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11 documents available in our comprehensive collection of Wallerstein resources. Find practical guides, tutorials, and documentation to enhance your knowledge.

Preview of Wasserstein Derivatives
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Wasserstein Derivatives (WZ-derivative.pdf)

86 KBEN 3 pages
An elementary proof is provided for the structure of Wasserstein derivatives, specifically that DF(ξ) = g(ξ), where g is a deterministic function depending...
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Preview of Convex Optimization Project
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Convex Optimization Project (ConvexOptProject.pdf)

309 KBEN 10 pages
The project focuses on equipping the space of histograms with a suitable metric, specifically the Wasserstein metric, and explores the optimal transport...
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Preview of Advances in World-Systems Analysis: Relaxing Structuralism
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Advances in World-Systems Analysis: Relaxing Structuralism (Felipe-Amin-06-08.pdf.pdf)

291 KBEN 20 pages
A critical analysis of World-Systems Analysis, questioning its structural-functionalist bias, starting with Immanuel Wallerstein's seminal ideas on global economic structures
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Preview of Żywiąc wojnę
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Żywiąc wojnę (Tetragon-Creveld-Zywiac-wojne-2-wyd-fragment.pdf)

804 KBIT 32 pages
Martin van Creveld, "Żywiąc wojnę. Logistyka od Wallensteina do Pattona", to książka o logistyce wojskowej od XVII do XX wieku.
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Preview of Innovation 2010: Nov 30-Dec 3
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Innovation 2010: Nov 30-Dec 3 (ob1a2 vnitrek 1a2 A.pdf)

68 KBEN 4 pages
The XVII International Symposium INNOVATION 2010 is organized by the Association of Innovative Entrepreneurship CR in cooperation with various government and industry partners. The event takes place from November 30 to December 3, 2010, at several locations in Prague, including...
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Preview of Optimizing Functionals on the Space of Probabilities with Input Convex Neural Networks
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Optimizing Functionals on the Space of Probabilities with Input Convex Neural Networks (2106.00774.pdf)

5.64 MBEN 32 pages
Gradient flows are used to optimize functionals in probability spaces with the Wasserstein metric. A typical approach involves the Jordan-Kinderlehrer-Otto scheme, but this is challenging in high dimensions. We propose using input-convex neural networks to approximate the scheme.
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Preview of Stochastic Analysis and Applications: From SDEs to MCMC and Generators
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Stochastic Analysis and Applications: From SDEs to MCMC and Generators (Notes_of_Stochastic_Analysis.pdf)

635 KBEN 10 pages
Notes on Stochastic Analysis by Narsil Zhang, covering Ito's Formula, Forward and Backward Equations, SDE & MCMC methods (SGLD, Stochastic Gradient Hamiltonian MC), Wasserstein distance, and Gradient Flows with a focus on SGLD, all within the context of Peking University's CS...
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Preview of pdf
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pdf (48_04.12.20.pdf)

602 KBDE 1 page
Die Stadt Nördlingen gibt folgende Informationen bekannt: 1.
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PDF (2010.01787.pdf)

7.46 MBEN 39 pages
Relational regularized autoencoder (RAE) learns data distribution by minimizing reconstruction loss and relational regularization on the latent space.
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Preview of Wellposedness of Second Order Master Equations for Mean Field Games with Nonsmooth Data
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Wellposedness of Second Order Master Equations for Mean Field Games with Nonsmooth Data (MZ-Master.pdf)

861 KBEN 94 pages
This paper studies second-order master equations from mean field games with nonsmooth data, relaxing the regularity of the data while maintaining the monotonicity condition.
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Preview of Nonconvex Optimization Bounds
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Nonconvex Optimization Bounds (32_main_paper.pdf)

283 KBEN 10 pages
Stochastic gradient-based optimization algorithms use early stopping based on a validation function. The stopping rule terminates when the gradient norm falls below a threshold. Bounds are derived for expected iterations and gradient evaluations.
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