Statistical learning theory 2024/25 — различия между версиями
Bauwens (обсуждение | вклад) (Новая страница: « == General Information == Lectures: on TBA in room TBA and in [https://us02web.zoom.us/j/82300259484?pwd=NWxXekxBeE5yMm9UTmwvLzNNNGlnUT09 zoom] by [https://www…») |
Bauwens (обсуждение | вклад) |
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(не показано 9 промежуточных версии этого же участника) | |||
Строка 1: | Строка 1: | ||
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== General Information == | == General Information == | ||
+ | First lecture Saturday 21.09 at 10h00 in room R208 (and on the above zoom link). | ||
− | Lectures: on | + | Lectures: on Tuesday 9h30--10h50 in room M302 and in [https://us02web.zoom.us/j/82300259484?pwd=NWxXekxBeE5yMm9UTmwvLzNNNGlnUT09 zoom] by [https://www.hse.ru/en/org/persons/160550073 Bruno Bauwens] |
− | Seminars: | + | Seminars: online by [https://www.hse.ru/org/persons/225553845/ Nikita Lukianenko]. |
− | + | Please join the [https://t.me/+1begXb8SomhmODI8 telegram group] The course is similar to [http://wiki.cs.hse.ru/Statistical_learning_theory_2023/24 last year]. | |
+ | == Homeworks == | ||
+ | |||
+ | Deadline every 2 weeks, before the lecture. The tasks are at the end of each problem list. (Problem lists will be updated, check the year.) | ||
+ | |||
+ | Before 3rd lecture: see problem lists 1 and 2. | ||
+ | Before 5th lecture: see problems lists 3 and 4. | ||
+ | Etc. | ||
+ | |||
+ | Email homeworks to brbauwens-at-gmail.com. Start the subject line with SLT-HW. Results will be here. | ||
+ | |||
+ | Late policy: 1 homework can be submitted at most 24 late without explanations. | ||
== Course materials == | == Course materials == | ||
Строка 22: | Строка 33: | ||
|| Philosophy. The online mistake bound model. The halving and weighted majority algorithms. <!-- [https://drive.google.com/drive/folders/1NXiLbhmO2Ml7jFmnLtjqhOgCoHg7yn9T?usp=sharing movies] --> | || Philosophy. The online mistake bound model. The halving and weighted majority algorithms. <!-- [https://drive.google.com/drive/folders/1NXiLbhmO2Ml7jFmnLtjqhOgCoHg7yn9T?usp=sharing movies] --> | ||
|| [https://www.dropbox.com/scl/fi/j2vqqp3e86yx7pkgmkky6/01slides_all.pdf?rlkey=lxzhu3xd3epypia8j49v25erg&dl=0 sl01] | || [https://www.dropbox.com/scl/fi/j2vqqp3e86yx7pkgmkky6/01slides_all.pdf?rlkey=lxzhu3xd3epypia8j49v25erg&dl=0 sl01] | ||
− | || [https://www.dropbox.com/ | + | || [https://www.dropbox.com/scl/fi/svgelu3iwijls092ehqqf/00book_intro.pdf?rlkey=jxdya4290kfc0hfl06b0y7k4b&st=lnv8chxf&dl=0 ch00] [https://www.dropbox.com/s/i9pc4kf0zsdeksb/01book_onlineMistakeBound.pdf?dl=0 ch01] |
|| [https://www.dropbox.com/scl/fi/qs5wqr97qoyh3l2gfju48/01sem.pdf?rlkey=6lvzcbfkw6lj9y77ep64nq7lk&dl=0 prob01] | || [https://www.dropbox.com/scl/fi/qs5wqr97qoyh3l2gfju48/01sem.pdf?rlkey=6lvzcbfkw6lj9y77ep64nq7lk&dl=0 prob01] | ||
