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Journal articles on the topic 'Online algorithms with recourse'

Author: Grafiati

Published: 25 May 2024

Last updated: 31 July 2025

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1

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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2

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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3

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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4

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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5

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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6

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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7

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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8

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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9

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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10

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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11

Smeulders, Bart, Valentin Bartier, Yves Crama, and Frits C. R. Spieksma. "Recourse in Kidney Exchange Programs." INFORMS Journal on Computing 34, no. 2 (2022): 1191–206. http://dx.doi.org/10.1287/ijoc.2021.1099.

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We introduce the problem of selecting patient-donor pairs in a kidney exchange program to undergo a crossmatch test, and we model this selection problem as a two-stage stochastic integer programming problem. The optimal solutions of this new formulation yield a larger expected number of realized transplants than previous approaches based on internal recourse or subset recourse. We settle the computational complexity of the selection problem by showing that it remains NP-hard even for maximum cycle length equal to two. Furthermore, we investigate to what extent different algorithmic approaches,

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12

Smale, Steve, and Yuan Yao. "Online Learning Algorithms." Foundations of Computational Mathematics 6, no. 2 (2005): 145–70. http://dx.doi.org/10.1007/s10208-004-0160-z.

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13

BARBAKH, WESAM, and COLIN FYFE. "ONLINE CLUSTERING ALGORITHMS." International Journal of Neural Systems 18, no. 03 (2008): 185–94. http://dx.doi.org/10.1142/s0129065708001518.

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We introduce a set of clustering algorithms whose performance function is such that the algorithms overcome one of the weaknesses of K-means, its sensitivity to initial conditions which leads it to converge to a local optimum rather than the global optimum. We derive online learning algorithms and illustrate their convergence to optimal solutions which K-means fails to find. We then extend the algorithm by underpinning it with a latent space which enables a topology preserving mapping to be found. We show visualisation results on some standard data sets.

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14

Unnikrishnan, Avinash, and Miguel Figliozzi. "Online Freight Network Assignment Model with Transportation Disruptions and Recourse." Transportation Research Record: Journal of the Transportation Research Board 2224, no. 1 (2011): 17–25. http://dx.doi.org/10.3141/2224-03.

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15

Gilbert, Andrew Simon. "Algorithmic culture and the colonization of life-worlds." Thesis Eleven 146, no. 1 (2018): 87–96. http://dx.doi.org/10.1177/0725513618776699.

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This article explores some of the concerns which are being raised about algorithms with recourse to Habermas’s theory of communicative action. The intention is not to undertake an empirical examination of ‘algorithms’ or their consequences but to connect critical theory to some contemporary concerns regarding digital cultures. Habermas’s ‘colonization of life-worlds’ thesis gives theoretical expression to two different trends which underlie many current criticisms of the insidious influence of digital algorithms: the privatization of communication, and the particularization of knowledge and ex

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16

Ying, Y., and D. X. Zhou. "Online Regularized Classification Algorithms." IEEE Transactions on Information Theory 52, no. 11 (2006): 4775–88. http://dx.doi.org/10.1109/tit.2006.883632.

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17

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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18

Christianson, Nicolas, Bo Sun, Steven Low, and Adam Wierman. "Risk-Sensitive Online Algorithms." ACM SIGMETRICS Performance Evaluation Review 52, no. 2 (2024): 6–8. http://dx.doi.org/10.1145/3695411.3695415.

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19

Albers, Susanne. "Online algorithms: a survey." Mathematical Programming 97, no. 1 (2003): 3–26. http://dx.doi.org/10.1007/s10107-003-0436-0.

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20

Ying, Yiming, and Ding-Xuan Zhou. "Online Pairwise Learning Algorithms." Neural Computation 28, no. 4 (2016): 743–77. http://dx.doi.org/10.1162/neco_a_00817.

