{"id":16223,"date":"2022-08-22T10:52:00","date_gmt":"2022-08-22T10:52:00","guid":{"rendered":"https:\/\/direc.dk\/online-algorithms-with-predictions\/"},"modified":"2025-10-20T13:41:53","modified_gmt":"2025-10-20T13:41:53","slug":"online-algorithms-with-predictions","status":"publish","type":"post","link":"https:\/\/direc.dk\/da\/online-algorithms-with-predictions\/","title":{"rendered":"Online Algorithms with Predictions"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"16223\" class=\"elementor elementor-16223 elementor-16186\" data-elementor-post-type=\"post\">\n\t\t\t\t\t\t<section data-particle_enable=\"false\" data-particle-mobile-disabled=\"false\" class=\"elementor-section elementor-top-section elementor-element elementor-element-58f5a022 elementor-section-height-min-height elementor-section-items-stretch elementor-section-content-middle elementor-reverse-mobile elementor-reverse-tablet elementor-section-full_width elementor-section-height-default\" data-id=\"58f5a022\" data-element_type=\"section\" data-e-type=\"section\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;,&quot;shape_divider_bottom&quot;:&quot;triangle&quot;,&quot;shape_divider_bottom_negative&quot;:&quot;yes&quot;,&quot;jet_parallax_layout_list&quot;:[]}\">\n\t\t\t\t\t\t\t<div class=\"elementor-background-overlay\"><\/div>\n\t\t\t\t\t\t<div class=\"elementor-shape elementor-shape-bottom\" aria-hidden=\"true\" data-negative=\"true\">\n\t\t\t<svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" viewBox=\"0 0 1000 100\" preserveAspectRatio=\"none\">\n\t<path class=\"elementor-shape-fill\" d=\"M500.2,94.7L0,0v100h1000V0L500.2,94.7z\"\/>\n<\/svg>\t\t<\/div>\n\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-no\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-5683f221\" data-id=\"5683f221\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<section data-particle_enable=\"false\" data-particle-mobile-disabled=\"false\" class=\"elementor-section elementor-inner-section elementor-element elementor-element-79347e75 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"79347e75\" data-element_type=\"section\" data-e-type=\"section\" data-settings=\"{&quot;jet_parallax_layout_list&quot;:[]}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-50 elementor-inner-column elementor-element elementor-element-72893b05\" data-id=\"72893b05\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-1d49d184 elementor-widget elementor-widget-heading\" data-id=\"1d49d184\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">DIREC-projekt<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-fdf51f animated-fast elementor-invisible elementor-widget elementor-widget-heading\" data-id=\"fdf51f\" data-element_type=\"widget\" data-e-type=\"widget\" data-settings=\"{&quot;_animation&quot;:&quot;fadeIn&quot;}\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h1 class=\"elementor-heading-title elementor-size-default\">Online algorithms with predictions<\/h1>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"elementor-column elementor-col-50 elementor-inner-column elementor-element elementor-element-386eb106\" data-id=\"386eb106\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap\">\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section data-particle_enable=\"false\" data-particle-mobile-disabled=\"false\" class=\"elementor-section elementor-top-section elementor-element elementor-element-3a849ee9 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"3a849ee9\" data-element_type=\"section\" data-e-type=\"section\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;,&quot;jet_parallax_layout_list&quot;:[]}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-50 elementor-top-column elementor-element elementor-element-28ee5ebf\" data-id=\"28ee5ebf\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-6beaf999 elementor-widget elementor-widget-heading\" data-id=\"6beaf999\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h4 class=\"elementor-heading-title elementor-size-default\">Resum\u00e9<\/h4>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"elementor-column elementor-col-50 elementor-top-column elementor-element elementor-element-36645a20\" data-id=\"36645a20\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-6b5bc281 elementor-widget elementor-widget-text-editor\" data-id=\"6b5bc281\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Industrisektoren st\u00e5r over for optimeringsudfordringer med hensyn til ressourceeffektivitet, som kan l\u00f8ses ved hj\u00e6lp af online-algoritmer, der skal tr\u00e6ffe beslutninger med delvis information. Mens maskinl\u00e6ring kan levere effektive l\u00f8sninger baseret p\u00e5 typiske data, kan den fejle med uforudsete input. Derfor er en hybrid tilgang, der kombinerer garantierne fra online-algoritmer med maskinl\u00e6ringsforudsigelser, n\u00f8dvendig. Dette sikrer, at sikre beslutninger overtrumfer risikable forudsigelser og kvantificerer l\u00f8sningskvaliteten i forhold til forudsigelsesn\u00f8jagtigheden for at h\u00e5ndtere risici og forhindre fejl.<\/p>\n<p><strong>Projektperiode:<\/strong> 2022-2025<br \/><strong>Budget:<\/strong> 3,5 millioner kr<\/p>\n<p><strong>Projektleder<\/strong><\/p>\n<ul>\n<li>Professor Kim Skak Larsen<\/li>\n<li>Department of Mathematics and Computer Science, SDU<\/li>\n<li>kslarsen@imada.sdu.dk<\/li>\n<\/ul>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-4510e62d elementor-widget elementor-widget-toggle\" data-id=\"4510e62d\" data-element_type=\"widget\" data-e-type=\"widget\" data-settings=\"{&quot;_animation&quot;:&quot;none&quot;}\" data-widget_type=\"toggle.