|
|
| Строка 1: |
Строка 1: |
| − | | + | Segeralah Mendaftar langsung di |
| − | == General Information ==
| + | * [https://macanplay.net/ Macanslot] |
| − | | + | * [https://paradox3d.net/ InaTogel] |
| − | The [https://www.dropbox.com/s/8iivgt3a96yw308/syllabus_StatisticalLearning_Bach_2018_2019.pdf?dl=0 syllabus]
| + | * [https://macanwin.net/ QqMacan] |
| − | | + | * [https://lechers.cc/ RoyalToto] |
| − | [https://www.dropbox.com/s/dh2n9cmhpmx97nj/colloqQuest.pdf?dl=0 Questions colloquium on 29 October.] (Lectures 1-8 updated 24/10.) | + | * [https://xenogames.net/ JayaTogelUp] |
| − | | + | * [https://eeooii.info/ Raja Slot4D] |
| − | Deadline homework 1: October 2nd. Questions: see seminars [https://www.dropbox.com/s/jb9mriumhtdpn8m/03sem.pdf?dl=0 3] and [https://www.dropbox.com/s/l2d9f7u77smrx4u/04sem.pdf?dl=0 4].
| + | * [https://139.180.153.95/ Raja Slot4D] |
| − | | + | * [https://209.58.183.93/ JayaTogelUp] |
| − | Deadline homework 2: October 27nd. Questions: see seminars 5-8 below.
| + | * [https://ronin138.com/ Ronin138] |
| − | | + | * [https://addicthealious.website/ slot 4d] |
| − | Deadline homework 3: December 11nd. Questions: see seminars 9-12 below.
| + | * [https://18.142.23.191/ Macan Slot] |
| − | | + | * [https://royaltotopedia.com RoyTop88] |
| − | [https://www.dropbox.com/s/dy9yu1ro4k5miet/List%20of%20Students_Bruno.xlsx?dl=0 Marks] | + | * [https://macanplay.com MacanSlot] |
| − | | + | * [https://macantoto88.com Toto 88] |
| − | Intermediate exams: October 29th.
| + | * [https://jayatogelup.com.com jayatogelup] |
| − | | + | [https://ronin19.com/ Ronin138] |
| − | Final exam: December 20th, same system as for intermediate exams. [https://www.dropbox.com/s/uaxdredmmm5ke7t/finalTheoryQuest.pdf?dl=0 Theory questions]
| + | [https://addicthealing.website/ slot 4d] |
| − | | + | [https://jayatogelcc.cc/ jayatogel] |
| − | Consultation: December 17th, no lecture. Students can ask questions and ask for solutions of exercises.
| + | [https://jayatogelcc.cc/ jayatogelcc] |
| − | | + | [http://northcoaststeelhead.com/ northcoaststeelhead.com] |
| − | | + | [http://supremeoutlet.us/ supremeoutlet.us] |
| − | == Course materials ==
| + | [http://208.78.220.231/ freebet] |
| − | | + | [http://blackfridaymichaelkors.us/ freebet] |
| − | {| class="wikitable"
| + | [https://supremeshirtshop.us/ supremeshirtshop.us] |
| − | |-
| + | [https://macanplayslot.web.fc2.com/ macanplay] |
| − | ! Date !! Summary !! Lecture notes !! Problem list !! Solutions
| + | [https://royaltotopedia4d.web.fc2.com/ royaltotopedia] |
| − | |-
| + | [https://macanplay8.web.fc2.com/ macanplay slot] |
| − | | 3 Sept || PAC-learning in the realizable setting definitions || [https://www.dropbox.com/s/l8e8xjfe2f8tjz8/01lect.pdf?dl=0 lecture1.pdf] updated 23/09
| + | [https://royaltotopedia88.web.fc2.com/ royaltoto] |
| − | || [https://www.dropbox.com/s/4ic3ce71znglmu9/01sem.pdf?dl=0 Problem list 1] || [https://www.dropbox.com/s/cixli4sghy0w01q/01solution.pdf?dl=0 Solutions 1]
| + | [https://olxtotos.web.fc2.com/ olxtoto] |
| − | |-
| + | [https://linklist.bio/OLX.TOTO olxtoto] |
