Relevant bibliographies by topics / Online algorithm with advice

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Online algorithm with advice'

Author: Grafiati
Published: 25 May 2024
Last updated: 31 July 2025

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Journal articles on the topic "Online algorithm with advice"

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Lee, Russell, Jessica Maghakian, Mohammad Hajiesmaili, Jian Li, Ramesh Sitaraman, and Zhenhua Liu. "Online peak-aware energy scheduling with untrusted advice." ACM SIGEnergy Energy Informatics Review 1, no. 1 (2021): 59–77. http://dx.doi.org/10.1145/3508467.3508473.

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This paper studies the online energy scheduling problem in a hybrid model where the cost of energy is proportional to both the volume and peak usage, and where energy can be either locally generated or drawn from the grid. Inspired by recent advances in online algorithms with Machine Learned (ML) advice, we develop parameterized deterministic and randomized algorithms for this problem such that the level of reliance on the advice can be adjusted by a trust parameter. We then analyze the performance of the proposed algorithms using two performance metrics: robustness that measures the competiti
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Bianchi, Maria Paola, Hans-Joachim Böckenhauer, Tatjana Brülisauer, Dennis Komm, and Beatrice Palano. "Online Minimum Spanning Tree with Advice." International Journal of Foundations of Computer Science 29, no. 04 (2018): 505–27. http://dx.doi.org/10.1142/s0129054118410034.

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In the online minimum spanning tree problem, a graph is revealed vertex by vertex; together with every vertex, all edges to vertices that are already known are given, and an online algorithm must irrevocably choose a subset of them as a part of its solution. The advice complexity of an online problem is a means to quantify the information that needs to be extracted from the input to achieve good results. For a graph of size [Formula: see text], we show an asymptotically tight bound of [Formula: see text] on the number of advice bits to produce an optimal solution for any given graph. For parti
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Boyar, Joan, Lene M. Favrholdt, Christian Kudahl, Kim S. Larsen, and Jesper W. Mikkelsen. "Online Algorithms with Advice." ACM Computing Surveys 50, no. 2 (2017): 1–34. http://dx.doi.org/10.1145/3056461.

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Barrière, Lali, Xavier Muñoz, Janosch Fuchs, and Walter Unger. "Online Matching in Regular Bipartite Graphs." Parallel Processing Letters 28, no. 02 (2018): 1850008. http://dx.doi.org/10.1142/s0129626418500081.

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In an online problem, the input is revealed one piece at a time. In every time step, the online algorithm has to produce a part of the output, based on the partial knowledge of the input. Such decisions are irrevocable, and thus online algorithms usually lead to nonoptimal solutions. The impact of the partial knowledge depends strongly on the problem. If the algorithm is allowed to read binary information about the future, the amount of bits read that allow the algorithm to solve the problem optimally is the so-called advice complexity. The quality of an online algorithm is measured by its com
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Chen, Li-Hsuan, Ling-Ju Hung, Henri Lotze, and Peter Rossmanith. "Online Node- and Edge-Deletion Problems with Advice." Algorithmica 83, no. 9 (2021): 2719–53. http://dx.doi.org/10.1007/s00453-021-00840-9.

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AbstractIn online edge- and node-deletion problems the input arrives node by node and an algorithm has to delete nodes or edges in order to keep the input graph in a given graph class $$\Pi $$ Π at all times. We consider only hereditary properties $$\Pi $$ Π , for which optimal online algorithms exist and which can be characterized by a set of forbidden subgraphs $${{\mathcal{F}}}$$ F and analyze the advice complexity of getting an optimal solution. We give almost tight bounds on the Delayed Connected$${{\mathcal{F}}}$$ F -Node-Deletion Problem, where all graphs of the family $${\mathcal{F}}$$
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Lykouris, Thodoris, and Sergei Vassilvitskii. "Competitive Caching with Machine Learned Advice." Journal of the ACM 68, no. 4 (2021): 1–25. http://dx.doi.org/10.1145/3447579.

