https://www.bibsonomy.org/tag/learning%20theoryBibSonomy RSS Feed for /tag/learning%20theoryBruce Hajek and Maxim Raginsky: Statistical Learning Theoryhttp://maxim.ece.illinois.edu/teaching/SLT/kirk862020-04-14T02:20:31+02:00course learning notes stats theory website <span itemprop="description">Bruce Hajek and Maxim Raginsky: Statistical Learning Theory</span>Statistical Machine Learning @ CMU by Ryan Tibshiranihttp://www.stat.cmu.edu/~ryantibs/statml/kirk862019-11-14T20:08:39+01:00course learning lecture notes stats theory <span itemprop="description">Statistical Machine Learning @ CMU by Ryan Tibshirani</span>Algorithmic Foundations of Learning 2018 - Oxford Universityhttp://www.stats.ox.ac.uk/~rebeschi/teaching/AFoL/18/kirk862019-11-14T17:56:15+01:00course learning lecture notes theory website <span itemprop="description">Algorithmic Foundations of Learning 2018 - Oxford University</span>Fall 2012: Learning Theory Course Materialhttps://cseweb.ucsd.edu/classes/fa12/cse291-b/kirk862019-11-14T13:44:23+01:00course learning lecture notes stats theory website <span itemprop="description">Fall 2012: Learning Theory Course Material</span>Introduction to Statistical Learning Theoryhttp://www.raetschlab.org/lectures/amsa/11-SLT.pdfkirk862019-08-03T21:06:54+02:00foundations learning mathematics probability stats theory <span itemprop="description">Introduction to Statistical Learning Theory</span>http://mr.crossref.org/iPage?doi=10.1561%2F2200000037kirk862019-06-17T01:23:59+02:00book learning theory <a itemprop="url" data-versiondate="2019-06-17T01:23:59+02:00" href="http://mr.crossref.org/iPage?doi=10.1561%2F2200000037" rel="nofollow" class="description-link">http://mr.crossref.org/iPage?doi=10.1561%2F2200000037</a>http://www.stevehanneke.com/kirk862019-06-17T01:19:04+02:00learning machine-learning theory website <a itemprop="url" data-versiondate="2019-06-17T01:19:04+02:00" href="http://www.stevehanneke.com/" rel="nofollow" class="description-link">http://www.stevehanneke.com/</a>http://mi.eng.cam.ac.uk/~cz277/doc/Slides-PAC.pdfkirk862019-06-13T14:31:23+02:00foundations learning theory <a itemprop="url" data-versiondate="2019-06-13T14:31:23+02:00" href="http://mi.eng.cam.ac.uk/~cz277/doc/Slides-PAC.pdf" rel="nofollow" class="description-link">http://mi.eng.cam.ac.uk/~cz277/doc/Slides-PAC.pdf</a>http://www.mit.edu/~9.520/fall18/#psetskirk862019-05-24T11:13:04+02:00bounds complexity compression course generalization learning sampling stats theory <a itemprop="url" data-versiondate="2019-05-24T11:13:04+02:00" href="http://www.mit.edu/~9.520/fall18/#psets" rel="nofollow" class="description-link">http://www.mit.edu/~9.520/fall18/#psets</a>https://cs.nyu.edu/~mohri/mlbook/kirk862019-05-20T02:12:28+02:00book bounds foundations generalization learning probability stats theory <a itemprop="url" data-versiondate="2019-05-20T02:12:28+02:00" href="https://cs.nyu.edu/~mohri/mlbook/" rel="nofollow" class="description-link">https://cs.nyu.edu/~mohri/mlbook/</a>https://people.eecs.berkeley.edu/~wainwrig/stat241b/kirk862019-04-29T05:37:38+02:00course learning stats theory <a itemprop="url" data-versiondate="2019-04-29T05:37:38+02:00" href="https://people.eecs.berkeley.edu/~wainwrig/stat241b/" rel="nofollow" class="description-link">https://people.eecs.berkeley.edu/~wainwrig/stat241b/</a>Statistical Learning Theory Sham Kakadehttp://stat.wharton.upenn.edu/~skakade/courses/stat928/kirk862019-04-29T05:36:43+02:00course learning stats theory <span itemprop="description">Statistical Learning Theory Sham Kakade</span>https://www.stat.berkeley.edu/~bartlett/courses/2014spring-cs281bstat241b/kirk862019-04-29T05:36:03+02:00course learning stats theory <a itemprop="url" data-versiondate="2019-04-29T05:36:03+02:00" href="https://www.stat.berkeley.edu/~bartlett/courses/2014spring-cs281bstat241b/" rel="nofollow" class="description-link">https://www.stat.berkeley.edu/~bartlett/courses/2014spring-cs281bstat241b/</a>Statistical