| − | | 10 Sept || VC-dimension and growth functions || [https://www.dropbox.com/s/q1jc2dlotwdn9e2/02lect.pdf?dl=0 lecture2.pdf] updated 23/09 || [https://www.dropbox.com/s/4gimo3fij5p7lnc/02sem.pdf?dl=0 Problem list 2] || [https://www.dropbox.com/s/69pnkefexsmq6nu/02solution.pdf?dl=0 Solutions 2]
| + | [https://c.mi.com/thread-4131553-1-0.html olxtoto] |
| − | |-
| + | [https://heylink.me/FAFA138 fafa138] |
| − | | 17 Sept || Proof that finite VC-dimension implies PAC-learnability || [https://www.dropbox.com/s/9rfvwvf0ne95j8e/03lect.pdf?dl=0 lecture3.pdf] updated 23/09 || [https://www.dropbox.com/s/jb9mriumhtdpn8m/03sem.pdf?dl=0 Problem list 3] || [https://www.dropbox.com/s/f0gnrfxv9i7at91/03solution.pdf?dl=0 Solutions 3]
| + | [https://heylink.me/FaFa138 fafa138] |
| − | |-
| + | [https://heylink.me/Fafa138 fafa138] |
| − | | 24 Sept || Applications to decision trees and threshold neural networks. Agnostic PAC-learnability. || [https://www.dropbox.com/s/9oa2zg7jz2ovquf/04lect.pdf?dl=0 lecture4.pdf] || [https://www.dropbox.com/s/l2d9f7u77smrx4u/04sem.pdf?dl=0 Problem list 4] || [https://www.dropbox.com/s/t4tqtw7tdh54u2i/04solution.pdf?dl=0 Solution 4]
| + | [https://magic.ly/FAFA138 fafa138] |
| − | |-
| + | [https://fafa138slot.web.fc2.com fafa138] |
| − | | 1 Oct || Agnostic PAC-learnability is equivalent with finite VC-dimension, structural risk minimization || [https://www.dropbox.com/s/jsrse5qaqk2jhi1/05lect.pdf?dl=0 lecture5.pdf] 14/10 || [https://www.dropbox.com/s/etw67uq1pu5g58t/05sem.pdf?dl=0 Problem list 5] || [https://www.dropbox.com/s/6mpom53yrldcrjy/05solution.pdf?dl=0 Solution 5]
| + | [https://heylink.me/FAFA138 fafa138] |
| − | |-
| + | [http://ec2-13-250-3-146.ap-southeast-1.compute.amazonaws.com/ fafa138] |
| − | | 9 Oct || Boosting, Mohri's book pages 121-131. || [https://www.dropbox.com/s/m6tc4miryv6cs21/06lect.pdf?dl=0 lecture6.pdf] 23/10 || [https://www.dropbox.com/s/85t74k9wmibcnmr/06sem.pdf?dl=0 Problem list 6] || No solution.
| + | |
| − | |-
| + | |
| − | | 15 Oct || Rademacher complexity and contraction lemma (=Talagrand's lemma), Mohri's book pages 33-41 and 78-79 || [https://www.dropbox.com/s/y2vr3mrwp66cuvz/07lect.pdf?dl=0 lecture7.pdf] || [https://www.dropbox.com/s/cuo0tmfv4k2egvh/07sem.pdf?dl=0 Problem list 7] || See lecture7.pdf
| + | |
| − | |-
| + | |
| − | | 21 Oct || Margin theory and risk bounds for boosting. || [https://www.dropbox.com/s/o5zae3d8nw5eexw/08lect.pdf?dl=0 lecture8.pdf] || [https://www.dropbox.com/s/xg7u3ss1a0vog5j/08sem.pdf?dl=0 Problem list 8]|| See lecture6.pdf for ex. 8.6.
| + | |
| − | |-
| + | |
| − | | 12 Nov || Deep boosting, we study the paper [http://www.cs.nyu.edu/~mohri/pub/mboost.pdf Multi-class deep boosting], V. Kuznetsov, M Mohri, and U. Syed, Advances in Neural Information Processing Systems, p2501--2509, 2014. Notes will be provided. || [https://www.dropbox.com/s/tc7drmxwu53opzq/09lect.pdf?dl=0 lecture9.pdf] || [https://www.dropbox.com/s/lsu6tgmc767u3yd/09sem.pdf?dl=0 Problem list 9] || [https://www.dropbox.com/s/8wmswbynzx0s9hd/09sol.pdf?dl=0 Solutions 9.]
| + | |
| − | |-
| + | |
| − | | 19 Nov || Support vector machines, primal and dual optimization problem, risk bounds. || See chapt. 5 of Mohri's book || [https://www.dropbox.com/s/ys37nsdfz3aa4ry/10sem.pdf?dl=0 Problem list 10]|| No solution.