− | || [https://www.dropbox.com/scl/fi/kksvt6ttgf06u8uce6g9z/01sol.pdf?rlkey=ldcqaewvg7cqdlfqkt7ltckej&dl=0 sol01] | + | || <!-- [https://www.dropbox.com/scl/fi/kksvt6ttgf06u8uce6g9z/01sol.pdf?rlkey=ldcqaewvg7cqdlfqkt7ltckej&dl=0 sol01] --> |
|- | |- | ||
| [https://www.youtube.com/watch?v=gQm1G3Ep-5s ?? Sept] | | [https://www.youtube.com/watch?v=gQm1G3Ep-5s ?? Sept] | ||
Строка 31: | Строка 42: | ||
|| [https://www.dropbox.com/s/p3auugqwc89132b/02book_sequentialOptimalAlgorithm.pdf?dl=0 ch02] [https://www.dropbox.com/s/b00dcqk1rob7rdz/03book_perceptron.pdf?dl=0 ch03] | || [https://www.dropbox.com/s/p3auugqwc89132b/02book_sequentialOptimalAlgorithm.pdf?dl=0 ch02] [https://www.dropbox.com/s/b00dcqk1rob7rdz/03book_perceptron.pdf?dl=0 ch03] | ||
|| [https://www.dropbox.com/scl/fi/di1k87aq44ss07mq4s6pi/02sem.pdf?rlkey=yu476v8z77bal6ma029frnilm&dl=0 prob02] | || [https://www.dropbox.com/scl/fi/di1k87aq44ss07mq4s6pi/02sem.pdf?rlkey=yu476v8z77bal6ma029frnilm&dl=0 prob02] | ||
− | || [https://www.dropbox.com/scl/fi/d2wuka77bu18j9plivwl5/02sol.pdf?rlkey=yp2eprgxpc7r2antyidjd8qiw&dl=0 sol02] | + | || <!-- [https://www.dropbox.com/scl/fi/d2wuka77bu18j9plivwl5/02sol.pdf?rlkey=yp2eprgxpc7r2antyidjd8qiw&dl=0 sol02] --> |
|- | |- | ||
| [https://www.youtube.com/watch?v=H7kvz2rxX4o ?? Sept] | | [https://www.youtube.com/watch?v=H7kvz2rxX4o ?? Sept] | ||
Строка 38: | Строка 49: | ||
|| [https://www.dropbox.com/scl/fi/oetz6dwz77jdlta1k03li/04book_predictionWithExperts.pdf?rlkey=f0u947kiq9bjjaa46iv68lr7j&dl=0 ch04] [https://www.dropbox.com/scl/fi/cx7hsxzwg2f8ep4qcuefc/05book_introProbability.pdf?rlkey=rfq0y9cgzqvl1dlxkccc3qebv&dl=0 ch05] | || [https://www.dropbox.com/scl/fi/oetz6dwz77jdlta1k03li/04book_predictionWithExperts.pdf?rlkey=f0u947kiq9bjjaa46iv68lr7j&dl=0 ch04] [https://www.dropbox.com/scl/fi/cx7hsxzwg2f8ep4qcuefc/05book_introProbability.pdf?rlkey=rfq0y9cgzqvl1dlxkccc3qebv&dl=0 ch05] | ||
|| [https://www.dropbox.com/scl/fi/3w9yk9rb7l0pb2l6q94fc/03sem.pdf?rlkey=jt40nnw35t7e8je9nj1ef22f1&dl=0 prob03] | || [https://www.dropbox.com/scl/fi/3w9yk9rb7l0pb2l6q94fc/03sem.pdf?rlkey=jt40nnw35t7e8je9nj1ef22f1&dl=0 prob03] | ||
− | || [https://www.dropbox.com/scl/fi/w26siug25arwoilgb5t7i/03sol.pdf?rlkey=7waf3ddt4fvz0xeicicayoilt&dl=0 sol03] | + | || <!-- [https://www.dropbox.com/scl/fi/w26siug25arwoilgb5t7i/03sol.pdf?rlkey=7waf3ddt4fvz0xeicicayoilt&dl=0 sol03] --> |
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Строка 48: | Строка 59: | ||
|| [https://www.dropbox.com/s/nh4puyv7nst4ems/06book_sampleComplexity.pdf?dl=0 ch06] | || [https://www.dropbox.com/s/nh4puyv7nst4ems/06book_sampleComplexity.pdf?dl=0 ch06] | ||
|| [https://www.dropbox.com/scl/fi/n4004z5mmrn3nbr9ggtt9/05sem.pdf?rlkey=sntvs95trliffbc2vh5vge06b&dl=0 prob05] | || [https://www.dropbox.com/scl/fi/n4004z5mmrn3nbr9ggtt9/05sem.pdf?rlkey=sntvs95trliffbc2vh5vge06b&dl=0 prob05] | ||
