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Sequential Change-Point Detection via Online Convex Optimization
Entropy, 2018 Sequential change-point detection when the distribution parameters are unknown is a fundamental problem in statistics and machine learning. When the post-change parameters are unknown, we consider a set of detection procedures based on sequential ...
Yang Cao, Liyan Xie, Yao Xie, Huan Xu
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A Review and Characterization of Progressive Visual Analytics
Informatics, 2018 Progressive Visual Analytics (PVA) has gained increasing attention over the past years. It brings the user into the loop during otherwise long-running and non-transparent computations by producing intermediate partial results.
Marco Angelini +3 more
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Formal Analysis of Online Algorithms [PDF]
, 2011 In [2], we showed how viewing online algorithms as reactive systems enables the application of ideas from formal verification to the competitive analysis of online algorithms. Our approach is based on weighted automata, which assign to each input word a cost in R≥0.
Benjamin Aminof +2 more
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Uniform Page Migration Problem in Euclidean Space
Algorithms, 2016 The page migration problem in Euclidean space is revisited. In this problem, online requests occur at any location to access a single page located at a server.
Amanj Khorramian, Akira Matsubayashi
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An Online Algorithm for Smoothed Online Convex Optimization [PDF]
ACM SIGMETRICS Performance Evaluation Review, 2019 We consider Online Convex Optimization (OCO) in the setting where the costs are m-strongly convex and the online learner pays a switching cost for changing decisions between rounds. We show that the recently proposed Online Balanced Descent (OBD) algorithm is constant competitive in this setting, with competitive ratio 3+O(1/m), irrespective of the ...
Goel, Gautam, Wierman, Adam
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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 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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