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Auswahl der wissenschaftlichen Literatur zum Thema „Online algorithm with advice“
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Zeitschriftenartikel zum Thema "Online algorithm with advice"
Lee, Russell, Jessica Maghakian, Mohammad Hajiesmaili, Jian Li, Ramesh Sitaraman und Zhenhua Liu. „Online peak-aware energy scheduling with untrusted advice“. ACM SIGEnergy Energy Informatics Review 1, Nr. 1 (November 2021): 59–77. http://dx.doi.org/10.1145/3508467.3508473.
Der volle Inhalt der QuelleBianchi, Maria Paola, Hans-Joachim Böckenhauer, Tatjana Brülisauer, Dennis Komm und Beatrice Palano. „Online Minimum Spanning Tree with Advice“. International Journal of Foundations of Computer Science 29, Nr. 04 (Juni 2018): 505–27. http://dx.doi.org/10.1142/s0129054118410034.
Der volle Inhalt der QuelleBoyar, Joan, Lene M. Favrholdt, Christian Kudahl, Kim S. Larsen und Jesper W. Mikkelsen. „Online Algorithms with Advice“. ACM Computing Surveys 50, Nr. 2 (19.06.2017): 1–34. http://dx.doi.org/10.1145/3056461.
Der volle Inhalt der QuelleBarrière, Lali, Xavier Muñoz, Janosch Fuchs und Walter Unger. „Online Matching in Regular Bipartite Graphs“. Parallel Processing Letters 28, Nr. 02 (Juni 2018): 1850008. http://dx.doi.org/10.1142/s0129626418500081.
Der volle Inhalt der QuelleChen, Li-Hsuan, Ling-Ju Hung, Henri Lotze und Peter Rossmanith. „Online Node- and Edge-Deletion Problems with Advice“. Algorithmica 83, Nr. 9 (30.06.2021): 2719–53. http://dx.doi.org/10.1007/s00453-021-00840-9.
Der volle Inhalt der QuelleLykouris, Thodoris, und Sergei Vassilvitskii. „Competitive Caching with Machine Learned Advice“. Journal of the ACM 68, Nr. 4 (07.07.2021): 1–25. http://dx.doi.org/10.1145/3447579.
Der volle Inhalt der QuelleBoyar, Joan, Lene M. Favrholdt, Christian Kudahl, Kim S. Larsen und Jesper W. Mikkelsen. „Online Algorithms with Advice: A Survey“. ACM SIGACT News 47, Nr. 3 (31.08.2016): 93–129. http://dx.doi.org/10.1145/2993749.2993766.
Der volle Inhalt der QuelleBöckenhauer, Hans-Joachim, Dennis Komm, Rastislav Královič, Richard Královič und Tobias Mömke. „Online algorithms with advice: The tape model“. Information and Computation 254 (Juni 2017): 59–83. http://dx.doi.org/10.1016/j.ic.2017.03.001.
Der volle Inhalt der QuelleAumayr, Erik, Jeffrey Chan und Conor Hayes. „Reconstruction of Threaded Conversations in Online Discussion Forums“. Proceedings of the International AAAI Conference on Web and Social Media 5, Nr. 1 (03.08.2021): 26–33. http://dx.doi.org/10.1609/icwsm.v5i1.14122.
Der volle Inhalt der QuelleZhao, Xiaofan, und Hong Shen. „Online algorithms for 2D bin packing with advice“. Neurocomputing 189 (Mai 2016): 25–32. http://dx.doi.org/10.1016/j.neucom.2015.11.035.
Der volle Inhalt der QuelleDissertationen zum Thema "Online algorithm with advice"
Renault, Marc Paul. „Lower and upper bounds for online algorithms with advice“. Paris 7, 2014. http://www.theses.fr/2014PA077196.