− | || [https://www.dropbox.com/scl/fi/55530savq0vn6apra7oo4/05sol.pdf?rlkey=ql9q3a7s7k5dkggymul4p4s2o&dl=0 sol05] | + | || <!-- [https://www.dropbox.com/scl/fi/55530savq0vn6apra7oo4/05sol.pdf?rlkey=ql9q3a7s7k5dkggymul4p4s2o&dl=0 sol05] --> |
|- | |- | ||
| [https://www.youtube.com/watch?v=8J5B9CCy-ws ?? Oct] | | [https://www.youtube.com/watch?v=8J5B9CCy-ws ?? Oct] | ||
Строка 55: | Строка 66: | ||
|| [https://www.dropbox.com/s/eurz2vkvt1wa5zm/07book_growthFunctions.pdf?dl=0 ch07] [https://www.dropbox.com/scl/fi/50oxlmjkx59hjrq82yqvx/08book_VCdimension.pdf?rlkey=5dtlcis378kqu24ttko6s7zpf&dl=0 ch08] | || [https://www.dropbox.com/s/eurz2vkvt1wa5zm/07book_growthFunctions.pdf?dl=0 ch07] [https://www.dropbox.com/scl/fi/50oxlmjkx59hjrq82yqvx/08book_VCdimension.pdf?rlkey=5dtlcis378kqu24ttko6s7zpf&dl=0 ch08] | ||
|| [https://www.dropbox.com/scl/fi/wvj022mv9w82mlynp4t28/06sem.pdf?rlkey=k8bieoxn7zlkfkzyhi311n26s&dl=0 prob06] | || [https://www.dropbox.com/scl/fi/wvj022mv9w82mlynp4t28/06sem.pdf?rlkey=k8bieoxn7zlkfkzyhi311n26s&dl=0 prob06] | ||
− | || [https://www.dropbox.com/scl/fi/gcr4n00ef62ezrta7atll/06sol.pdf?rlkey=b9rgqxgmnlxouvsl5eevpwg3d&dl=0 sol06] | + | || <!-- [https://www.dropbox.com/scl/fi/gcr4n00ef62ezrta7atll/06sol.pdf?rlkey=b9rgqxgmnlxouvsl5eevpwg3d&dl=0 sol06] --> |
|- | |- | ||
| [https://www.youtube.com/watch?v=zHau8Br_UFQ ?? Oct] | | [https://www.youtube.com/watch?v=zHau8Br_UFQ ?? Oct] | ||
Строка 62: | Строка 73: | ||
|| [https://www.dropbox.com/scl/fi/15zjsv1w9coq2py9djlai/09book_riskBounds.pdf?rlkey=4lnyo8kcd226qlybrdgyt36i8&dl=0 ch09] | || [https://www.dropbox.com/scl/fi/15zjsv1w9coq2py9djlai/09book_riskBounds.pdf?rlkey=4lnyo8kcd226qlybrdgyt36i8&dl=0 ch09] | ||
|| [https://www.dropbox.com/scl/fi/neso7q9vq8ouix208u841/07sem.pdf?rlkey=k8dxkxwqdxf3kjsclzt9vwiw5&dl=0 prob07] | || [https://www.dropbox.com/scl/fi/neso7q9vq8ouix208u841/07sem.pdf?rlkey=k8dxkxwqdxf3kjsclzt9vwiw5&dl=0 prob07] | ||
− | || [https://www.dropbox.com/scl/fi/dw3u10rhy33pv37z5zf5m/07sol.pdf?rlkey=wssi52zoiveccmpy2197ry5pt&dl=0 sol07] | + | || <!-- [https://www.dropbox.com/scl/fi/dw3u10rhy33pv37z5zf5m/07sol.pdf?rlkey=wssi52zoiveccmpy2197ry5pt&dl=0 sol07] --> |
|- | |- | ||
| [https://www.youtube.com/watch?v=yMsUH1brAs8 ?? Oct] | | [https://www.youtube.com/watch?v=yMsUH1brAs8 ?? Oct] | ||
Строка 69: | Строка 80: | ||
|| [https://www.dropbox.com/scl/fi/ohtmf1fwsu9c6vkrj6e5a/10book_measureConcentration.pdf?rlkey=dqsgskp8slui6xoq9c7tx680b&dl=0 ch10] [https://www.dropbox.com/s/hfrvhebbsskbk6g/11book_RademacherComplexity.pdf?dl=0 ch11] | || [https://www.dropbox.com/scl/fi/ohtmf1fwsu9c6vkrj6e5a/10book_measureConcentration.pdf?rlkey=dqsgskp8slui6xoq9c7tx680b&dl=0 ch10] [https://www.dropbox.com/s/hfrvhebbsskbk6g/11book_RademacherComplexity.pdf?dl=0 ch11] | ||
|| [https://www.dropbox.com/scl/fi/g278mmezenlyxd1my0ta9/08sem.pdf?rlkey=hvqmbumpd0xb6pumdgv5bqx6u&dl=0 prob08] | || [https://www.dropbox.com/scl/fi/g278mmezenlyxd1my0ta9/08sem.pdf?rlkey=hvqmbumpd0xb6pumdgv5bqx6u&dl=0 prob08] | ||
