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Parallel Online Algorithms for the Bin Packing Problem
We study parallel online algorithms: For some fixed integer k , a collective of k parallel processes that perform online decisions on the same...
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Online Algorithms for Spectral Hypergraph Sparsification
We provide the first online algorithm for spectral hypergraph sparsification. In the online setting, hyperedges with positive weights are arriving in...
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Better Algorithms for Online Bin Stretching via Computer Search
Online Bin Stretching is a problem closely related to Online Bin Packing and various scheduling problems. There is extensive history of computer...
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Online local fisher risk minimization: a new online kernel method for online classification
This study presents a new online kernel algorithm for online classification, called the online local Fisher rick minimization (OLFRM). Motivated by...
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Efficient approximation and privacy preservation algorithms for real time online evolving data streams
Because of the processing of continuous unstructured large streams of data, mining real-time streaming data is a more challenging research issue than...
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Online diagnosis of COVID-19 from chest radiography images by using deep learning algorithms
The COVID-19 outbreak, which has a devastating impact on the health and well-being of the global population, is a respiratory disease. It is vital to...
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Online State Exploration: Competitive Worst Case and Learning-Augmented Algorithms
This paper introduces the online state exploration problem. In the problem, there is a hidden d-dimensional target state. We are given a distance...
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Privacy Preserving Algorithms for Distributed Online Learning
In this chapter, we focus on introducing a distributed online optimization problem for a set of nodes communicating on a time-varying unbalanced...
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Online AutoML: an adaptive AutoML framework for online learning
Automated Machine Learning (AutoML) has been used successfully in settings where the learning task is assumed to be static. In many real-world...
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Challenges and approaches when realizing online surface inspection systems with deep learning algorithms
Using deep learning in complex online surface inspection systems is challenging due to different framework conditions. First, time restrictions in...
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Online Algorithms for Prize-Collecting Optimization Problems
Many real-world optimization problems are online by nature, requiring provably-good decisions that need to be made in the present without knowing the...
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Relaxing the Irrevocability Requirement for Online Graph Algorithms
Online graph problems are considered in models where the irrevocability requirement is relaxed. We consider the Late Accept model, where a request...
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OEC: an online ensemble classifier for mining data streams with noisy labels
Distilling actionable patterns from large-scale streaming data in the presence of concept drift is a challenging problem, especially when data is...
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Preliminaries of Online Algorithms and Competitive Analysis
This chapter presents the basic ideas of online algorithms and competitive analysis. It aims to establish the foundation for the online algorithms...
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An Experimental Comparison of Batch and Online Machine Learning Algorithms
This chapter presents the results of the experimental analyses. The first study (Sect. 9.1) examines the use of Batch Machine Learning (BML) and...
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Quantifying polarization in online political discourse
In an era of increasing political polarization, its analysis becomes crucial for the understanding of democratic dynamics. This paper presents a...
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Correlated Online k-Nearest Neighbors Regressor Chain for Online Multi-output Regression
Online multi-output regression is a crucial task in machine learning with applications in various domains such as environmental monitoring, energy...
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WALCOM: Algorithms and Computation 18th International Conference and Workshops on Algorithms and Computation, WALCOM 2024, Kanazawa, Japan, March 18–20, 2024, Proceedings
This book constitutes the refereed proceedings of the 18th International Conference and Workshops on Algorithms and Computation, WALCOM 2024, held in...
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Fast and robust online-learning facial expression recognition and innate novelty detection capability of extreme learning algorithms
Facial Expression Recognition (FER) is a task usually framed as predicting an emotional state given a facial image. FER has received numerous...
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Novel Initialization Functions for Metaheuristic-Based Online Virtual Network Embedding
Virtual network embedding (VNE) is the process of allocating resources in a substrate (i.e. physical) network to support virtual networks optimally....