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Traditional online algorithms encapsulate decision making under uncertainty, and give ways to hedge against all possible future events, while guaranteeing a nearly optimal solution, as compared to an offline optimum. On the other hand, machine learning algorithms are in the business of extrapolating patterns found in the data to predict the future, and usually come with strong guarantees on the expected generalization error. In this work, we develop a framework for augmenting online algorithms with a machine learned predictor to achieve competitive ratios that provably improve upon uncondition
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Boyar, Joan, Lene M. Favrholdt, Christian Kudahl, Kim S. Larsen, and Jesper W. Mikkelsen. "Online Algorithms with Advice: A Survey." ACM SIGACT News 47, no. 3 (2016): 93–129. http://dx.doi.org/10.1145/2993749.2993766.

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Böckenhauer, Hans-Joachim, Dennis Komm, Rastislav Královič, Richard Královič, and Tobias Mömke. "Online algorithms with advice: The tape model." Information and Computation 254 (June 2017): 59–83. http://dx.doi.org/10.1016/j.ic.2017.03.001.

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Aumayr, Erik, Jeffrey Chan, and Conor Hayes. "Reconstruction of Threaded Conversations in Online Discussion Forums." Proceedings of the International AAAI Conference on Web and Social Media 5, no. 1 (2021): 26–33. http://dx.doi.org/10.1609/icwsm.v5i1.14122.

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Online discussion boards, or Internet forums, are a significant part of the Internet. People use Internet forums to post questions, provide advice and participate in discussions. These online conversations are represented as threads, and the conversation trees within these threads are important in understanding the behaviour of online users. Unfortunately, the reply structures of these threads are generally not publicly accessible or not maintained. Hence, in this paper, we introduce an efficient and simple approach to reconstruct the reply structure in threaded conversations. We contrast its ac
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Zhao, Xiaofan, and Hong Shen. "Online algorithms for 2D bin packing with advice." Neurocomputing 189 (May 2016): 25–32. http://dx.doi.org/10.1016/j.neucom.2015.11.035.

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Dissertations / Theses on the topic "Online algorithm with advice"

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Renault, Marc Paul. "Lower and upper bounds for online algorithms with advice." Paris 7, 2014. http://www.theses.fr/2014PA077196.

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Les algorithmes en ligne fonctionnent dans un contexte où l'entrée est révélé au fur et à mesure du temps; chaque morceau révélé est appelé une demande. Après réception de chaque demahde, les algorithmes en ligne doivent prendre une action avant que la prochaine demande soit révélée, c'est-à-dire que les algorithmes en ligne doivent prendre une décision irrévocable basée sur les demandes déjà révélées sans aucune connaissance des demandes à venir. Le but est d'optimiser une fonction de coût dépendante de l'entrée. L'analyse compétitive est la méthode standard utilisée pour analyser la qualité
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Jin, Shendan. "Online computation beyond standard models." Electronic Thesis or Diss., Sorbonne université, 2020. http://www.theses.fr/2020SORUS152.

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Dans le cadre standard du calcul en ligne, l’entrée de l’algorithme n’est pas entièrement connue à l’avance, mais elle est révélée progressivement sous forme d’une séquence de requêtes. Chaque fois qu'une requête arrive, l'algorithme en ligne doit prendre des décisions irrévocables pour servir la demande, sans connaissance des requêtes futures. Dans le domaine des algorithmes en ligne, le cadre standard utilisé pour évaluer les performances des algorithmes en ligne est l’analyse compétitive. De manière informelle, le concept d’analyse compétitive consiste à comparer les performances d’un algor
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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.

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The main work for this thesis has been a thorough study of the novel Prediction with Partially Monitored Grouped Expert Advice and Side Information paradigm. This is newly proposed in this thesis, and it extends the widely studied Prediction with Expert Advice paradigm. The extension is based on two assumptions and one restriction that modify the original problem. The first assumption, Grouped, presumes that the experts are structured into groups. The second assumption, Side Information, introduces additional information that can be used to timely relate predictions with groups. Finally, the r
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Henke, Hans-Christian. "Online Advice : Konzeption eines ergebnisbasierten Simulationsansatzes /." [S.l. : s.n.], 2003. http://www.gbv.de/dms/zbw/362397171.pdf.