− | || [https://www.dropbox.com/scl/fi/06yobqe58fiecsobp4yrb/08sol.pdf?rlkey=9c7t1y4nxxtg14vpndsyyko2u&dl=0 sol08] | + | || <!-- [https://www.dropbox.com/scl/fi/06yobqe58fiecsobp4yrb/08sol.pdf?rlkey=9c7t1y4nxxtg14vpndsyyko2u&dl=0 sol08] --> |
|- | |- | ||
| | | | ||
Строка 79: | Строка 90: | ||
|| [https://www.dropbox.com/s/573a2vtjfx8qqo8/12book_regression.pdf?dl=0 ch12] [https://www.dropbox.com/scl/fi/hxeh5btc0bb2f52fnqh5f/13book_SVM.pdf?rlkey=dw3u2rtfstpsb8mi9hnuc8poy&dl=0 ch13] | || [https://www.dropbox.com/s/573a2vtjfx8qqo8/12book_regression.pdf?dl=0 ch12] [https://www.dropbox.com/scl/fi/hxeh5btc0bb2f52fnqh5f/13book_SVM.pdf?rlkey=dw3u2rtfstpsb8mi9hnuc8poy&dl=0 ch13] | ||
|| [https://www.dropbox.com/scl/fi/rp2m0dvovdjbvzdl7t1bl/09sem.pdf?rlkey=v1jsm5dagh7tymci5pkqn5gox&dl=0 prob09] | || [https://www.dropbox.com/scl/fi/rp2m0dvovdjbvzdl7t1bl/09sem.pdf?rlkey=v1jsm5dagh7tymci5pkqn5gox&dl=0 prob09] | ||
− | || [https://www.dropbox.com/scl/fi/e598w1t8tzqxfvn1d4ww1/09sol.pdf?rlkey=yr1gzu8kg2rdkubaelicljj46&dl=0 sol09] | + | || <!-- [https://www.dropbox.com/scl/fi/e598w1t8tzqxfvn1d4ww1/09sol.pdf?rlkey=yr1gzu8kg2rdkubaelicljj46&dl=0 sol09] --> |
|- | |- | ||
| [https://youtu.be/9FhFxLHR4eE ?? Nov] | | [https://youtu.be/9FhFxLHR4eE ?? Nov] | ||
Строка 86: | Строка 97: | ||
|| [https://www.dropbox.com/scl/fi/lozpqk5nnm8us77qfhn7x/14book_kernels.pdf?rlkey=s8e7a46rm3znkw13ubj3fzzz0&dl=0 ch14] | || [https://www.dropbox.com/scl/fi/lozpqk5nnm8us77qfhn7x/14book_kernels.pdf?rlkey=s8e7a46rm3znkw13ubj3fzzz0&dl=0 ch14] | ||
|| [https://www.dropbox.com/scl/fi/9mjmb6deu08ipf38s57bh/10sem.pdf?rlkey=z1khm4i8r39eeqmhargte24s4&dl=0 prob10] | || [https://www.dropbox.com/scl/fi/9mjmb6deu08ipf38s57bh/10sem.pdf?rlkey=z1khm4i8r39eeqmhargte24s4&dl=0 prob10] | ||
− | || [https://www.dropbox.com/scl/fi/a5c0buap9b1h1ojdbhp3u/10sol.pdf?rlkey=8ft5tjyy1sl5dkj4p4hh8phbc&dl=0 sol10] | + | || <!-- [https://www.dropbox.com/scl/fi/a5c0buap9b1h1ojdbhp3u/10sol.pdf?rlkey=8ft5tjyy1sl5dkj4p4hh8phbc&dl=0 sol10] --> |
|- | |- | ||
| [https://www.youtube.com/watch?v=OgiaWrWh_WA ?? Nov] | | [https://www.youtube.com/watch?v=OgiaWrWh_WA ?? Nov] | ||
Строка 93: | Строка 104: | ||
|| [https://www.dropbox.com/s/e7m1cs7e8ulibsf/15book_AdaBoost.pdf?dl=0 ch15] | || [https://www.dropbox.com/s/e7m1cs7e8ulibsf/15book_AdaBoost.pdf?dl=0 ch15] | ||
|| [https://www.dropbox.com/scl/fi/ykbzx314pdn3mn3jiehli/11sem.pdf?rlkey=hpmtks20a3k5zsvr8jm1iqc35&dl=0 prob11] | || [https://www.dropbox.com/scl/fi/ykbzx314pdn3mn3jiehli/11sem.pdf?rlkey=hpmtks20a3k5zsvr8jm1iqc35&dl=0 prob11] | ||
− | || [https://www.dropbox.com/scl/fi/c805j4f54ioiozphvh9j0/11sol.pdf?rlkey=6rrxlweaiko1lm0z2ua4k7mqk&dl=0 sol11] | + | || <!-- [https://www.dropbox.com/scl/fi/c805j4f54ioiozphvh9j0/11sol.pdf?rlkey=6rrxlweaiko1lm0z2ua4k7mqk&dl=0 sol11] --> |
|- | |- | ||
| [https://youtu.be/GL574ljefJ8 ?? Nov] | | [https://youtu.be/GL574ljefJ8 ?? Nov] | ||
Строка 110: | Строка 121: | ||
|} | |} | ||
