Relevant bibliographies by topics / Online algorithms with recourse

Contents

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

Academic literature on the topic 'Online algorithms with recourse'

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

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Journal articles on the topic "Online algorithms with recourse"

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Vasilopoulos, Vasileios, Georgios Pavlakos, Karl Schmeckpeper, Kostas Daniilidis, and Daniel E. Koditschek. "Reactive navigation in partially familiar planar environments using semantic perceptual feedback." International Journal of Robotics Research 41, no. 1 (2021): 85–126. http://dx.doi.org/10.1177/02783649211048931.

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This article solves the planar navigation problem by recourse to an online reactive scheme that exploits recent advances in simultaneous localization and mapping (SLAM) and visual object recognition to recast prior geometric knowledge in terms of an offline catalog of familiar objects. The resulting vector field planner guarantees convergence to an arbitrarily specified goal, avoiding collisions along the way with fixed but arbitrarily placed instances from the catalog as well as completely unknown fixed obstacles so long as they are strongly convex and well separated. We illustrate the generi
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Abdelkader, Krifa, and Bouzrara Kais. "Robust H∞ gain neuro-adaptive observer design for nonlinear uncertain systems." Transactions of the Institute of Measurement and Control 41, no. 8 (2018): 2293–309. http://dx.doi.org/10.1177/0142331218798685.

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To guarantee convergent state estimates and exact approximations, it is highly desirable that observers can independently dominate the effects of unmodelled dynamics. Based on adaptive nonlinear approximation, this paper presents a robust H∞ gain neuro-adaptive observer (R H∞GNAO) design methodology for a large class of uncertain nonlinear systems in the presence of time-varying unknown parameters with bounded external disturbances on the state vector and on the output of the original system. The proposed R H∞GNAO incorporates radial basis function neural networks (RBFNNs) to approximate the u
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Eleiwy, Jabbar Abed, Ruqaya Shaker Mahmood, Asma A. Abdulrahman, Hassan Mohamed Muhi-Aldeen, Fouad S. Tahir, and Yurii Khlaponin. "Enhancement of watermarking based on deep neural network for images." EUREKA: Physics and Engineering, no. 1 (January 31, 2025): 152–62. https://doi.org/10.21303/2461-4262.2025.003438.

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The spread of the Internet of Things applications and the shared massive amount of data leads to the absence of data security and missing product protection, such as copyrights, pharmaceutical products, and online medical result fraud. To address the security gap, it is possible to propose a model based on developing a new filter derived from Laguerre polynomials based on essential mathematical operations by using the parent function to construct a new discrete Laguerre wavelets transform (DLWT) in image analysis with the watermark, as well as reaching an ideal algorithm through the readings f
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Angelopoulos, Spyros, Christoph Dürr, and Shendan Jin. "Online maximum matching with recourse." Journal of Combinatorial Optimization 40, no. 4 (2020): 974–1007. http://dx.doi.org/10.1007/s10878-020-00641-w.

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Avitabile, T., C. Mathieu, and L. Parkinson. "Online constrained optimization with recourse." Information Processing Letters 113, no. 3 (2013): 81–86. http://dx.doi.org/10.1016/j.ipl.2012.09.011.

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Wang, Jinde. "Approximate nonlinear programming algorithms for solving stochastic programs with recourse." Annals of Operations Research 31, no. 1 (1991): 371–84. http://dx.doi.org/10.1007/bf02204858.

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Kulkarni, Ankur A., and Uday V. Shanbhag. "Recourse-based stochastic nonlinear programming: properties and Benders-SQP algorithms." Computational Optimization and Applications 51, no. 1 (2010): 77–123. http://dx.doi.org/10.1007/s10589-010-9316-8.

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Megow, Nicole, Martin Skutella, José Verschae, and Andreas Wiese. "The Power of Recourse for Online MST and TSP." SIAM Journal on Computing 45, no. 3 (2016): 859–80. http://dx.doi.org/10.1137/130917703.