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Furkin, Jennifer D. "MOM TO MOM: ONLINE BREASTFEEDING ADVICE." UKnowledge, 2018. https://uknowledge.uky.edu/comm_etds/64.

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Exploring online support groups has gained more and more popularity in the last decade. Investigating the type of support messages users send each other has broadened the already extensive social support framework built in the last forty years. Mothers utilize online support for various topics, and a very common topic is breastfeeding. The perception of breastfeeding has changed throughout history with shifting beliefs and societal norms coupled with solid facts about its importance in the sustaining of infants. Online breastfeeding support has been previously explored through the categorizati
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Porter, 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.

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Thesis (Ph. D.)--University of Missouri-Columbia, 2008.<br>The 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.
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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.

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Researchers have suggested that social networking sites are especially suited to creating a two-way communication with audiences as described by Kent & Taylor’s dialogic communication theory. However, researchers have also shown that most organizations are failing to actually create this type of dialogue with their followers on SNS. This leads to the question: why are organizations failing to realize this potential? In this study, I consider one possible reason: that organizations are following advice offered online by self-appointed “experts” on SNS strategy and that advice is not effective.
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Barbaro, 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.

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Murphy, Nicholas John. "An online learning algorithm for technical trading." Master's thesis, Faculty of Science, 2019. http://hdl.handle.net/11427/31048.

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We use an adversarial expert based online learning algorithm to learn the optimal parameters required to maximise wealth trading zero-cost portfolio strategies. The learning algorithm is used to determine the relative population dynamics of technical trading strategies that can survive historical back-testing as well as form an overall aggregated portfolio trading strategy from the set of underlying trading strategies implemented on daily and intraday Johannesburg Stock Exchange data. The resulting population time-series are investigated using unsupervised learning for dimensionality reduction
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Orlansky, 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.

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Books on the topic "Online algorithm with advice"

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Kienholz, Michelle. Online guide to medical research: Valuable internet resources for medical research, practice & advice. Ventana, 1999.

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Moore, Alexis. Cyber self-defense: Expert advice to avoid online predators, identity theft, and cyberbullying. Lyons Press, 2014.

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John, Yate Martin, ed. Knock 'em dead résumés: Smart advice to make your online and paper résumés more productive. 8th ed. Adams Media, 2008.

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Pauline, David, ed. Your personal net doctor: Your guide to health and medical advice on the Internet and online services. Wolff New Media, 1996.

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Price, Joan. The insider's guide to internet health searches: Real-life success stories and expert advice for finding online health information you can trust. Rodale Press, 2002.

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Erlebach, Thomas. Approximation and Online Algorithms: 10th International Workshop, WAOA 2012, Ljubljana, Slovenia, September 13-14, 2012, Revised Selected Papers. Springer Berlin Heidelberg, 2013.

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Bolles, Mark Emery. Job-hunting online: A guide to job listings, message boards, research sites, the UnderWeb, counseling, networking, self-assessment tools, niche sites. 5th ed. Ten Speed Press, 2008.

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Collier, Marsha. Ebay for dummies. 5th ed. Wiley, 2007.

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Komm, Dennis. Introduction to Online Computation: Determinism, Randomization, Advice. Springer London, Limited, 2017.

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Komm, Dennis. Introduction to Online Computation: Determinism, Randomization, Advice. Springer International Publishing AG, 2016.

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Book chapters on the topic "Online algorithm with advice"

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Borodin, Allan, Joan Boyar, Kim S. Larsen, and Denis Pankratov. "Advice Complexity of Priority Algorithms." In Approximation and Online Algorithms. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-04693-4_5.

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Adamaszek, Anna, Marc P. Renault, Adi Rosén, and Rob van Stee. "Reordering Buffer Management with Advice." In Approximation and Online Algorithms. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-08001-7_12.

