Sebastian Banert

Advent of Code 2023 in Haskell Day 1

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Lagrange duality

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Fenchel duality

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Strong duality

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Dual solutions and the infimal value function

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Weak duality and primal-dual optimality

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Infimal value function and dual problem

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Perturbation functions

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Conjugate functions III Examples

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Conjugate functions II Subdifferential and proximal points

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Conjugate functions I Definition and properties

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Accelerated forward-backward IV Conclusion

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Accelerated forward-backward III Convergence rate

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Accelerated forward-backward II Consecutive iterations

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Accelerated forward-backward I Using previous iterations

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Forward-backward method V Convergence rate and conclusion

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Forward-backward method IV Convergence to an optimal point

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Forward-backward method III The fundamental inequality

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Forward-backward method II The algorithm, a descent method

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Forward-backward method I Optimality conditions

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Proximal points II Uniqueness and inequality

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Proximal points I Definition and existence

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Functions with Lipschitz continuous gradients

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Subgradient method VI Conclusion

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Subgradient method V Convergence of the iteration sequence

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Subgradient method IV Function values

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Subgradient method III Boundedness of the subgradients

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Subgradient method II Fundamental inequality and distance to a solution

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Subgradient method I Algorithm and examples

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Interior of the domain I Local boundedness from above

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