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Tometzki, Thomas, and Sebastian Engell. "Hybrid Evolutionary Optimization of Two-Stage Stochastic Integer Programming Problems: An Empirical Investigation." Evolutionary Computation 17, no. 4 (2009): 511–26. http://dx.doi.org/10.1162/evco.2009.17.4.17404.

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In this contribution, we consider decision problems on a moving horizon with significant uncertainties in parameters. The information and decision structure on moving horizons enables recourse actions which correct the here-and-now decisions whenever the horizon is moved a step forward. This situation is reflected by a mixed-integer recourse model with a finite number of uncertainty scenarios in the form of a two-stage stochastic integer program. A stage decomposition-based hybrid evolutionary algorithm for two-stage stochastic integer programs is proposed that employs an evolutionary algorith
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Wang, Paul Y., Sainyam Galhotra, Romila Pradhan, and Babak Salimi. "Demonstration of generating explanations for black-box algorithms using Lewis." Proceedings of the VLDB Endowment 14, no. 12 (2021): 2787–90. http://dx.doi.org/10.14778/3476311.3476345.

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Explainable artificial intelligence (XAI) aims to reduce the opacity of AI-based decision-making systems, allowing humans to scrutinize and trust them. Unlike prior work that attributes the responsibility for an algorithm's decisions to its inputs as a purely associational concept, we propose a principled causality-based approach for explaining black-box decision-making systems. We present the demonstration of Lewis, a system that generates explanations for black-box algorithms at the global, contextual, and local levels, and provides actionable recourse for individuals negatively affected by
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Dissertations / Theses on the topic "Online algorithms with recourse"

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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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Lowe, Wing Wah. "An exploration of stochastic decomposition algorithms for stochastic linear programs with recourse." Diss., The University of Arizona, 1994. http://hdl.handle.net/10150/186667.

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Stochastic linear programs are linear programs in which some of the problem data are random variables. The particular kind of programs that we study belong to the recourse model. Under this model, some decisions are postponed until better information becomes available (e.g., an outcome of a random variable is realized), while other decisions must be made 'here and now.' For example, in a telecommunication network planning problem, decisions regarding the addition of network capacity have to be made before knowing customer demand (i.e., 'here and now'). Once the demand is realized, efficient us
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Li, Le. "Online stochastic algorithms." Thesis, Angers, 2018. http://www.theses.fr/2018ANGE0031.

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Cette thèse travaille principalement sur trois sujets. Le premier concentre sur le clustering en ligne dans lequel nous présentons un nouvel algorithme stochastique adaptatif pour regrouper des ensembles de données en ligne. Cet algorithme repose sur l'approche quasi-bayésienne, avec une estimation dynamique (i.e., dépendant du temps) du nombre de clusters. Nous prouvons que cet algorithme atteint une borne de regret de l'ordre et que cette borne est asymptotiquement minimax sous la contrainte sur le nombre de clusters. Nous proposons aussi une implémentation par RJMCMC. Le deuxième sujet est
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Shi, Tian. "Novel Algorithms for Understanding Online Reviews." Diss., Virginia Tech, 2021. http://hdl.handle.net/10919/104998.

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This dissertation focuses on the review understanding problem, which has gained attention from both industry and academia, and has found applications in many downstream tasks, such as recommendation, information retrieval and review summarization. In this dissertation, we aim to develop machine learning and natural language processing tools to understand and learn structured knowledge from unstructured reviews, which can be investigated in three research directions, including understanding review corpora, understanding review documents, and understanding review segments. For the corpus-level
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Sentenac, Flore. "Learning and Algorithms for Online Matching." Electronic Thesis or Diss., Institut polytechnique de Paris, 2023. http://www.theses.fr/2023IPPAG005.