− | Background on multi-armed bandits: A. Slivkins, [Introduction to multi-armed bandits https://arxiv.org/pdf/1904.07272.pdf], 2022. | + | <!-- Background on multi-armed bandits: A. Slivkins, [Introduction to multi-armed bandits https://arxiv.org/pdf/1904.07272.pdf], 2022.--> |
The lectures in October and November are based on the book: | The lectures in October and November are based on the book: | ||
Foundations of machine learning 2nd ed, Mehryar Mohri, Afshin Rostamizadeh, and Ameet Talwalker, 2018. | Foundations of machine learning 2nd ed, Mehryar Mohri, Afshin Rostamizadeh, and Ameet Talwalker, 2018. | ||
− | + | A gentle introduction to the materials of the first 3 lectures and an overview of probability theory, can be found in chapters 1-6 and 11-12 of the following book: | |
− | Sanjeev Kulkarni and Gilbert Harman: An Elementary Introduction to Statistical Learning Theory, 2012. | + | Sanjeev Kulkarni and Gilbert Harman: An Elementary Introduction to Statistical Learning Theory, 2012. |
== Grading formula == | == Grading formula == | ||
Строка 122: | Строка 133: | ||
Final grade = 0.35 * [score of homeworks] + 0.35 * [score of colloquium] + 0.3 * [score on the exam] + bonus from quizzes. | Final grade = 0.35 * [score of homeworks] + 0.35 * [score of colloquium] + 0.3 * [score on the exam] + bonus from quizzes. | ||
− | All homework questions have the same weight. Each solved extra homework task increases the score of the final exam by 1 point. | + | All homework questions have the same weight. Each solved extra homework task increases the score of the final exam by 1 point. At the end of the lectures there is a short quiz in which you may earn 0.1 bonus points on the final non-rounded grade. |
− | There is no rounding except | + | There is no rounding except for transforming the final grade to the official grade. Arithmetic rounding is used. |
− | Autogrades: if you only need 6/10 on the exam to | + | Autogrades: if you only need 6/10 on the exam to have the maximal 10/10 for the course, this will be given automatically. This may happen because of extra homework questions and bonuses from quizzes. |
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== Colloquium == | == Colloquium == | ||
Строка 150: | Строка 150: | ||
-- You may use handwritten notes, lecture materials from this wiki (either printed or through your PC), Mohri's book <br> | -- You may use handwritten notes, lecture materials from this wiki (either printed or through your PC), Mohri's book <br> | ||
-- You may not search on the internet or interact with other humans (e.g. by phone, forums, etc) | -- You may not search on the internet or interact with other humans (e.g. by phone, forums, etc) | ||
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== Office hours == | == Office hours == |
Текущая версия на 22:35, 20 сентября 2024
Содержание
General Information
First lecture Saturday 21.09 at 10h00 in room R208 (and on the above zoom link).