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Pairwise learning usually refers to a learning task that involves a loss function depending on pairs of examples, among which the most notable ones are bipartite ranking, metric learning, and AUC maximization. In this letter we study an online algorithm for pairwise learning with a least-square loss function in an unconstrained setting of a reproducing kernel Hilbert space (RKHS) that we refer to as the Online Pairwise lEaRning Algorithm (OPERA). In contrast to existing works (Kar, Sriperumbudur, Jain, & Karnick, 2013 ; Wang, Khardon, Pechyony, & Jones, 2012 ), which require that the i

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21

Le Thi, Hoai An, and Vinh Thanh Ho. "Online Learning Based on Online DCA and Application to Online Classification." Neural Computation 32, no. 4 (2020): 759–93. http://dx.doi.org/10.1162/neco_a_01266.

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We investigate an approach based on DC (Difference of Convex functions) programming and DCA (DC Algorithm) for online learning techniques. The prediction problem of an online learner can be formulated as a DC program for which online DCA is applied. We propose the two so-called complete/approximate versions of online DCA scheme and prove their logarithmic/sublinear regrets. Six online DCA-based algorithms are developed for online binary linear classification. Numerical experiments on a variety of benchmark classification data sets show the efficiency of our proposed algorithms in comparison wi

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22

Liu, Yuxin, Yi Mei, Mengjie Zhang, and Zili Zhang. "A Predictive-Reactive Approach with Genetic Programming and Cooperative Coevolution for the Uncertain Capacitated Arc Routing Problem." Evolutionary Computation 28, no. 2 (2020): 289–316. http://dx.doi.org/10.1162/evco_a_00256.

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The uncertain capacitated arc routing problem is of great significance for its wide applications in the real world. In the uncertain capacitated arc routing problem, variables such as task demands and travel costs are realised in real time. This may cause the predefined solution to become ineffective and/or infeasible. There are two main challenges in solving this problem. One is to obtain a high-quality and robust baseline task sequence, and the other is to design an effective recourse policy to adjust the baseline task sequence when it becomes infeasible and/or ineffective during the executi

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23

Butler, Owen, and Darren Musgrove. "72 Elemental Screening of Welding Fumes by Ed-Xrf Using a Standardless Calibration Algorithm." Annals of Work Exposures and Health 67, Supplement_1 (2023): i22—i23. http://dx.doi.org/10.1093/annweh/wxac087.060.

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Abstract X-ray fluorescence (XRF) is an ideal analytical technique for rapid elemental analysis in supporting forensic analysis, for exposure assessments and for product compositional analysis. Standardless calibration algorithms are widely used in modern XRF systems so providing, in many cases, near quantitative analysis, without recourse to needing matrix-matched standards. However if available, matrix standards can be used to further improve the performance of such algorithms and so provide better quantitative data. In this presentation, XRF analysis of bulk welding fume samples was perform

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24

Siddig, Murwan, and Yongjia Song. "Adaptive partition-based SDDP algorithms for multistage stochastic linear programming with fixed recourse." Computational Optimization and Applications 81, no. 1 (2021): 201–50. http://dx.doi.org/10.1007/s10589-021-00323-1.

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25

Sand, G., J. Till, T. Tometzki, M. Urselmann, S. Engell, and M. Emmerich. "Engineered versus standard evolutionary algorithms: A case study in batch scheduling with recourse." Computers & Chemical Engineering 32, no. 11 (2008): 2706–22. http://dx.doi.org/10.1016/j.compchemeng.2007.09.006.

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26

Pay, Babak Saleck, and Yongjia Song. "Partition-based decomposition algorithms for two-stage Stochastic integer programs with continuous recourse." Annals of Operations Research 284, no. 2 (2017): 583–604. http://dx.doi.org/10.1007/s10479-017-2689-7.

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27

Baranova, Tatiana, Aleksandra Kobicheva, Elena Tokareva, and Charles Bryant. "Online examination session: teachers’ and students’ satisfaction level." E3S Web of Conferences 284 (2021): 09003. http://dx.doi.org/10.1051/e3sconf/202128409003.