Der volle Inhalt der QuelleOnline algorithms operate in a setting where the input is revealed piece by piece; the pieces are called requests. After receiving each request, online algorithms must take an action before the next request is revealed, i. E. Online algorithms must make irrevocable decisions based on the input revealed so far without any knowledge of the future input. The goal is to optimize some cost function over the input. Competitive analysis is the standard method used to analyse the quality of online algorithms. The competitive ratio is the worst case ratio, over all valid finite request sequences, of the online algorithm's performance against an optimal offline algorithm for the same request sequence. The competitive ratio compares the performance of an algorithm with no knowledge about the future against an algorithm with full knowledge about the future. Since the complete absence of future knowledge is often not a reasonable assumption, models, termed online algorithms with advice, which give the online algorithms access to a quantified amount of future knowledge, have been proposed. The interest in this model is in examining how the competitive ratio changes as a function of the amount of advice. In this thesis, we present upper and lower bounds in the advice model for classical online problems such as the k-server problem, the bin packing problem, the dual bin packing (multiple knapsack) problem, scheduling problem on m identical machines, the reordering buffer management problem and the list update problem
Jin, Shendan. „Online computation beyond standard models“. Electronic Thesis or Diss., Sorbonne université, 2020. http://www.theses.fr/2020SORUS152.
Der volle Inhalt der QuelleIn the standard setting of online computation, the input is not entirely available from the beginning, but is revealed incrementally, piece by piece, as a sequence of requests. Whenever a request arrives, the online algorithm has to make immediately irrevocable decisions to serve the request, without knowledge on the future requests. Usually, the standard framework to evaluate the performance of online algorithms is competitive analysis, which compares the worst-case performance of an online algorithm to an offline optimal solution. In this thesis, we will study some new ways of looking at online problems. First, we study the online computation in the recourse model, in which the irrevocability on online decisions is relaxed. In other words, the online algorithm is allowed to go back and change previously made decisions. More precisely, we show how to identify the trade-off between the number of re-optimization and the performance of online algorithms for the online maximum matching problem. Moreover, we study measures other than competitive analysis for evaluating the performance of online algorithms. We observe that sometimes, competitive analysis cannot distinguish the performance of different algorithms due to the worst-case nature of the competitive ratio. We demonstrate that a similar situation arises in the linear search problem. More precisely, we revisit the linear search problem and introduce a measure, which can be applied as a refinement of the competitive ratio. Last, we study the online computation in the advice model, in which the algorithm receives as input not only a sequence of requests, but also some advice on the request sequence. Specifically, we study a recent model with untrusted advice, in which the advice can be either trusted or untrusted. Assume that in the latter case, the advice can be generated from a malicious source. We show how to identify a Pareto optimal strategy for the online bidding problem in the untrusted advice model
Cayuela, Rafols Marc. „Algorithmic Study on Prediction with Expert Advice : Study of 3 novel paradigms with Grouped Experts“. Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-254344.
Der volle Inhalt der QuelleHuvudarbetet för den här avhandlingen har varit en grundlig studie av den nya Prediction with Partially Monitored Grouped Expert Advice and Side Information paradigmet. Detta är nyligen föreslagit i denna avhandling, och det utökar det brett studerade Prediction with Expert Advice paradigmet. Förlängningen baseras på två antaganden och en begränsning som ändrar det ursprungliga problemet. Det första antagandet, Grouped, förutsätter att experterna är inbyggda i grupper. Det andra antagandet, Side Information, introducerar ytterligare information som kan användas för att i tid relatera förutsägelser med grupper. Slutligen innebär begränsningen, Partially Monitored, att gruppens förutsägelser endast är kända för en grupp i taget. Studien av detta paradigm innefattar utformningen av en komplett förutsägelsesalgoritm, beviset på en teoretisk bindning till det sämre fallet kumulativa ånger för en sådan algoritm och en experimentell utvärdering av algoritmen (bevisar förekomsten av fall där detta paradigm överträffar Prediction with Expert Advice). Eftersom algoritmens utveckling är konstruktiv tillåter den dessutom att enkelt bygga två ytterligare prediksionsalgoritmer för Prediction with Grouped Expert Advice och Prediction with Grouped Expert Advice and Side Information paradigmer. Därför presenterar denna avhandling tre nya prediktionsalgoritmer med motsvarande ångergränser och en jämförande experimentell utvärdering inklusive det ursprungliga Prediction with Expert Advice paradigmet.
Henke, Hans-Christian. „Online Advice : Konzeption eines ergebnisbasierten Simulationsansatzes /“. [S.l. : s.n.], 2003. http://www.gbv.de/dms/zbw/362397171.pdf.
Der volle Inhalt der QuelleFurkin, Jennifer D. „MOM TO MOM: ONLINE BREASTFEEDING ADVICE“. UKnowledge, 2018. https://uknowledge.uky.edu/comm_etds/64.