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Christ, Marie G., Lene M. Favrholdt, and Kim S. Larsen. "Online Multi-Coloring with Advice." In Approximation and Online Algorithms. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-18263-6_8.

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Böckenhauer, Hans-Joachim, Janosch Fuchs, and Walter Unger. "Exploring Sparse Graphs with Advice (Extended Abstract)." In Approximation and Online Algorithms. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-04693-4_7.

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Böckenhauer, Hans-Joachim, Dennis Komm, and Raphael Wegner. "Call Admission Problems on Grids with Advice (Extended Abstract)." In Approximation and Online Algorithms. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-04693-4_8.

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Dobrev, Stefan, Rastislav Královič, and Richard Královič. "Independent Set with Advice: The Impact of Graph Knowledge." In Approximation and Online Algorithms. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-38016-7_2.

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Böckenhauer, Hans-Joachim, Dennis Komm, Rastislav Královič, Richard Královič, and Tobias Mömke. "On the Advice Complexity of Online Problems." In Algorithms and Computation. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-10631-6_35.

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Renault, Marc P., and Adi Rosén. "On Online Algorithms with Advice for the k-Server Problem." In Approximation and Online Algorithms. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-29116-6_17.

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Rohatgi, Dhruv. "Near-Optimal Bounds for Online Caching with Machine Learned Advice." In Proceedings of the Fourteenth Annual ACM-SIAM Symposium on Discrete Algorithms. Society for Industrial and Applied Mathematics, 2020. http://dx.doi.org/10.1137/1.9781611975994.112.

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Ouyang, Daosheng, Yiqiang Zou, Yunshi Hu, Yimin You, Jing Lin, and Weiming Tong. "Intelligent Diagnosis of High-Voltage Switchgear Based on GANs and DualLSTM-DropNet." In Lecture Notes in Electrical Engineering. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-4856-6_9.

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Abstract As artificial intelligence technology continues to advance in the smart grid domain, it shows significant potential for optimizing online monitoring and intelligent diagnosis of high-voltage switchgear. Online monitoring and intelligent diagnosis involve the real-time collection of characteristic parameters to assess equipment health, enabling fault diagnosis, condition evaluation, and lifespan prediction through algorithmic integration. However, challenges such as limited data samples, insufficient data validity and correlation, reliance on single diagnosis algorithms, and suboptimal
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Conference papers on the topic "Online algorithm with advice"

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Sahu, Neelesh Kumar, Rishabh Soni, Priyanshu Namdeo, Nikhil Mishra, P. Humanshu Naidu, and Priyansh Pawar. "Development of Assistance System for Online Dispute Resolution and Legal Advice Using AIML." In 2025 International Conference on Computational, Communication and Information Technology (ICCCIT). IEEE, 2025. https://doi.org/10.1109/icccit62592.2025.10927904.

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Zhou, Xuepeng, Miaoping Sun, and Liping Chen. "The Distributed Online Algorithm for Constrained Online Cluster Game Nash Equilibrium." In 2024 43rd Chinese Control Conference (CCC). IEEE, 2024. http://dx.doi.org/10.23919/ccc63176.2024.10661386.

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Zhao, Xiaofan, Xin Li, and 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.

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Creveling, Jessica, та Cedric Hagen. "COMBINING A δ13CCARB CORRELATION ALGORITHM AND A REFINED RADIOMETRIC CHRONOLOGY TO ADVANCE PRECAMBRIAN (EDIACARAN) BASIN ANALYSIS". У GSA 2020 Connects Online. Geological Society of America, 2020. http://dx.doi.org/10.1130/abs/2020am-355524.

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Vaidya, Nupur D., Yogesh A. Suryawanshi, and 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.

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Ganapathi Subramanian, Sriram, Matthew E. Taylor, Kate Larson, and Mark Crowley. "Multi-Agent Advisor Q-Learning (Extended Abstract)." In Thirty-Second International Joint Conference on Artificial Intelligence {IJCAI-23}. International Joint Conferences on Artificial Intelligence Organization, 2023. http://dx.doi.org/10.24963/ijcai.2023/776.