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This paper is aimed at defining the satisfaction level of students and teachers with online examination session. To implement the study, we conducted online surveys for 2nd year bachelor students and 1st year master students (N=97) and online interviews with teachers (N=12). The analysis of received data indicated that students felt more satisfied with online examination session than teachers due to a number of reasons. Firstly, elder teachers faced technical problems on some steps of examination session. Secondly, teachers worried about the reliability of students’ testing results as they had

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28

Ross, S., J. Pineau, S. Paquet, and B. Chaib-draa. "Online Planning Algorithms for POMDPs." Journal of Artificial Intelligence Research 32 (July 29, 2008): 663–704. http://dx.doi.org/10.1613/jair.2567.

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Partially Observable Markov Decision Processes (POMDPs) provide a rich framework for sequential decision-making under uncertainty in stochastic domains. However, solving a POMDP is often intractable except for small problems due to their complexity. Here, we focus on online approaches that alleviate the computational complexity by computing good local policies at each decision step during the execution. Online algorithms generally consist of a lookahead search to find the best action to execute at each time step in an environment. Our objectives here are to survey the various existing online P

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29

Ashlagi, Itai, Brendan Lucier, and Moshe Tennenholtz. "Equilibria of Online Scheduling Algorithms." Proceedings of the AAAI Conference on Artificial Intelligence 27, no. 1 (2013): 67–73. http://dx.doi.org/10.1609/aaai.v27i1.8631.

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We describe a model for competitive online scheduling algorithms. Two servers, each with a single observable queue, compete for customers. Upon arrival, each customer strategically chooses the queue with minimal expected wait time. Each scheduler wishes to maximize its number of customers, and can strategically select which scheduling algorithm, such as First-Come-First-Served (FCFS), to use for its queue. This induces a game played by the servers and the customers. We consider a non-Bayesian setting, where servers and customers play to maximize worst-case payoffs. We show that there is a uniq

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30

Sun, Peng, and Teng Zhao. "Deploying Robots and Online Algorithms." Applied Mechanics and Materials 325-326 (June 2013): 1058–61. http://dx.doi.org/10.4028/www.scientific.net/amm.325-326.1058.

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The improvement of 802.11 mesh networks is a robust quagmire. In this work, we show the construction of link-level acknowledgements. In order to answer this grand challenge, we use linear-time epistemologies to disconfirm that 802.11 mesh networks and architecture can collaborate to fix this riddle.

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31

Blum, Avrim, Tuomas Sandholm, and Martin Zinkevich. "Online algorithms for market clearing." Journal of the ACM 53, no. 5 (2006): 845–79. http://dx.doi.org/10.1145/1183907.1183913.

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32

Lagrée, Paul, Olivier Cappé, Bogdan Cautis, and Silviu Maniu. "Algorithms for Online Influencer Marketing." ACM Transactions on Knowledge Discovery from Data 13, no. 1 (2019): 1–30. http://dx.doi.org/10.1145/3274670.

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33

ZHANG, YONG, YUXIN WANG, FRANCIS Y. L. CHIN, and HING-FUNG TING. "COMPETITIVE ALGORITHMS FOR ONLINE PRICING." Discrete Mathematics, Algorithms and Applications 04, no. 02 (2012): 1250015. http://dx.doi.org/10.1142/s1793830912500152.

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Given a seller with m items, a sequence of users {u1, u2, …} come one by one, the seller must set the unit price and assign some items to each user on his/her arrival. Items can be sold fractionally. Each ui has his/her value function vi(⋅) such that vi(x) is the highest unit price ui is willing to pay for x items. The objective is to maximize the revenue by setting the price and number of items for each user. In this paper, we have the following contributions: if the highest value h among all vi(x) is known in advance, we first show the lower bound of the competitive ratio is ⌊ log h⌋/2, then

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34

Devanur, Nikhil R. "Online algorithms with stochastic input." ACM SIGecom Exchanges 10, no. 2 (2011): 40–49. http://dx.doi.org/10.1145/1998549.1998558.