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-toggle\">\n\t\t\t\t\t\t\t<div class=\"elementor-toggle-item\">\n\t\t\t\t\t<div id=\"elementor-tab-title-1151\" class=\"elementor-tab-title\" data-tab=\"1\" role=\"button\" aria-controls=\"elementor-tab-content-1151\" aria-expanded=\"false\">\n\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-toggle-icon elementor-toggle-icon-left\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-toggle-icon-closed\"><i class=\"fas fa-caret-right\"><\/i><\/span>\n\t\t\t\t\t\t\t\t<span class=\"elementor-toggle-icon-opened\"><i class=\"elementor-toggle-icon-opened fas fa-caret-up\"><\/i><\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t<a class=\"elementor-toggle-title\" tabindex=\"0\">Mere info (p\u00e5 engelsk)<\/a>\n\t\t\t\t\t<\/div>\n\n\t\t\t\t\t<div id=\"elementor-tab-content-1151\" class=\"elementor-tab-content elementor-clearfix\" data-tab=\"1\" role=\"region\" aria-labelledby=\"elementor-tab-title-1151\"><p>All industrial sectors face optimization problems, and usually many of them, i.e., situations where one must optimize wrt. some resource. This could be minimizing material usage or it could be optimizing towards time or space consumption. Examples include cutting shapes from expensive material, packing containers best possibly to minimize transportation costs, or scheduling routes or dependent tasks to finish earliest possible.<\/p>\n<p>In some cases, all information is available when the processing of tasks commences, but in many situations, tasks arrive during the process, and decisions regarding their treatment must be made shortly after their arrival before further tasks appear. Such problems are referred to as \u201conline\u201d. Online problems lead to poorer solutions than one can obtain with their offline counterparts unless fairly precise, additional information about future tasks is available. In designing and analyzing algorithms, in general, the goal is to determine the quality of an algorithmic solution, preferably with guarantees on performance for all inputs, so that it is possible to promise delivery times or bounds on expenses, etc. Such an analysis also allows the designer to determine if it would be beneficial to search for other algorithmic solutions. Assessing the quality of the algorithms experimentally suffers from the difficulty of determining which inputs to test on and providing trustworthy worst-case bounds.<\/p>\n<p>The area of online algorithms has existed for many years and provides analyses giving worst-case guarantees. However, since these guarantees hold for all inputs, even the most extreme and, sometimes, unrealistic, these guarantees are very pessimistic and often not suited for choosing good algorithms for the typical cases. Thus, in practice, companies often use techniques based on heuristic methods, machine learning, etc. Machine learning, especially, has proven very successful in many applications in providing solutions that are good in practice, when presented with typical inputs. However, on input not captured by training data, the algorithm may fail dramatically.<\/p>\n<p>We need combinations of the desirable properties of guarantees from the online algorithms world and of the experienced good behavior on typical input from, for instance, the machine learning world. That is, we need algorithms that follow predictions given from a machine learning component, for instance, since that often gives good results, but it should not do so blindly or the worst-case behavior will generally be even worse than the guarantees provided by standard online algorithms and their analyses. Thus, a controlling algorithmic unit should monitor the predictions that are given so that safety decisions can overrule the predictions when things are progressing in a worrisome direction.<\/p>\n<p>We also need ways of quantifying the guaranteed quality of our solutions as a function of how closely an input resembles the predicted (by a machine learning component, for instance) input. This is a crucial part of risk management. We want reassurance that we do not \u201cfall off the cliff\u201d just because predictions are slightly off. This includes limiting the \u201ddamage\u201d possible from machine learning adversarial attacks. As an integral part of a successful approach to this problem, we need measures developed to quantify an input\u2019s distance from the prediction (the prediction error) that are defined in such a manner that quality can be expressed as a function of the prediction error. For online algorithm applications, this often needs to be different from standard loss functions for machine learning.<\/p>\n<p><strong>Research problem and aims<\/strong><\/p>\n<p>Our main aim is to further the development of generally-applicable techniques for utilizing usually good, but untrusted predictions, while at the same time providing worst-case guarantees, in the realm of online optimization problems. We want to further establish this research topic at Danish universities and subsequently disseminate knowledge of this to the industry via collaboration. Developments of this nature are of course considered internationally. Progress is to a large extent made by considering carefully chosen concrete problems, their modeling and properties, and extract general techniques from those studies, and further test their applicability on new problems.