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Cette thèse se concentre principalement sur les problèmes d'appariement en ligne, où des ensembles de ressources sont alloués séquentiellement à des flux de demandes. Nous les traitons à la fois du point de vue de l'apprentissage en ligne et de l'analyse compétitive, toujours lorsqueEn ce qui concerne l'apprentissage en ligne, nous étudions comment la structure spécifique de l'appariement influence l'apprentissage dans la première partie, puis comment les effets de report dans le système affectent ses performances.En ce qui concerne l'analyse compétitive, nous étudions le problème de l'apparie
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Trippen, Gerhard Wolfgang. "Online exploration and search in graphs /." View abstract or full-text, 2006. http://library.ust.hk/cgi/db/thesis.pl?COMP%202006%20TRIPPE.

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Li, Rongbin, and 李榕滨. "New competitive algorithms for online job scheduling." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2014. http://hdl.handle.net/10722/197555.

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Job scheduling, which greatly impacts on the system performance, is a fundamental problem in computer science. In this thesis, we study three kinds of scheduling problems, that is, deadline scheduling, due date scheduling, and flow time scheduling. Traditionally, the major concern for scheduling problems is the system performance, i.e. the “Quality of Service" (QoS). Different scheduling problems use different QoS measurements. For deadline scheduling, the most common QoS to optimize is the throughput; for due date scheduling, it is the total quoted lead time; and for flow time scheduling, it
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ALBUQUERQUE, LUIZ FERNANDO FERNANDES DE. "ONLINE ALGORITHMS ANALYSIS FOR SPONSORED LINKS SELECTION." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2009. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=16088@1.

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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO<br>Links patrocinados são aqueles que aparecem em destaque nos resultados de pesquisas em máquinas de busca na Internet e são grande fonte de receita para seus provedores. Para os anunciantes, que fazem ofertas por palavras-chave para aparecerem em destaque nas consultas dos usuários, são uma oportunidade de divulgação da marca, conquista e manutenção de clientes. Um dos desafios das máquinas de busca neste modelo de negócio é selecionar os anunciantes que serão exibidos a cada consulta de modo a maximizar sua receita em determinado período. E
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Pasteris, S. U. "Efficient algorithms for online learning over graphs." Thesis, University College London (University of London), 2016. http://discovery.ucl.ac.uk/1516210/.

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In this thesis we consider the problem of online learning with labelled graphs, in particular designing algorithms that can perform this problem quickly and with low memory requirements. We consider the tasks of Classification (in which we are asked to predict the labels of vertices) and Similarity Prediction (in which we are asked to predict whether two given vertices have the same label). The first half of the thesis considers non- probabilistic online learning, where there is no probability distribution on the labelling and we bound the number of mistakes of an algorithm by a function of th
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Bonifaci, Vincenzo. "Models and algorithms for online server routing." Doctoral thesis, La Sapienza, 2007. http://hdl.handle.net/11573/917056.

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Books on the topic "Online algorithms with recourse"

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Fiat, Amos, and Gerhard J. Woeginger, eds. Online Algorithms. Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/bfb0029561.

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Kaklamanis, Christos, and Asaf Levin, eds. Approximation and Online Algorithms. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-80879-2.

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Koenemann, Jochen, and Britta Peis, eds. Approximation and Online Algorithms. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-92702-8.

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Chalermsook, Parinya, and Bundit Laekhanukit, eds. Approximation and Online Algorithms. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-18367-6.

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Bampis, Evripidis, and Ola Svensson, eds. Approximation and Online Algorithms. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-18263-6.

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Sanità, Laura, and Martin Skutella, eds. Approximation and Online Algorithms. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-28684-6.

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Erlebach, Thomas, and Giuseppe Persiano, eds. Approximation and Online Algorithms. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-38016-7.

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Solis-Oba, Roberto, and Giuseppe Persiano, eds. Approximation and Online Algorithms. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-29116-6.

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Jansen, Klaus, and Monaldo Mastrolilli, eds. Approximation and Online Algorithms. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-51741-4.

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Solis-Oba, Roberto, and Rudolf Fleischer, eds. Approximation and Online Algorithms. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-89441-6.

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Book chapters on the topic "Online algorithms with recourse"

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Liu, Alison Hsiang-Hsuan, and Jonathan Toole-Charignon. "The Power of Amortized Recourse for Online Graph Problems." In Approximation and Online Algorithms. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-18367-6_7.