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In the last decade, there have been significant advances in multi-agent reinforcement learning (MARL) but there are still numerous challenges, such as high sample complexity and slow convergence to stable policies, that need to be overcome before wide-spread deployment is possible. However, many real-world environments already, in practice, deploy sub-optimal or heuristic approaches for generating policies. An interesting question that arises is how to best use such approaches as advisors to help improve reinforcement learning in multi-agent domains. We provide a principled framework for incor
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Hikima, Yuya, Yasunori Akagi, Naoki Marumo, and Hideaki Kim. "Online Matching with Controllable Rewards and Arrival Probabilities." In Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}. International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/ijcai.2022/254.

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Online bipartite matching has attracted much attention due to its importance in various applications such as advertising, ride-sharing, and crowdsourcing. In most online matching problems, the rewards and node arrival probabilities are given in advance and are not controllable. However, many real-world matching services require them to be controllable and the decision-maker faces a non-trivial problem of optimizing them. In this study, we formulate a new optimization problem, Online Matching with Controllable Rewards and Arrival probabilities (OM-CRA), to simultaneously determine not only the
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Nirala, C. K., and 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.

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Sivagnanam, Amutheezan, Salah Uddin Kadir, Ayan Mukhopadhyay, et al. "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}. International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/ijcai.2022/546.

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Vehicle routing problems (VRPs) can be divided into two major categories: offline VRPs, which consider a given set of trip requests to be served, and online VRPs, which consider requests as they arrive in real-time. Based on discussions with public transit agencies, we identify a real-world problem that is not addressed by existing formulations: booking trips with flexible pickup windows (e.g., 3 hours) in advance (e.g., the day before) and confirming tight pickup windows (e.g., 30 minutes) at the time of booking. Such a service model is often required in paratransit service settings, where pa
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Cai, 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}. International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/616.

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Aiming to improve the performance of existing reversion based online portfolio selection strategies, we propose a novel multi-period strategy named “Vector Autoregressive Weighting Reversion” (VAWR). Firstly, vector autoregressive moving-average algorithm used in time series prediction is transformed into exploring the dynamic relationships between different assets for more accurate price prediction. Secondly, we design the modified online passive aggressive technique and advance a scheme to weigh investment risk and cumulative experience to update the closed-form of portfolio. Theoretical ana
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Reports on the topic "Online algorithm with advice"

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Balman, Mehmet, and Tevfik Kosar. An Online Scheduling Algorithm with Advance Reservation for Large-Scale Data Transfers. Office of Scientific and Technical Information (OSTI), 2010. http://dx.doi.org/10.2172/1050437.

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Santesson, S., and P. Hallam-Baker. Online Certificate Status Protocol Algorithm Agility. RFC Editor, 2011. http://dx.doi.org/10.17487/rfc6277.

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Streeter, Matthew, and Daniel Golovin. An Online Algorithm for Maximizing Submodular Functions. Defense Technical Information Center, 2007. http://dx.doi.org/10.21236/ada476748.

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Anderson, Erika, and Dominic Chalmers. The Shifting Locus of Authoritative Advice for Gen-Z and Their Financial Lives: An Opportunity for the Credit Union Sector? University of Glasgow and University of Strathclyde, 2025. https://doi.org/10.36399/gla.pubs.349744.

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Gen Z are reshaping the way financial advice is sought and acted upon. Moving away from traditional sources like family, banks, and financial advisors, younger generations are turning to social media platforms like TikTok and Instagram, where financial influencers —“finfluencers”— offer accessible, though often unregulated, advice. While this shift has democratized financial education, it has also introduced significant risks to advice-seekers, including misinformation, high-risk investment recommendations, and a lack of regulatory oversight. For Credit Unions, this transformation presents cha
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Labonno, Nusrat Jahan, and Wahid bin Ahsan. Health Misinformation on Social Media in Bangladesh: Public Health Impact and Mitigation Strategies. Userhub, 2024. http://dx.doi.org/10.58947/rgkm-sdpt.

