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| ====== Stochastic calculus for Machine Learning ====== | ====== Stochastic calculus for Machine Learning ====== | ||
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| + | {{ world:cours:qr-code-mva.png?150 }} | ||
| ====== Registration to the course ====== | ====== Registration to the course ====== | ||
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| ====== Program of the course ====== | ====== Program of the course ====== | ||
| - | * **Where?** ENS Paris-Saclay. %%Room: 1A14.%% | + | * **Where?** ENS Paris-Saclay. /*Room: 1A14.*/ |
| - | * **When?** Every course will hold on Thursday <color red>from 9H to 12H00</color> (exact dates are given below). | + | * **When?** /*Every course will hold on Thursday <color red>from 9H to 12H00</color> (exact dates are given below).*/ |
| - | * **Who?** The list of the teachers are given below with their acronyms: | + | |
| - | * AD: Alain Durmus. | + | |
| - | * RD: Randal Douc. | + | |
| - | * **What?** The chapters refer to the book: [[https://www.springer.com/gp/book/9783319977034|Markov chains]] by R. Douc, E. Moulines, P. Priouret and P. Soulier. Springer publishers. | + | |
| - | * **Teaching material**: {{world:mainmc-tome1.pdf|pdf version of Markov Chains book}} | + | |
| - | ^ Courses ^ Topics ^ Material ^ | + | ^ Courses ^ Topics ^ Material ^ |
| - | | 1 | Brownian motion and the Wiener space: defintions and first properties | | | + | | 1 | Brownian motion and the Wiener space: defintions and first properties | {{:world:prob_0.pdf| TD 0}} and {{:world:BM0.pdf| TD 1}} and {{:world:chap_1-_brownian_motion_and_v1.pdf|notes}} | |
| - | | 2 | Brownian motion: Markov property and further properties | | | + | | 2 | Brownian motion: Markov property and further properties | {{:world:td3_cs.pdf| TD 3}} and {{:world:note_2_cs.pdf| notes}} | |
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