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| - | ====== Lecture: Convex Optimization and Online Learning (MM25) ====== | ||
| - | ** Language: ** English or German, as the audience requests. | ||
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| - | ** Content: ** This lecture covers basic concepts of convex analysis and programming (classes of convex sets and functions, duality, nonexpansive mappings, splitting of convex programs, etc) with a focus on the analysis of iterative algorithms for solving large-scale convex optimization problems. Particular attention is paid to techniques for online convex optimization and the prediction of individual sequences in unknown environments, which play a key role in machine learning applications. | ||
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| - | The content of the lecture is targeted at students of mathematics and scientific computing with a long-term interest in machine learning, to prepare them for more advanced topics closer to research. | ||
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| - | ** Prerequisites: ** All proofs are elementary and only require knowledge from the mandatory undergraduate courses on analysis and linear algebra. | ||
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| - | ** Registration: ** If you wish to attend the lecture and the exercises, please sign up using [[https://muesli.mathi.uni-heidelberg.de/|MÜSLI]]. | ||
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| - | <color #ed1c24>You have to be logged in to access the files listed below.</color> | ||
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| - | **Lecture Notes: ** | ||
| - | All statements (second part) will be proven in the lecture. | ||
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| - | //Convex Analysis and Programming// | ||
| - | * {{ :teaching:ft1819:convex:convexfunctions.pdf |Smooth Convex Functions}} | ||
| - | * shortcut: {{ :teaching:ft1819:convex:kkt.pdf |KKT Conditions}} | ||
| - | * {{ :teaching:ft1819:convex:projection.pdf |Projection}} (update: 22.11.18), {{ :teaching:ft1819:convex:proxmaps.pdf |Proximal Mappings}} | ||
| - | * {{ :teaching:ft1819:convex:convexnonsmooth.pdf |Nonsmooth Convex Functions}} | ||
| - | * {{ :teaching:ft1819:convex:conjugation.pdf |Conjugation}} | ||
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| - | //Online Convex Optimisation and Learning// | ||
| - | * {{ :teaching:ft1819:convex:online-introduction.pdf |Introduction}} | ||
| - | * {{ :teaching:ft1819:convex:experts.pdf |Learning from Experts}} | ||
| - | * {{ :teaching:ft1819:convex:co-offline.pdf |Basic Offline Convex Optimisation}} | ||
| - | * {{ :teaching:ft1819:convex:co-online-fo.pdf |First-Order Online Convex Optimisation}} | ||
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| - | //Miscellany// | ||
| - | * {{ :teaching:ft1819:convex:loss-functions.pdf |Loss Functions}}, {{ :teaching:ft1819:convex:svd.pdf |SVD}} | ||
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| - | **Exercise Sheets ** | ||
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| - | * {{ :teaching:ft1819:convex:uebungsblatt1.pdf |Sheet 1}} (TBD 31.10) | ||
| - | * {{ :teaching:ft1819:convex:uebungsblatt2.pdf |Sheet 2}} (TBD 07.11) | ||
| - | * {{ :teaching:ft1819:convex:uebungsblatt3.pdf |Sheet 3}} (TBD 14.11, exercise 5: 21.11) / {{ :teaching:ft1819:convex:data_ex5.zip |data_ex5.zip}}, {{ :teaching:ft1819:convex:code_ex3.5.zip |code_ex3.5.zip}} | ||
| - | * {{ :teaching:ft1819:convex:uebungsblatt4.pdf |Sheet 4}} (TBD 21.11) | ||
| - | * {{ :teaching:ft1819:convex:uebungsblatt5.pdf |Sheet 5}} (TBD 28.11) {{ :teaching:ft1819:convex:code_ex5.3.zip |code_ex5.3.zip}} | ||
| - | * {{ :teaching:ft1819:convex:uebungsblatt6.pdf |Sheet 6}} (TBD 05.12) | ||
| - | * {{ :teaching:ft1819:convex:uebungsblatt7.pdf |Sheet 7}} (TBD 12.12) / {{ :teaching:ft1819:convex:data_ex3.zip |data_ex3.zip }} | ||