
  72. 72 Filippo Santambrogio: Introduction to optimal transport theory - lecture 2
  73. 73 Filippo Santambrogio: Introduction to optimal transport theory - lecture 1
  74. 74 Stefan Volkwein: Introduction to PDE-constrained optimization - lecture 2
  75. 75 Stefan Volkwein: Introduction to PDE-constrained optimization - lecture 1
  76. 76 Günter Leugering: Nonoverlapping domain decompositionof nonlinear p-type optimal controlproblems ...
  77. 77 Xin Guo: Some recent progress in continuous-time reinforcement learning and regret analysis
  78. 78 Marie-Claire Quenez: European and american optionsin a non-linear incomplete market with default
  79. 79 Edouard Pauwels: Curiosities and counterexamples in smooth convex optimization
  80. 80 Kevin Scaman: Non-convex SGD and Lojasiewicz-type conditions for deep learning
  81. 81 Victor Magron : Exploiting sparsity in polynomial optimization Lecture 2
  82. 82 Victor Magron : Exploiting sparsity in polynomial optimization Lecture 1
  83. 83 Benoîte de Saporta : Stochastic control for medical treatment optimization
  84. 84 Pierre-Louis Lions: Large random matrices and PDE’s
  85. 85 Ali Aouad : Advancements in the control of dynamic matching markets
  86. 86 Giuseppe Savaré: Lagrangian, Eulerian and Kantorovich formulations of multi-agent optimal control...
  87. 87 Franca Hoffmann: Dynamics of strategic agents and algorithms as PDEs
  88. 88 Nicolas Charon: Path constrained unbalanced optimal transport
  89. 89 Julie Delon: Wasserstein barycenters for generic transport costs
  90. 90 Andrei Agrachev: Sub-Riemannian geometry of osculating curves
  91. 91 Jill-Jênn Vie: Intelligence artificielle
  92. 92 Emma Hubert: A new approach to principal-agent problems with volatility control
  93. 93 Xin Guo: Continuous-time mean field games: a primal-dual characterization
  94. 94 Gökçe Dayanıklı: Cooperation, competition, and common pool resources in mean field games
  95. 95 Yassine Hamoudi: Optimization problem on quantum computers - Lecture 2
  96. 96 Yassine Hamoudi: Optimization problem on quantum computers - Lecture 1

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