| + | |
| − | |-
| + | |
| − | | 26 Nov || Kernels, Kernel reproducing Hilbert spaces, representer theorem, examples of kernels || [https://www.dropbox.com/s/xkic1j6r516ierl/11lect.pdf?dl=0 lecture11.pdf] || [https://www.dropbox.com/s/g3huq5aqzdaesrg/11sem.pdf?dl=0 Problem set 11] || Solutions: see lecture11.pdf
| + | |
| − | |-
| + | |
| − | | 3 Dec || A polynomial time improper learning algorithm for constant depth L1-regularized neural networks, from [http://www.jmlr.org/proceedings/papers/v48/zhangd16.pdf this paper]. Online algorithms: halving algorithm, weighted and exponentially weighted average algorithms. See Mohri's book Sections 7.1 and 7.2. || [https://www.dropbox.com/s/aq6798jps111l86/12lect.pdf?dl=0 lecture12.pdf] || [https://www.dropbox.com/s/o4t6smc70o1bt3t/12sem.pdf?dl=0 Problem list 12] || No solution.
| + | |
| − | |-
| + | |
| − | | 10 Dec || We finish online learning. Discuss the algorithm from [http://papers.nips.cc/paper/4616-bandit-algorithms-boost-brain-computer-interfaces-for-motor-task-selection-of-a-brain-controlled-button.pdf this paper]. || || See previous list. ||
| + | |
| − | |}
| + | |
| − | | + | |
| − | 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.
| + | |
| − | | + | |
| − | Afterward, we hope to cover chapters 1-8 from the book:
| + | |
| − | Foundations of machine learning, Mehryar Mohri, Afshin Rostamizadeh, and Ameet Talwalker, 2012. These books can be downloaded from http://gen.lib.rus.ec/ .
| + | |
| − | | + | |
| − | <!--
| + | |
| − | (We will study a new boosting algorithm, based on the paper: )
| + | |
| − | -->
| + | |
| − | | + | |
| − | == Office hours ==
| + | |
| − | | + | |
| − | {| class="wikitable"
| + | |
| − | |-
| + | |
| − | ! Person !! Monday !! Tuesday !! Wednesday !! Thursday !! Friday !!
| + | |
| − | |-
| + | |
| − | | Bruno Bauwens || 16:45–19:00 || 15:05–18:00 || || || || Room 620
| + | |
| − | |-
| + | |
| − | |}
| + | |
| − | | + | |
| − | | + | |
| − | == Russian texts ==
| + | |
| − | | + | |
| − | The following links might help students who have trouble with English. A [http://www.machinelearning.ru/wiki/images/d/d9/Voron-2011-tnop.pdf lecture] on VC-dimensions was given by K. Vorontsov.
| + | |
| − | A [http://machinelearning.ru/wiki/index.php?title=%D0%A2%D0%B5%D0%BE%D1%80%D0%B8%D1%8F_%D1%81%D1%82%D0%B0%D1%82%D0%B8%D1%81%D1%82%D0%B8%D1%87%D0%B5%D1%81%D0%BA%D0%BE%D0%B3%D0%BE_%D0%BE%D0%B1%D1%83%D1%87%D0%B5%D0%BD%D0%B8%D1%8F_(%D0%BA%D1%83%D1%80%D1%81_%D0%BB%D0%B5%D0%BA%D1%86%D0%B8%D0%B9%2C_%D0%9D._%D0%9A._%D0%96%D0%B8%D0%B2%D0%BE%D1%82%D0%BE%D0%B2%D1%81%D0%BA%D0%B8%D0%B9) course] on Statistical Learning Theory by Nikita Zhivotovsky is given at MIPT. Some short description about PAC learning on p136 in the [http://gen.lib.rus.ec/search.php?req=%D0%9D%D0%B0%D1%83%D0%BA%D0%B0+%D0%B8+%D0%B8%D1%81%D0%BA%D1%83%D1%81%D1%81%D1%82%D0%B2%D0%BE+%D0%BF%D0%BE%D1%81%D1%82%D1%80%D0%BE%D0%B5%D0%BD%D0%B8%D1%8F+%D0%B0%D0%BB%D0%B3%D0%BE%D1%80%D0%B8%D1%82%D0%BC%D0%BE%D0%B2%2C+%D0%BA%D0%BE%D1%82%D0%BE%D1%80%D1%8B%D0%B5+%D0%B8%D0%B7%D0%B2%D0%BB%D0%B5%D0%BA%D0%B0%D1%8E%D1%82+%D0%B7%D0%BD%D0%B0%D0%BD%D0%B8%D1%8F+%D0%B8%D0%B7+%D0%B4%D0%B0%D0%BD%D0%BD%D1%8B%D1%85&lg_topic=libgen&open=0&view=simple&res=25&phrase=0&column=def book]
| + | |
| − | ``Наука и искусство построения алгоритмов, которые извлекают знания из данных'', Петер Флах. On [http://www.machinelearning.ru machinelearning.ru]
| + | |
| − | you can find brief and clear definitions.
| + | |