Learning Theory Course from Tengyu Mahttps://web.stanford.edu/class/cs229t/kirk862019-04-29T05:35:32+02:00course learning stats theory <span itemprop="description">Statistical Learning Theory Course from Tengyu Ma</span>This course will give a detailed introduction to learning theory with a focus on the classification problem. It will be shown how to obtain (pobabilistic) bounds on the generalization error for certain types of algorithms. The main themes will be: * probabilistic inequalities and concentration inequalities * union bounds, chaining * measuring the size of a function class, Vapnik Chervonenkis dimension, shattering dimension and Rademacher averages * classification with real-valued functions  Some knowledge of probability theory would be helpful but not required since the main tools will be introduced.http://videolectures.net/mlss03_bousquet_slt/kirk862019-04-26T13:50:17+02:00bounds generalization learning mathematics probability stats theory <span itemprop="description">This course will give a detailed introduction to learning theory with a focus on the classification problem. It will be shown how to obtain (pobabilistic) bounds on the generalization error for certain types of algorithms. The main themes will be: * probabilistic inequalities and concentration inequalities * union bounds, chaining * measuring the size of a function class, Vapnik Chervonenkis dimension, shattering dimension and Rademacher averages * classification with real-valued functions  Some knowledge of probability theory would be helpful but not required since the main tools will be introduced.</span>https://howsheilaseesit.blog/2017/03/13/time-for-analytics-of-the-oppressed-my-starter-for-10-for-digifest-debate/georgeroberts2017-08-02T10:39:57+02:00analytics education higher learning social theory <a itemprop="url" data-versiondate="2017-08-02T10:39:57+02:00" href="https://howsheilaseesit.blog/2017/03/13/time-for-analytics-of-the-oppressed-my-starter-for-10-for-digifest-debate/" rel="nofollow" class="description-link">https://howsheilaseesit.blog/2017/03/13/time-for-analytics-of-the-oppressed-my-starter-for-10-for-digifest-debate/</a>https://journal.thriveglobal.com/how-technology-hijacks-peoples-minds-from-a-magician-and-google-s-design-ethicist-56d62ef5edf3georgeroberts2017-05-10T07:42:32+02:00culture design education higher learning marketing philosophy theory <a itemprop="url" data-versiondate="2017-05-10T07:42:32+02:00" href="https://journal.thriveglobal.com/how-technology-hijacks-peoples-minds-from-a-magician-and-google-s-design-ethicist-56d62ef5edf3" rel="nofollow" class="description-link">https://journal.thriveglobal.com/how-technology-hijacks-peoples-minds-from-a-magician-and-google-s-design-ethicist-56d62ef5edf3</a>http://www.businessballs.com/generations-nicknames-theories.htmgeorgeroberts2017-03-17T08:12:22+01:00learning theory <a itemprop="url" data-versiondate="2017-03-17T08:12:22+01:00" href="http://www.businessballs.com/generations-nicknames-theories.htm" rel="nofollow" class="description-link">http://www.businessballs.com/generations-nicknames-theories.htm</a>http://www.hdc.ed.ac.uk/georgeroberts2017-03-17T08:11:52+01:00education higher learning theory <a itemprop="url" data-versiondate="2017-03-17T08:11:52+01:00" href="http://www.hdc.ed.ac.uk/" rel="nofollow" class="description-link">http://www.hdc.ed.ac.uk/</a>https://www.theguardian.com/education/2017/mar/12/no-evidence-to-back-idea-of-learning-stylesgeorgeroberts2017-03-17T08:11:02+01:00learning styles theory <a itemprop="url" data-versiondate="2017-03-17T08:11:02+01:00" href="https://www.theguardian.com/education/2017/mar/12/no-evidence-to-back-idea-of-learning-styles" rel="nofollow" class="description-link">https://www.theguardian.com/education/2017/mar/12/no-evidence-to-back-idea-of-learning-styles</a>