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35

Bienkowski, Marcin, Martin Böhm, Jaroslaw Byrka, et al. "Online Algorithms for Multilevel Aggregation." Operations Research 68, no. 1 (2020): 214–32. http://dx.doi.org/10.1287/opre.2019.1847.

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36

Gatto, Michael, and Peter Widmayer. "On robust online scheduling algorithms." Journal of Scheduling 14, no. 2 (2009): 141–56. http://dx.doi.org/10.1007/s10951-009-0115-y.

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37

Ying, Yiming. "Convergence analysis of online algorithms." Advances in Computational Mathematics 27, no. 3 (2006): 273–91. http://dx.doi.org/10.1007/s10444-005-9002-z.

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38

Ying, Yiming, and Massimiliano Pontil. "Online Gradient Descent Learning Algorithms." Foundations of Computational Mathematics 8, no. 5 (2007): 561–96. http://dx.doi.org/10.1007/s10208-006-0237-y.

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39

Kumar, Sandeep, and Deepak Garg. "Online Financial Algorithms: Competitive Analysis." International Journal of Computer Applications 40, no. 7 (2012): 8–14. http://dx.doi.org/10.5120/4974-7228.

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40

Earle, Michael A. "Vector Solutions for Azimuth." Journal of Navigation 61, no. 3 (2008): 537–45. http://dx.doi.org/10.1017/s037346330800475x.

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Vector based methods applied to navigational problems offer some advantages in the calculation of distance and azimuth. In this paper, the methods of vector analysis are used to develop a variety of expressions for azimuth that are suited to both the syntax of computer algorithms and commercial mathematical software. The solutions presented here do not require recourse to the rules of spherical trigonometry - a distinct advantage when dealing with the spheroid. In the process of preparing this paper, an error of principle that occurred in a previous work was revealed and is repaired here.

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41

Goyal, Shashank, and Diwakar Gupta. "The Online Reservation Problem." Algorithms 13, no. 10 (2020): 241. http://dx.doi.org/10.3390/a13100241.

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Many sharing-economy platforms operate as follows. Owners list the availability of resources, prices, and contract-length limits. Customers propose contract start times and lengths. The owners decide immediately whether to accept or decline each proposal, even if the contract is for a future date. Accepted proposals generate revenue. Declined proposals are lost. At any decision epoch, the owner has no information regarding future proposals. The owner seeks easy-to-implement algorithms that achieve the best competitive ratio (CR). We first derive a lower bound on the CR of any algorithm. We the

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42

Huang, Sabrina Angela, Jeffrey Hancock, and Stephanie Tom Tong. "Folk Theories of Online Dating: Exploring People’s Beliefs About the Online Dating Process and Online Dating Algorithms." Social Media + Society 8, no. 2 (2022): 205630512210895. http://dx.doi.org/10.1177/20563051221089561.

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How do online daters come to understand and make sense of their online dating experiences and the algorithms that underlie online dating platforms? Across two mixed-method studies, we take a metaphoric approach to identify and explore people’s folk theories about traditional dating, online dating, and online dating algorithms. In Study 1, we take a quantitative approach and use an innovative wiki-survey procedure to identify individuals’ folk theories of online dating and their associated themes through content analyses. In Study 2, we take a qualitative approach, exploring participants’ folk

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43

Dixit, Rishabh, Amrit Singh Bedi, Ruchi Tripathi, and Ketan Rajawat. "Online Learning With Inexact Proximal Online Gradient Descent Algorithms." IEEE Transactions on Signal Processing 67, no. 5 (2019): 1338–52. http://dx.doi.org/10.1109/tsp.2018.2890368.