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Gupta, Anupam, Vijaykrishna Gurunathan, Ravishankar Krishnaswamy, Amit Kumar, and Sahil Singla. "Online Discrepancy with Recourse for Vectors and Graphs." In Proceedings of the 2022 Annual ACM-SIAM Symposium on Discrete Algorithms (SODA). Society for Industrial and Applied Mathematics, 2022. http://dx.doi.org/10.1137/1.9781611977073.57.

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Fiat, Amos, and Gerhard J. Woeginger. "Competitive analysis of algorithms." In Online Algorithms. Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/bfb0029562.

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Albers, Susanne, and Jeffery Westbrook. "Self-organizing data structures." In Online Algorithms. Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/bfb0029563.

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Irani, Sandy. "Competitive analysis of paging." In Online Algorithms. Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/bfb0029564.

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Chrobak, Marek, and Lawrence L. Larmore. "Metrical task systems, the server problem and the work function algorithm." In Online Algorithms. Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/bfb0029565.

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Bartal, Yair. "Distributed paging." In Online Algorithms. Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/bfb0029566.

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Aspnes, James. "Competitive analysis of distributed algorithms." In Online Algorithms. Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/bfb0029567.

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Csirik, János, and Gerhard J. Woeginger. "On-line packing and covering problems." In Online Algorithms. Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/bfb0029568.

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Azar, Yossi. "On-line load balancing." In Online Algorithms. Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/bfb0029569.

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Conference papers on the topic "Online algorithms with recourse"

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Joshi, Deepak, Saugat Ghimire, Salman S. Shiuab, and Vaithianathan “Mani” Venkatasubramanian. "Computational Analysis of Online Oscillation Monitoring Algorithms." In 2024 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm). IEEE, 2024. http://dx.doi.org/10.1109/smartgridcomm60555.2024.10738090.

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Wu, Liang, and Meiwen Guo. "Homomorphic Encryption Algorithms for Online Furniture Customization Platforms." In 2024 International Conference on Information Technology, Communication Ecosystem and Management (ITCEM). IEEE, 2024. https://doi.org/10.1109/itcem65710.2024.00032.

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Fonseca, João, Andrew Bell, Carlo Abrate, Francesco Bonchi, and Julia Stoyanovich. "Setting the Right Expectations: Algorithmic Recourse Over Time." In EAAMO '23: Equity and Access in Algorithms, Mechanisms, and Optimization. ACM, 2023. http://dx.doi.org/10.1145/3617694.3623251.

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Krishnaswamy, Ravishankar, Shi Li, and Varun Suriyanarayana. "Online Unrelated-Machine Load Balancing and Generalized Flow with Recourse." In STOC '23: 55th Annual ACM Symposium on Theory of Computing. ACM, 2023. http://dx.doi.org/10.1145/3564246.3585222.

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Abé, M., and T. Igusa. "New Control Algorithms for Semi-Active Dynamic Vibration Absorbers." In ASME 1995 Design Engineering Technical Conferences collocated with the ASME 1995 15th International Computers in Engineering Conference and the ASME 1995 9th Annual Engineering Database Symposium. American Society of Mechanical Engineers, 1995. http://dx.doi.org/10.1115/detc1995-0619.

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Abstract A semi-active dynamic vibration absorber is proposed for controlling the free-vibration impulse response of structures. It is assumed that (i) the initial displacement for the absorber spring can be set to non-zero values and (ii) the viscous damping coefficient for the absorber damping can be adjusted. The theory is first developed for a single-degree-of-freedom structure, and is then generalized to continuous structures. The extensive use of closed-form analytical results provides useful insight into the complex interaction between the structure and absorber. This makes it possible
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Meng, De, Maryam Fazel, and Mehran Mesbahi. "Online algorithms for network formation." In 2016 IEEE 55th Conference on Decision and Control (CDC). IEEE, 2016. http://dx.doi.org/10.1109/cdc.2016.7798259.