Der volle Inhalt der QuellePorter, Noriko. „Japanese and U. S. mother's concerns and experts' advice content analysis of mothers' questions on online message boards and experts' advice in parenting magazines /“. Diss., Columbia, Mo. : University of Missouri-Columbia, 2008. http://hdl.handle.net/10355/5517.
Der volle Inhalt der QuelleThe entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file (viewed on June 15, 2009) Vita. Includes bibliographical references.
Fowler-Dawson, Amy E. „Expand your online reach with these 10 social media tips from the pros: An analysis of online social networking advice“. OpenSIUC, 2016. https://opensiuc.lib.siu.edu/theses/2047.
Der volle Inhalt der QuelleBarbaro, Billy. „Tuning Hyperparameters for Online Learning“. Case Western Reserve University School of Graduate Studies / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=case1522419008006144.
Der volle Inhalt der QuelleMurphy, Nicholas John. „An online learning algorithm for technical trading“. Master's thesis, Faculty of Science, 2019. http://hdl.handle.net/11427/31048.
Der volle Inhalt der QuelleOrlansky, Emily. „Beauty is in the mouth of the beholder advice networks at Haverford College /“. Diss., Connect to the thesis, 2009. http://hdl.handle.net/10066/3707.
Der volle Inhalt der QuelleBücher zum Thema "Online algorithm with advice"
Kienholz, Michelle. Online guide to medical research: Valuable internet resources for medical research, practice & advice. San Jose, CA: Ventana, 1999.
Den vollen Inhalt der Quelle findenMoore, Alexis. Cyber self-defense: Expert advice to avoid online predators, identity theft, and cyberbullying. Guilford, Connecticut: Lyons Press, 2014.
Den vollen Inhalt der Quelle findenThe weblog handbook: Practical advice on creating and maintaining your blog. Cambridge, MA: Perseus Pub., 2002.
Den vollen Inhalt der Quelle findenJohn, Yate Martin, Hrsg. Knock 'em dead résumés: Smart advice to make your online and paper résumés more productive. 8. Aufl. Avon, Mass: Adams Media, 2008.
Den vollen Inhalt der Quelle findenPauline, David, Hrsg. Your personal net doctor: Your guide to health and medical advice on the Internet and online services. New York: Wolff New Media, 1996.
Den vollen Inhalt der Quelle findenTwitter marketing tips: 3 surprisingly powerful tips to make Twitter pay off with no costs upfront and much more : 101 world class expert facts, hints, tips and advice on Twitter. Brisbane, Australia]: [Emereo], 2009.
Den vollen Inhalt der Quelle findenPrice, Joan. The insider's guide to internet health searches: Real-life success stories and expert advice for finding online health information you can trust. Emmaus, PA: Rodale Press, 2002.
Den vollen Inhalt der Quelle findenGiuseppe, Persiano, und SpringerLink (Online service), Hrsg. Approximation and Online Algorithms: 9th International Workshop, WAOA 2011, Saarbrücken, Germany, September 8-9, 2011, Revised Selected Papers. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.
Den vollen Inhalt der Quelle findenErlebach, Thomas. Approximation and Online Algorithms: 10th International Workshop, WAOA 2012, Ljubljana, Slovenia, September 13-14, 2012, Revised Selected Papers. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013.
Den vollen Inhalt der Quelle findenBolles, Mark Emery. Job-hunting online: A guide to job listings, message boards, research sites, the UnderWeb, counseling, networking, self-assessment tools, niche sites. 5. Aufl. Berkeley: Ten Speed Press, 2008.
Den vollen Inhalt der Quelle findenBuchteile zum Thema "Online algorithm with advice"
Borodin, Allan, Joan Boyar, Kim S. Larsen und Denis Pankratov. „Advice Complexity of Priority Algorithms“. In Approximation and Online Algorithms, 69–86. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-04693-4_5.
Der volle Inhalt der QuelleAdamaszek, Anna, Marc P. Renault, Adi Rosén und Rob van Stee. „Reordering Buffer Management with Advice“. In Approximation and Online Algorithms, 132–43. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-08001-7_12.