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44

Cerrone, Rosaria. "Are Artificial Intelligence and Machine Learning Shaping a New Risk Management Approach?" International Business Research 16, no. 12 (2023): 82. http://dx.doi.org/10.5539/ibr.v16n12p82.

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Digital revolution is influencing many economic sectors and for a few years banking sector is under a great transformation mainly due to the development and the use of new technologies. The most recent ones are artificial intelligence (AI) with the recourse to advanced algorithms. The main banking services, their offer, but above all, the customer relations have been significantly influenced by the this. The recourse to new channels, the monitoring of risks and the controls of frauds are only some of the applications of machine learning (ML). To manage the increase in financial and non-financi

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45

Rosenkrantz, Daniel J., Giri K. Tayi, and S. S. Ravi. "Obtaining online approximation algorithms for facility dispersion from offline algorithms." Networks 47, no. 4 (2006): 206–17. http://dx.doi.org/10.1002/net.20109.

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46

Hinkel, Sascha, and Jörg Hörnschemeyer. "Die Kritische Online-Edition der Nuntiaturberichte Eugenio Pacellis (1917–1929)." Quellen und Forschungen aus italienischen Archiven und Bibliotheken 101, no. 1 (2021): 28–57. http://dx.doi.org/10.1515/qufiab-2021-0004.

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Abstract Eugenio Pacelli, the later Pope Pius XII, was already considered a leading diplomat of the Holy See when he served as nuncio in Germany. Using the critical online edition of his nuncial reports, digital humanities methodologies will be used to explore which topics dominated his reports, the diplomatic style of his nunciature and whether Pacelli adapted the form and content of his reports to the various recipients. To this end, quantitative methods of textual analysis such as the frequency distribution of types in relation to tokens as well as recourse to key terms and multi-word units

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47

Amos, Patricia Mawusi, P. K. A. Bedu-Addo, and Theresa Antwi. "Experiences of Online Counseling Among Undergraduates in Some Ghanaian Universities." SAGE Open 10, no. 3 (2020): 215824402094184. http://dx.doi.org/10.1177/2158244020941844.

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Counseling is an age-old practice with roots dating back to the 20th century. Twenty-first-century boom in technology has offered new opportunities for counseling practice, making it possible for counselors and clients to interact virtually without recourse to physical meetings. This study sought to investigate students’ experiences of online counseling in some Ghanaian universities. A qualitative phenomenological approach was used to examine the experiences of undergraduate students using online counseling. Five of the student-clients used WhatsApp messaging, two used e-mailing, and one used

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48

Crammer, Koby, and Yoram Singer. "Online Ranking by Projecting." Neural Computation 17, no. 1 (2005): 145–75. http://dx.doi.org/10.1162/0899766052530848.

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We discuss the problem of ranking instances. In our framework, each instance is associated with a rank or a rating, which is an integer in 1 to k. Our goal is to find a rank-prediction rule that assigns each instance a rank that is as close as possible to the instance's true rank. We discuss a group of closely related online algorithms, analyze their performance in the mistake-bound model, and prove their correctness. We describe two sets of experiments, with synthetic data and with the Each Movie data set for collaborative filtering. In the experiments we performed, our algorithms outperform

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49

Liu, Zhicheng, Ling Chen, Hong Chang, Donglei Du, and Xiaoyan Zhang. "Online algorithms for BP functions maximization." Theoretical Computer Science 858 (February 2021): 114–21. http://dx.doi.org/10.1016/j.tcs.2021.01.020.

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50

Höhne, Felix, Sören Schmitt, and Rob van Stee. "SIGACT News Online Algorithms Column 36." ACM SIGACT News 51, no. 4 (2020): 89–107. http://dx.doi.org/10.1145/3444815.3444830.

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In this column, we will discuss some papers in online algorithms that appeared in 2020. As usual, we make no claim at complete coverage here, and have instead made a selection. If we have unaccountably missed your favorite paper and you would like to write about it or about any other topic in online algorithms, please don't hesitate to contact us!

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