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The dissemination of health misinformation via digital platforms poses a significant risk to public health in Bangladesh, with many individuals acting on false information. This study aims to understand how the general population engages with health-related content, identify the causes and impact of misinformation, and offer recommendations to mitigate this issue. Using a mixed-methods approach, the study combines qualitative data from detailed interviews with quantitative data from online surveys. Key findings indicate a widespread tendency to trust and follow health recommendations found onl
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Meeker, 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), 2021. http://dx.doi.org/10.19088/core.2021.007.

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On the 19 and 20 October 2021, the Institute of Development Studies hosted an online dialogue which aimed to enhance efforts to inform and influence policy, management, and practice with intersectional gender-responsive evidence by sharing learning between CORE cohort members from their approaches and experiences at country and regional levels. The event was attended by over 30 participants from 19 partners across the CORE cohort and highlighted the experiences of CORE partners Glasswing and the Arab Reform Initiative (ARI). This learning guide captures the practical insights and advice from t
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Schmidt-Sane, Megan, Tabitha Hrynick, Erica Nelson, and Tom Barker. Mutual Learning for Policy Impact: Insights from CORE. Adapting research methods in the context of Covid-19. Institute of Development Studies (IDS), 2021. http://dx.doi.org/10.19088/core.2021.008.

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On 25 November 2021, the CORE Knowledge Translation Services team at the Institute of Development Studies, UK, hosted an online clinic session to facilitate the sharing of experiences and mutual learning on how CORE projects have or can adapt their research activities in the context of the Covid-19 pandemic. The clinic was attended by 22 CORE members from 12 projects and featured contributions from two CORE projects: The Youth Question in Africa: Impact, Response and Protection Measures in the IGAD Region and A New Digital Deal for an Inclusive Post-Covid-19 Social Compact: Developing Digital
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8

Meeker, 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), 2021. http://dx.doi.org/10.19088/core.2021.005.

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On 23 June 2021, Southern Voice and the Institute of Development Studies co-hosted an online dialogue which aimed to enhance efforts to inform and influence policy by sharing learning between CORE projects, at different stages in their policy engagement activities, on their approaches and experiences at sub-national, national, and regional levels. The event was attended by over 70 participants from across the CORE cohort and highlighted the experiences of CORE partners, Partnership for Economic Policy (PEP), International Centre for Research on Women (ICRW), and Group for the Analysis of Devel
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9

Tidd, Alexander N., Richard A. Ayers, Grant P. Course, and 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. Edited by Mark James and Hannah Ladd-Jones. Marine Alliance for Science and Technology for Scotland (MASTS), 2019. http://dx.doi.org/10.15664/10023.23452.

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[Extract from Executive Summary] The competition for space from competing sectors in the coastal waters of Scotland has never been greater and thus there is a growing a need for interactive seascape planning tools that encompass all marine activities. Similarly, the need to gather data to inform decision makers, especially in the fishing industry, has become essential to provide advice on the economic impact on fishing fleets both in terms of alternative conservation measures (e.g. effort limitations, temporal and spatial closures) as well as the overlap with other activities, thereby allowing
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10

Gertler, Paul, Sebastian Martinez, Laura B. Rawlings, Patrick Premand, and Christel M. J. Vermeersch. Impact Evaluation in Practice: Second Edition. Inter-American Development Bank, 2016. http://dx.doi.org/10.18235/0006529.

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The second edition of the Impact Evaluation in Practice handbook is a comprehensive and accessible introduction to impact evaluation for policy makers and development practitioners. First published in 2011, it has been used widely across the development and academic communities. The book incorporates real-world examples to present practical guidelines for designing and implementing impact evaluations. Readers will gain an understanding of impact evaluations and the best ways to use them to design evidence-based policies and programs. The updated version covers the newest techniques for evaluat
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