https://www.bibsonomy.org/concept/tag/algorithmsBibSonomy RSS Feed for /concept/tag/algorithmshttps://www.adnews.com.au/opinion/please-explain-instagram-s-algorithms-and-unconscious-biasmartina352026-03-15T11:06:59+01:00unconscious algorithms bias instagram <a itemprop="url" data-versiondate="2026-03-15T11:06:59+01:00" href="https://www.adnews.com.au/opinion/please-explain-instagram-s-algorithms-and-unconscious-bias" rel="nofollow" class="description-link">https://www.adnews.com.au/opinion/please-explain-instagram-s-algorithms-and-unconscious-bias</a>Abstract page for arXiv paper 2508.09053: Behavioural Theory of Reflective Algorithms II: Reflective Parallel Algorithmshttps://arxiv.org/abs/2508.09053scch2026-01-19T08:07:25+01:00Algorithms Theory Behavioural Reflective <span itemprop="description">Abstract page for arXiv paper 2508.09053: Behavioural Theory of Reflective Algorithms II: Reflective Parallel Algorithms</span>This “journal-first” paper presents a summary of the behavioural theory of reflective sequential algorithms (RSAs), i.e. sequential algorithms that can modify their own behaviour. The theory comprises a set of language-independent postulates defining the...https://link.springer.com/chapter/10.1007/978-3-031-33163-3_18scch2025-07-07T08:09:43+02:00Algorithms Theory Behavioural Reflective <span itemprop="description">This “journal-first” paper presents a summary of the behavioural theory of reflective sequential algorithms (RSAs), i.e. sequential algorithms that can modify their own behaviour. The theory comprises a set of language-independent postulates defining the...</span>https://stars.library.ucf.edu/honorstheses/1086/nsurina2024-03-24T21:56:47+01:00hashtags tiktok algorithms <a itemprop="url" data-versiondate="2024-03-24T21:56:47+01:00" href="https://stars.library.ucf.edu/honorstheses/1086/" rel="nofollow" class="description-link">https://stars.library.ucf.edu/honorstheses/1086/</a>A very common workflow is to index some data based on its embeddings and then given a new query embedding retrieve the most similar examples with k-Nearest Neighbor search. For example, you can imagine embedding a large collection of papers by their abstracts and then given a new paper of interest retrieve the most similar papers to it. TLDR in my experience it ~always works better to use an SVM instead of kNN, if you can afford the slight computational hithttps://github.com/karpathy/randomfun/blob/master/knn_vs_svm.ipynbjil2023-11-15T16:18:31+01:00similar most svm ranking knn vector qa <span itemprop="description">A very common workflow is to index some data based on its embeddings and then given a new query embedding retrieve the most similar examples with k-Nearest Neighbor search. For example, you can imagine embedding a large collection of papers by their abstracts and then given a new paper of interest retrieve the most similar papers to it. TLDR in my experience it ~always works better to use an SVM instead of kNN, if you can afford the slight computational hit</span>https://www.sciencedirect.com/science/article/pii/S0167642322000971scch2023-09-18T15:48:03+02:00behavioural reflective algorithms sequential theory <a itemprop="url" data-versiondate="2023-09-18T15:48:03+02:00" href="https://www.sciencedirect.com/science/article/pii/S0167642322000971" rel="nofollow" class="description-link">https://www.sciencedirect.com/science/article/pii/S0167642322000971</a>https://gregorygundersen.com/blog/2020/02/04/bayesian-linear-regression/becker2022-12-13T14:44:45+01:00bayesian linear background bayes regression knowledge integration <a itemprop="url" data-versiondate="2022-12-13T14:44:45+01:00" href="https://gregorygundersen.com/blog/2020/02/04/bayesian-linear-regression/" rel="nofollow" class="description-link">https://gregorygundersen.com/blog/2020/02/04/bayesian-linear-regression/</a>SoLAR Spotlight–Conversations on LearningAnalyticshttps://soundcloud.com/user-916492194/episode-18-explainable-models-for-learning-analyticsereidt2022-10-23T11:52:53+02:00podcast SoLAR algorithms learninganalytics education explainableAI deployment modeldevelopment <span itemprop="description">SoLAR Spotlight–Conversations on LearningAnalytics</span>Marius Wehner und Lynn Schmodde von der Wirtschaftswissenschaftlichen Fakultät der Heinrich-Heine-Universität Düsseldorf berichten von ihrer Forschung zu Learning Analytics. Im Verbundprojekt LADi haben sie Diskriminierungspotenziale und Bias in den Algorithmen untersucht sowie die Wahrnehmung der Lernenden von Beurteilungen durch Learning Analytics. Interviewer in Folge 11 des DINItus Podcasts ist Erik Reidt vom ZIM/Multimediazentrum der HHU Düsseldorf.https://anchor.fm/dinitus/episodes/Learning-Analytics--Teil-1-e1kptkpereidt2022-07-24T11:19:49+02:00podcast assessment ethics edtech evidence algorithms bias learninganalytics highered research <span itemprop="description">Marius Wehner und Lynn Schmodde von der Wirtschaftswissenschaftlichen Fakultät der Heinrich-Heine-Universität Düsseldorf berichten von ihrer Forschung zu Learning Analytics. Im Verbundprojekt LADi haben sie Diskriminierungspotenziale und Bias in den Algorithmen untersucht sowie die Wahrnehmung der Lernenden von Beurteilungen durch Learning Analytics. Interviewer in Folge 11 des DINItus Podcasts ist Erik Reidt vom ZIM/Multimediazentrum der HHU Düsseldorf.