Lectures: on Tuesday 9h30--10h50 in room M302 and in zoom by Bruno Bauwens
Seminars: online by Nikita Lukianenko.
Please join the telegram group The course is similar to last year.
Homeworks
Deadline every 2 weeks, before the lecture. The tasks are at the end of each problem list. (Problem lists will be updated, check the year.)
Before 3rd lecture: see problem lists 1 and 2. Before 5th lecture: see problems lists 3 and 4. Etc.
Email homeworks to brbauwens-at-gmail.com. Start the subject line with SLT-HW. Results will be here.
Late policy: 1 homework can be submitted at most 24 late without explanations.
Course materials
Video | Summary | Slides | Lecture notes | Problem list | Solutions |
---|---|---|---|---|---|
Part 1. Online learning | |||||
?? Sept | Philosophy. The online mistake bound model. The halving and weighted majority algorithms. | sl01 | ch00 ch01 | prob01 | |
?? Sept | The perceptron algorithm. Kernels. The standard optimal algorithm. | sl02 | ch02 ch03 | prob02 | |
?? Sept | Prediction with expert advice. Recap probability theory (seminar). | sl03 | ch04 ch05 | prob03 | |
Part 2. Distribution independent risk bounds | |||||
?? Oct | Necessity of a hypothesis class. Sample complexity in the realizable setting, examples: threshold functions and finite classes. | sl04 | ch06 | prob05 | |
?? Oct | Growth functions, VC-dimension and the characterization of sample comlexity with VC-dimensions | sl05 | ch07 ch08 | prob06 | |
?? Oct | Risk decomposition and the fundamental theorem of statistical learning theory | sl06 | ch09 | prob07 | |
?? Oct | Bounded differences inequality, Rademacher complexity, symmetrization, contraction lemma. | sl07 | ch10 ch11 | prob08 | |
Part 3. Margin risk bounds with applications | |||||
?? Nov | Simple regression, support vector machines, margin risk bounds, and neural nets with dropout regularization | sl08 | ch12 ch13 | prob09 | |
?? Nov | Kernels: RKHS, representer theorem, risk bounds | sl09 | ch14 | prob10 | |
?? Nov | AdaBoost and the margin hypothesis | sl10 | ch15 | prob11 | |
?? Nov | Implicit regularization of stochastic gradient descent in overparameterized neural nets (recording with many details about the Hessian) | ch16 ch17 | |||
?? Dec | Part 2 of previous lecture: Hessian control and stability of the NTK. |
The lectures in October and November are based on the book:
Foundations of machine learning 2nd ed, Mehryar Mohri, Afshin Rostamizadeh, and Ameet Talwalker, 2018.
A gentle introduction to the materials of the first 3 lectures and an overview of probability theory, can be found in chapters 1-6 and 11-12 of the following book: Sanjeev Kulkarni and Gilbert Harman: An Elementary Introduction to Statistical Learning Theory, 2012.
Grading formula
Final grade = 0.35 * [score of homeworks] + 0.35 * [score of colloquium] + 0.3 * [score on the exam] + bonus from quizzes.
All homework questions have the same weight. Each solved extra homework task increases the score of the final exam by 1 point. At the end of the lectures there is a short quiz in which you may earn 0.1 bonus points on the final non-rounded grade.
There is no rounding except for transforming the final grade to the official grade. Arithmetic rounding is used.
Autogrades: if you only need 6/10 on the exam to have the maximal 10/10 for the course, this will be given automatically. This may happen because of extra homework questions and bonuses from quizzes.
Colloquium
Rules and questions from last year.
Date: TBA
Problems exam
TBA
-- You may use handwritten notes, lecture materials from this wiki (either printed or through your PC), Mohri's book
-- You may not search on the internet or interact with other humans (e.g. by phone, forums, etc)
Office hours
Bruno Bauwens: TBA
Nikita Lukianenko: Write in Telegram, the time is flexible