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Bern, M., D. H. Greene, A. Raghunathan, and M. Sudan. "Online algorithms for locating checkpoints." In the twenty-second annual ACM symposium. ACM Press, 1990. http://dx.doi.org/10.1145/100216.100264.

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Meyerson, Adam. "Online algorithms for network design." In the sixteenth annual ACM symposium. ACM Press, 2004. http://dx.doi.org/10.1145/1007912.1007958.

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Kuh, Anthony, Muhammad Sharif Uddin, and Phyllis Ng. "Online unsupervised kernel learning algorithms." In 2017 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC). IEEE, 2017. http://dx.doi.org/10.1109/apsipa.2017.8282179.

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Ramanathan, Dinesh, and Rajesh Gupta. "System level online power management algorithms." In the conference. ACM Press, 2000. http://dx.doi.org/10.1145/343647.343867.

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Reports on the topic "Online algorithms with recourse"

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Ur, Shmuel. Analysis of Online Algorithms for Organ Allocation. Defense Technical Information Center, 1990. http://dx.doi.org/10.21236/ada249361.

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Labrindis, Alexandros, and Nick Roussopoulos. A Performance Evaluation of Online Warehouse Update Algorithms. Defense Technical Information Center, 1998. http://dx.doi.org/10.21236/ada441038.

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Harriss, Lydia, and Katie Raymer. Online Information and Fake News. Parliamentary Office of Science and Technology, 2017. http://dx.doi.org/10.58248/pn559.

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Internet search engines and social media platforms are an increasingly popular way of accessing news and information. In 2017, the proportion of UK adults consuming news online exceeded those who watched news on TV (74% versus 69%). This note considers how people access news online, how algorithms (sequences of instructions) and social networks influence the content that users see, and options for mitigating any negative impact.
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Mathew, Jijo K., Christopher M. Day, Howell Li, and Darcy M. Bullock. Curating Automatic Vehicle Location Data to Compare the Performance of Outlier Filtering Methods. Purdue University, 2021. http://dx.doi.org/10.5703/1288284317435.

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Agencies use a variety of technologies and data providers to obtain travel time information. The best quality data can be obtained from second-by-second tracking of vehicles, but that data presents many challenges in terms of privacy, storage requirements and analysis. More frequently agencies collect or purchase segment travel time based upon some type of matching of vehicles between two spatially distributed points. Typical methods for that data collection involve license plate re-identification, Bluetooth, Wi-Fi, or some type of rolling DSRC identifier. One of the challenges in each of thes
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Danylchuk, Hanna B., and Serhiy O. Semerikov. Advances in machine learning for the innovation economy: in the shadow of war. Криворізький державний педагогічний університет, 2023. http://dx.doi.org/10.31812/123456789/7732.

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This preface introduces the selected and revised papers presented at the 10th International Conference on Monitoring, Modeling &amp; Management of Emergent Economy (M3E2 2022), held online in Ukraine, on November 17-18, 2022. The conference aimed to bring together researchers, practitioners, and students from various fields to exchange ideas, share experiences, and discuss challenges and opportunities in applying computational intelligence and data science for the innovation economy. The innovation economy is a term that describes the emerging paradigm of economic development that is driven by
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Arhin, Stephen, Babin Manandhar, Hamdiat Baba Adam, and Adam Gatiba. Predicting Bus Travel Times in Washington, DC Using Artificial Neural Networks (ANNs). Mineta Transportation Institute, 2021. http://dx.doi.org/10.31979/mti.2021.1943.

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Washington, DC is ranked second among cities in terms of highest public transit commuters in the United States, with approximately 9% of the working population using the Washington Metropolitan Area Transit Authority (WMATA) Metrobuses to commute. Deducing accurate travel times of these metrobuses is an important task for transit authorities to provide reliable service to its patrons. This study, using Artificial Neural Networks (ANN), developed prediction models for transit buses to assist decision-makers to improve service quality and patronage. For this study, we used six months of Automati
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