Der volle Inhalt der QuelleChrist, Marie G., Lene M. Favrholdt und Kim S. Larsen. „Online Multi-Coloring with Advice“. In Approximation and Online Algorithms, 83–94. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-18263-6_8.
Der volle Inhalt der QuelleBöckenhauer, Hans-Joachim, Janosch Fuchs und Walter Unger. „Exploring Sparse Graphs with Advice (Extended Abstract)“. In Approximation and Online Algorithms, 102–17. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-04693-4_7.
Der volle Inhalt der QuelleBöckenhauer, Hans-Joachim, Dennis Komm und Raphael Wegner. „Call Admission Problems on Grids with Advice (Extended Abstract)“. In Approximation and Online Algorithms, 118–33. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-04693-4_8.
Der volle Inhalt der QuelleDobrev, Stefan, Rastislav Královič und Richard Královič. „Independent Set with Advice: The Impact of Graph Knowledge“. In Approximation and Online Algorithms, 2–15. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-38016-7_2.
Der volle Inhalt der QuelleBöckenhauer, Hans-Joachim, Dennis Komm, Rastislav Královič, Richard Královič und Tobias Mömke. „On the Advice Complexity of Online Problems“. In Algorithms and Computation, 331–40. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-10631-6_35.
Der volle Inhalt der QuelleRenault, Marc P., und Adi Rosén. „On Online Algorithms with Advice for the k-Server Problem“. In Approximation and Online Algorithms, 198–210. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-29116-6_17.
Der volle Inhalt der QuelleRohatgi, Dhruv. „Near-Optimal Bounds for Online Caching with Machine Learned Advice“. In Proceedings of the Fourteenth Annual ACM-SIAM Symposium on Discrete Algorithms, 1834–45. Philadelphia, PA: Society for Industrial and Applied Mathematics, 2020. http://dx.doi.org/10.1137/1.9781611975994.112.
Der volle Inhalt der QuelleAdamy, Udo, Thomas Erlebach, Dieter Mitsche, Ingo Schurr, Bettina Speckmann und Emo Welzl. „Off-line Admission Control for Advance Reservations in Star Networks“. In Approximation and Online Algorithms, 211–24. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/978-3-540-31833-0_18.
Der volle Inhalt der QuelleKonferenzberichte zum Thema "Online algorithm with advice"
Zhao, Xiaofan, Xin Li und Hong Shen. „Improved Online Algorithms for One-Dimensional BinPacking with Advice“. In 2017 18th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT). IEEE, 2017. http://dx.doi.org/10.1109/pdcat.2017.00042.
Der volle Inhalt der QuelleCreveling, Jessica, und Cedric Hagen. „COMBINING A δ13CCARB CORRELATION ALGORITHM AND A REFINED RADIOMETRIC CHRONOLOGY TO ADVANCE PRECAMBRIAN (EDIACARAN) BASIN ANALYSIS“. In GSA 2020 Connects Online. Geological Society of America, 2020. http://dx.doi.org/10.1130/abs/2020am-355524.
Der volle Inhalt der QuelleVaidya, Nupur D., Yogesh A. Suryawanshi und Manish Chavan. „Design for enhancing the performance of Advance Encryption Standard algorithm VHDL“. In 2016 Online International Conference on Green Engineering and Technologies (IC-GET). IEEE, 2016. http://dx.doi.org/10.1109/get.2016.7916849.
Der volle Inhalt der QuelleGanapathi Subramanian, Sriram, Matthew E. Taylor, Kate Larson und Mark Crowley. „Multi-Agent Advisor Q-Learning (Extended Abstract)“. In Thirty-Second International Joint Conference on Artificial Intelligence {IJCAI-23}. California: International Joint Conferences on Artificial Intelligence Organization, 2023. http://dx.doi.org/10.24963/ijcai.2023/776.
Der volle Inhalt der QuelleHikima, Yuya, Yasunori Akagi, Naoki Marumo und Hideaki Kim. „Online Matching with Controllable Rewards and Arrival Probabilities“. In Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}. California: International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/ijcai.2022/254.
Der volle Inhalt der QuelleNirala, C. K., und P. Saha. „Development of an algorithm for online pulse discrimination in micro-EDM using current and voltage sensors and their comparison“. In 2015 IEEE International Advance Computing Conference (IACC). IEEE, 2015. http://dx.doi.org/10.1109/iadcc.2015.7154758.