<\/p>\n<p>We are planning to initiate work on online call control and scheduling with precedence constraints. The rationale is that these problems are important in their own right and at the same type represent different types of challenges. Call control focuses on admitting as many requests as possible with limited bandwidth, whereas scheduling focuses on time, handling all requests as effectively as possible.<\/p>\n<p>Call control can be seen as point-to-point requests in a network with limited capacity. The goal is to accept as profitable a collection of requests as possible. Scheduling deals with jobs of different duration that must be executed on some \u201cmachine\u201d (not necessarily a computer), respecting some constraints that some jobs cannot be executed before certain other jobs are completed. In this problem, all jobs must be scheduled on some machine, and the target is to complete all jobs as fast as possible. To fully define these problems more details are required about the structure of the resources and the precise optimization goals.<\/p>\n<p>Some generic insight we would like to gain and which is sorely lacking in the community currently is formalizable conditions for good predictions. We want the performance of algorithms to degrade gracefully with prediction errors. This is important for the explainability and trustworthiness of algorithms. Related to this, whereas some predictions may be easy to work with theoretically, it is important to focus on classes of predictions that are learnable in practice. To be useful, this also requires robustness, in the sense that minor, inconsequential changes in the input sequence compared with the prediction should not affect the result dramatically.<br \/>We are also interested in giving minor consideration to impossibility results, i.e., proving limits on how good solutions can be obtained. Whereas this is not directly constructive, it can tell us if we are done or how close we are to an optimal algorithm, so we do not waste time trying to improve algorithms that cannot be improved or only improved marginally.<\/p>\n<p><strong>Value creation<\/strong><\/p>\n<p>The project leads to value creation in a number of different directions.<\/p>\n<p>Research-wise, with the developments in machine learning and related data science disciplines over the last years, the integration and utilization of these techniques into other areas of computer science is of great interest, and Danish research should be at the forefront of these endeavors. We facilitate this by bringing people with expertise in different topics together and consolidating knowledge of the primary techniques across institutions. Educating students in these topics is usually a nice side-effect of running such a project. The primary focus, of course, is to educate the PhD student and train the research assistants, but this is accompanied by having MS students working on their theses during the project period solve related, well-defined subproblems.<\/p>\n<p>We are advocating the combined techniques that strive towards excellent typical-case performance while providing worst-case guarantees, and believe that they should be adopted by industry to a larger extent. The project will lead to results on concrete problems, but our experience tells us that companies generally need variations of these or new solutions to somewhat different problems. Thus, the most important aspect in this regards is capacity building, so that we can assist with concrete developments for particular companyspecific problems. Other than the fact that problems appear in many variations in different companies, a main reason why problem adaption would often be necessary is that the added value of the combined algorithmic approaches is based on predictions. And it varies greatly in what type of data is obtainable and which subset of the data can give useful predictions.<\/p>\n<p>We have prior experience with industry consulting, the industrial PhD program, and co-advised MS students, and maintain close relationships with local industry. After, and in principle also during, this project, we are open to subsequent joint projects with industry that take their challenges as the starting point, whereafter we utilize the know-how and experience gained from the current project. Work such as that could be on a consultancy basis, through a joint student project, or, at a larger scale, with, for instance, the Innovation Foundation as a partner.<\/p>\n<p>Finally, we see it as an advantage in our project that we include researchers who are relatively new to Denmark such that they get to interact with more people at different institutions and expand their Danish network.<\/p>\n<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section data-particle_enable=\"false\" data-particle-mobile-disabled=\"false\" class=\"elementor-section elementor-top-section elementor-element elementor-element-508e0424 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"508e0424\" data-element_type=\"section\" data-e-type=\"section\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;,&quot;jet_parallax_layout_list&quot;:[]}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-50 elementor-top-column elementor-element elementor-element-3d273c9b\" data-id=\"3d273c9b\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-1cc89402 elementor-widget elementor-widget-heading\" data-id=\"1cc89402\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h4 class=\"elementor-heading-title elementor-size-default\">V\u00e6rdi<\/h4>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"elementor-column elementor-col-50 elementor-top-column elementor-element elementor-element-2b667004\" data-id=\"2b667004\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-423f0218 elementor-widget elementor-widget-text-editor\" data-id=\"423f0218\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Projektet sigter mod at lede integrationen af maskinl\u00e6ring med andre omr\u00e5der inden for datalogi ved at samle eksperter, konsolidere viden p\u00e5 tv\u00e6rs af institutioner og uddanne ph.d.