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Special Issue “1st Online Conference on Algorithms (IOCA2021)”
Algorithms, 2022 This Special Issue of Algorithms is dedicated to the 1st Online Conference on Algorithms (IOCA 2021), which was held completely online from 27 September to 10 October 2021 [...]
Frank Werner
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Adaptive Online Learning for the Autoregressive Integrated Moving Average Models
Mathematics, 2021 This paper addresses the problem of predicting time series data using the autoregressive integrated moving average (ARIMA) model in an online manner. Existing algorithms require model selection, which is time consuming and unsuitable for the setting of ...
Weijia Shao +3 more
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IEEE Access, 2019 Currently, Storage-as-a-Service (StaaS) clouds offer multiple data storage and access pricing options which usually consist of hot and cold tiers. The cold tier storage option offers a lower storage price while the hot tier storage option offers a lower ...
Mingyu Liu, Li Pan, Shijun Liu
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An Online Minorization-Maximization Algorithm
, 2023 AbstractModern statistical and machine learning settings often involve high data volume and data streaming, which require the development of online estimation algorithms. The online Expectation–Maximization (EM) algorithm extends the popular EM algorithm to this setting, via a stochastic approximation approach.We show that an online version of the ...
Nguyen, Hien +3 more
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An Analysis of the Most Used Machine Learning Algorithms for Online Fraud Detection [PDF]
Informatică economică, 2019 Today illegal activities regarding online financial transactions have become increasingly complex and borderless, resulting in huge financial losses for both sides, customers and organizations.
Elena-Adriana MINASTIREANU +1 more
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Landscape and Taxonomy of Online Parser-Supported Log Anomaly Detection Methods
IEEE AccessAs production system estates become larger and more complex, ensuring stability through traditional monitoring approaches becomes more challenging. Rule-based monitoring is common in industrial settings, but it has limitations.
Scott Lupton +3 more
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Randomized Competitive Analysis for Two Server Problems
Algorithms, 2008 We prove that there exists a randomized online algorithm for the 2-server 3-point problem whose expected competitive ratio is at most 1.5897. This is the first nontrivial upper bound for randomized k-server algorithms in a general metric space whose ...
Jun Kawahara, Kazuo Iwama, Wolfgang Bein
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EURO Journal on Computational Optimization, 2015 In a k-min search problem, a player wants to buy k units of an asset with the objective of minimizing the total buying cost. At each time period t, a price qt is observed, and the player has to decide on the number of units to buy without any knowledge ...
Javeria Iqbal, Iftikhar Ahmad
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Online Learning With Inexact Proximal Online Gradient Descent Algorithms [PDF]
IEEE Transactions on Signal Processing, 2019 We consider non-differentiable dynamic optimization problems such as those arising in robotics and subspace tracking. Given the computational constraints and the time-varying nature of the problem, a low-complexity algorithm is desirable, while the accuracy of the solution may only increase slowly over time.
Rishabh Dixit +3 more
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The Scary Black Box: AI Driven Recommender Algorithms as The Most Powerful Social Force
Etnoantropološki Problemi, 2022 Recommender algorithms shape societies by individually exposing online users to everything they see, hear and feel in real time. We examine the development of recommender algorithms from the Page Rank and advertising platforms to social media trending ...
Ljubiša Bojić +2 more
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