</span>https://www.bayesrulesbook.com/bshanks2022-07-18T01:07:23+02:00textbook stats bayes probability <a itemprop="url" data-versiondate="2022-07-18T01:07:23+02:00" href="https://www.bayesrulesbook.com/" rel="nofollow" class="description-link">https://www.bayesrulesbook.com/</a>This episode is all about bias. Our hosts Maren Scheffel and Nia Dowel talk to Shamya Karumbaiah and Rene Kizilcec about bias in learning analytics and some of the work they are doing in that area.https://soundcloud.com/user-916492194/episode-16-biasereidt2022-06-19T11:16:01+02:00podcast edtech SoLAR algorithms bias learninganalytics education support <span itemprop="description">This episode is all about bias. Our hosts Maren Scheffel and Nia Dowel talk to Shamya Karumbaiah and Rene Kizilcec about bias in learning analytics and some of the work they are doing in that area.</span>Philosophical Disquisitions Friday, April 8, 2022https://philosophicaldisquisitions.blogspot.com/2022/04/how-can-algorithms-be-biased.htmlereidt2022-04-10T12:42:39+02:00framework fairness output algorithms bias learninganalytics artificialintelligence validation <span itemprop="description">Philosophical Disquisitions Friday, April 8, 2022</span>card_game yugioh crafting_system deck_building sortinghttps://www.pcgamer.com/yu-gi-oh-master-duel-review/amandavanjek2022-04-05T23:58:15+02:00sorting crafting_system yugioh deck_building card_game <span itemprop="description">card_game yugioh crafting_system deck_building sorting</span>Der Kurs vermittelt ein grundlegendes Verständnis für Machine Learning und den Umgang mit Algorithmen. Nach einem Einführungsteil auf der Basis inhaltlicher Wissensvermittlung, haben Sie intensiv die Möglichkeit, Kompetenzen durch forschendes Lernen und anhand realer Szenarien zu entwickeln.https://ki-campus.org/amaleaereidt2022-01-09T10:07:44+01:00MOOC practice algorithms machinelearning learninganalytics artificialintelligence <span itemprop="description">Der Kurs vermittelt ein grundlegendes Verständnis für Machine Learning und den Umgang mit Algorithmen. Nach einem Einführungsteil auf der Basis inhaltlicher Wissensvermittlung, haben Sie intensiv die Möglichkeit, Kompetenzen durch forschendes Lernen und anhand realer Szenarien zu entwickeln.</span>https://github.com/huawei-noah/HEBObecker2021-12-27T16:08:17+01:00huawei bayesian optimization bayes hebo <a itemprop="url" data-versiondate="2021-12-27T16:08:17+01:00" href="https://github.com/huawei-noah/HEBO" rel="nofollow" class="description-link">https://github.com/huawei-noah/HEBO</a>IWM-Lecture series - 7 Dec 2021https://www.slideshare.net/kverbert/towards-the-next-generation-of-interactive-and-adaptive-explanation-methods-250798434ereidt2021-12-12T11:43:29+01:00algorithms adaptiveinstruction evaluation interactivity slideshare learninganalytics recommender explainableAI <span itemprop="description">IWM-Lecture series - 7 Dec 2021</span>Jeroen Ooge, Gregor Stiglic, Katrien Verbert First published: 28 November 2021 https://doi.org/10.1002/widm.1427https://wires.onlinelibrary.wiley.com/doi/10.1002/widm.1427ereidt2021-12-05T12:50:51+01:00paper visualanalytics visualization algorithms learninganalytics decisionmaking artificialintelligence healthcare research <span itemprop="description">Jeroen Ooge, Gregor Stiglic, Katrien Verbert First published: 28 November 2021 https://doi.org/10.1002/widm.1427</span>Trade Unions are confronted with the need to go digital. We offer a tool and skills to responsibly collect data and build a data-powered campaign.https://www.fes.de/en/themenportal-gewerkschaften-und-gute-arbeit/international-trade-union-policy/articles-in-international-trade-union-policy/application-open-for-online-course-on-union-techmeneteqel2021-11-17T09:13:40+01:00algorithms union_organizing UnionTexh <span itemprop="description">Trade Unions are confronted with the need to go digital. We offer a tool and skills to responsibly collect data and build a data-powered campaign.</span>EdSurge | Jose Marichal on Nov 1, 2021https://www.edsurge.com/news/2021-11-01-teaching-students-to-make-good-choices-in-an-algorithm-driven-worldereidt2021-11-07T11:08:03+01:00ethics algorithms students machinelearning learninganalytics highered decisionmaking artificialintelligence <span itemprop="description">EdSurge | Jose Marichal on Nov 1, 2021</span>What if algorithms were used to tailor a more personalised course for each student? Alison Watson proposes a Netflix of Learning | 19/10/21https://wonkhe.com/blogs/how-netflix-and-skill-can-transform-higher-education/ereidt2021-10-24T12:41:24+02:00algorithms learninganalytics highered personalizedlearning skillsdevelopment transformation <span itemprop="description">What if algorithms were used to tailor a more personalised course for each student? Alison Watson proposes a Netflix of Learning | 19/10/21</span>