-studerende og kandidatstuderende gennem samarbejdsprojekter.<\/p>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t<div data-particle_enable=\"false\" data-particle-mobile-disabled=\"false\" class=\"elementor-element elementor-element-a0b9a5e e-flex e-con-boxed e-con e-parent\" data-id=\"a0b9a5e\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;jet_parallax_layout_list&quot;:[]}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-c7510ad elementor-widget-divider--view-line elementor-widget elementor-widget-divider\" data-id=\"c7510ad\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"divider.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-divider\">\n\t\t\t<span class=\"elementor-divider-separator\">\n\t\t\t\t\t\t<\/span>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<section data-particle_enable=\"false\" data-particle-mobile-disabled=\"false\" class=\"elementor-section elementor-top-section elementor-element elementor-element-465361d6 elementor-section-height-min-height elementor-section-items-stretch elementor-section-content-middle elementor-reverse-mobile elementor-reverse-tablet elementor-section-stretched elementor-section-boxed elementor-section-height-default\" data-id=\"465361d6\" data-element_type=\"section\" data-e-type=\"section\" data-settings=\"{&quot;stretch_section&quot;:&quot;section-stretched&quot;,&quot;jet_parallax_layout_list&quot;:[]}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-no\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-346f9445\" data-id=\"346f9445\" data-element_type=\"column\" data-e-type=\"column\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t<div class=\"elementor-background-overlay\"><\/div>\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-7ad14b8 animated-fast elementor-invisible elementor-widget elementor-widget-heading\" data-id=\"7ad14b8\" data-element_type=\"widget\" data-e-type=\"widget\" data-settings=\"{&quot;_animation&quot;:&quot;fadeIn&quot;}\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Partnere<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<section data-particle_enable=\"false\" data-particle-mobile-disabled=\"false\" class=\"elementor-section elementor-inner-section elementor-element elementor-element-1870119b elementor-section-content-top elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"1870119b\" data-element_type=\"section\" data-e-type=\"section\" data-settings=\"{&quot;jet_parallax_layout_list&quot;:[]}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-25 elementor-inner-column elementor-element elementor-element-6f7aa7fe\" 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height=\"352\" src=\"https:\/\/direc.dk\/wp-content\/uploads\/2021\/08\/SDU-logo-tekst_DK-1024x451.png\" class=\"attachment-large size-large wp-image-5977\" alt=\"\" srcset=\"https:\/\/direc.dk\/wp-content\/uploads\/2021\/08\/SDU-logo-tekst_DK-1024x451.png 1024w, https:\/\/direc.dk\/wp-content\/uploads\/2021\/08\/SDU-logo-tekst_DK-300x132.png 300w, https:\/\/direc.dk\/wp-content\/uploads\/2021\/08\/SDU-logo-tekst_DK-768x338.png 768w, https:\/\/direc.dk\/wp-content\/uploads\/2021\/08\/SDU-logo-tekst_DK-1200x529.png 1200w, https:\/\/direc.dk\/wp-content\/uploads\/2021\/08\/SDU-logo-tekst_DK.png 1353w\" sizes=\"(max-width: 800px) 100vw, 800px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"elementor-column elementor-col-25 elementor-inner-column elementor-element elementor-element-597211c0\" data-id=\"597211c0\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap\">\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"elementor-column elementor-col-25 elementor-inner-column elementor-element elementor-element-270eba47\" data-id=\"270eba47\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap\">\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>Vores fokus er p\u00e5 at forbedre optimeringsalgoritmer i online beslutningstagning. Ved at anvende teknikker fra online algoritmer til l\u00f8sning af optimeringsproblemer kan vi give garantier for v\u00e6rst t\u00e6nkelige scenarier, men den normale (gennemsnitlige) adf\u00e6rd kan v\u00e6re utilfredsstillende. Ved hj\u00e6lp af teknikker fra maskinl\u00e6ring kan vi ofte opn\u00e5 god adf\u00e6rd i praksis, men garantier mangler, is\u00e6r for situationer, der ikke er d\u00e6kket af tr\u00e6ningsdataene. Vi sigter mod at kombinere de bedste egenskaber fra disse to omr\u00e5der.<\/p>\n","protected":false},"author":3,"featured_media":29800,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[212,218,34,215],"tags":[79],"class_list":["post-16223","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-dataanalyse-og-algoritmer","category-projekt","category-scitech-projekt","category-uddannelse-og-kapacitetsopbygning","tag-ws4-da"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.8 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Online Algorithms with Predictions - DIREC<\/title>\n<meta name=\"description\" content=\"The mobility of people and things is an important societal process that facilitates and affects the lives of most people. 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