Der volle Inhalt der QuelleSivagnanam, Amutheezan, Salah Uddin Kadir, Ayan Mukhopadhyay, Philip Pugliese, Abhishek Dubey, Samitha Samaranayake und Aron Laszka. „Offline Vehicle Routing Problem with Online Bookings: A Novel Problem Formulation with Applications to Paratransit“. In Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}. California: International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/ijcai.2022/546.
Der volle Inhalt der QuelleCai, Xia. „Vector Autoregressive Weighting Reversion Strategy for Online Portfolio Selection“. In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/616.
Der volle Inhalt der QuelleZhu, Yada, Jianbo Li, Jingrui He, Brian L. Quanz und Ajay A. Deshpande. „A Local Algorithm for Product Return Prediction in E-Commerce“. In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/517.
Der volle Inhalt der QuelleZenun Franco, Rodrigo. „Online Recommender System for Personalized Nutrition Advice“. In RecSys '17: Eleventh ACM Conference on Recommender Systems. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3109859.3109862.
Der volle Inhalt der QuelleBerichte der Organisationen zum Thema "Online algorithm with advice"
Balman, Mehmet, und Tevfik Kosar. An Online Scheduling Algorithm with Advance Reservation for Large-Scale Data Transfers. Office of Scientific and Technical Information (OSTI), Mai 2010. http://dx.doi.org/10.2172/1050437.
Der volle Inhalt der QuelleSantesson, S., und P. Hallam-Baker. Online Certificate Status Protocol Algorithm Agility. RFC Editor, Juni 2011. http://dx.doi.org/10.17487/rfc6277.
Der volle Inhalt der QuelleStreeter, Matthew, und Daniel Golovin. An Online Algorithm for Maximizing Submodular Functions. Fort Belvoir, VA: Defense Technical Information Center, Dezember 2007. http://dx.doi.org/10.21236/ada476748.
Der volle Inhalt der QuelleMeeker, Jessica. Mutual Learning for Policy Impact: Insights from CORE. Shaping Policy and Practice with Intersectional Gender Responsive Evidence (in the Context of Covid-19). Institute of Development Studies (IDS), November 2021. http://dx.doi.org/10.19088/core.2021.007.
Der volle Inhalt der QuelleSchmidt-Sane, Megan, Tabitha Hrynick, Erica Nelson und Tom Barker. Mutual Learning for Policy Impact: Insights from CORE. Adapting research methods in the context of Covid-19. Institute of Development Studies (IDS), Dezember 2021. http://dx.doi.org/10.19088/core.2021.008.
Der volle Inhalt der QuelleMeeker, Jessica. Mutual Learning for Policy Impact: Insights from CORE. Sharing Experience and Learning on Approaches to Influence Policy and Practice. Institute of Development Studies (IDS), August 2021. http://dx.doi.org/10.19088/core.2021.005.
Der volle Inhalt der QuelleTidd, Alexander N., Richard A. Ayers, Grant P. Course und Guy R. Pasco. Scottish Inshore Fisheries Integrated Data System (SIFIDS): work package 6 final report development of a pilot relational data resource for the collation and interpretation of inshore fisheries data. Herausgegeben von Mark James und Hannah Ladd-Jones. Marine Alliance for Science and Technology for Scotland (MASTS), 2019. http://dx.doi.org/10.15664/10023.23452.
Der volle Inhalt der QuelleGertler, Paul, Sebastian Martinez, Laura B. Rawlings, Patrick Premand und Christel M. J. Vermeersch. Impact Evaluation in Practice: Second Edition. Inter-American Development Bank, September 2016. http://dx.doi.org/10.18235/0006529.
Der volle Inhalt der QuelleMilek, Karen, und Richard Jones, Hrsg. Science in Scottish Archaeology: ScARF Panel Report. Society of Antiquaries of Scotland, September 2012. http://dx.doi.org/10.9750/scarf.06.2012.193.
Der volle Inhalt der QuellePaule, Bernard, Flourentzos Flourentzou, Tristan de KERCHOVE d’EXAERDE, Julien BOUTILLIER und Nicolo Ferrari. PRELUDE Roadmap for Building Renovation: set of rules for renovation actions to optimize building energy performance. Department of the Built Environment, 2023. http://dx.doi.org/10.54337/aau541614638.
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