Showing 21 - 40 results of 69 for search '(((( relevant data algorithm ) OR ( element data algorithm ))) OR ( implicit learning algorithm ))', query time: 0.12s Refine Results
  1. 21

    Improvement of Kernel Principal Component Analysis-Based Approach for Nonlinear Process Monitoring by Data Set Size Reduction Using Class Interval by Mohammed Tahar Habib Kaib (21633176)

    Published 2024
    “…In this paper, the proposed algorithm selects relevant observations from the original data set by utilizing a class interval technique (i.e. histogram) to maintain a bunch of representative samples from each bin. …”
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    Reinforced steering Evolutionary Markov Chain for high-dimensional feature selection by Atiq ur Rehman (3044409)

    Published 2024
    “…<p>The increasing accessibility of extensive datasets has amplified the importance of extracting insights from high-dimensional data. However, the task of selecting relevant features in these high-dimensional spaces is made more difficult due to the curse of dimensionality. …”
  4. 24

    Multi Self-Organizing Map (SOM) Pipeline Architecture for Multi-View Clustering by Saadia Jamil (22045946)

    Published 2024
    “…It calculates the dimension relevance with various data instances. These further place the relevant dimension samples in one group. …”
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    Simple and effective neural-free soft-cluster embeddings for item cold-start recommendations by Shameem A. Puthiya Parambath (14150997)

    Published 2022
    “…CIP can be used in conjunction with relevance ranking metrics like NDCG and MAP to measure the effectiveness of the cold-start recommendation algorithm.…”
  7. 27

    C-3PA: Streaming Conformance, Confidence and Completeness in Prefix-Alignments by Raun, Kristo

    Published 2023
    “…Further, no indication is given of how close the trace is to termination—a highly relevant measure in a streaming setting. This paper introduces a novel approximate streaming conformance checking algorithm that enriches prefix-alignments with confidence and completeness measures. …”
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    Correlation Clustering with Overlaps by Fakhereldine, Amin

    Published 2020
    “…Moreover, we allow the new vertex splitting operation, which allows the resulting clusters to overlap. In other words, data elements (or vertices) will be allowed to be members in more than one cluster instead of limiting them to only one single cluster, as in classical clustering methods. …”
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    masterThesis
  10. 30

    Artificial Intelligence for the Prediction and Early Diagnosis of Pancreatic Cancer: Scoping Review by Zainab Jan (17306614)

    Published 2023
    “…PubMed, Google Scholar, Science Direct, BioRXiv, and MedRxiv were explored to identify relevant articles. Study selection and data extraction were independently conducted by 2 reviewers. …”
  11. 31

    Nested ensemble selection: An effective hybrid feature selection method by Kamalov, Firuz

    Published 2023
    “…It has been shown that while feature selection algorithms are able to distinguish between relevant and irrelevant features, they fail to differentiate between relevant and redundant and correlated features. …”
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    article
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    Frontiers and trends of supply chain optimization in the age of industry 4.0: an operations research perspective by Zhitao Xu (2426023)

    Published 2024
    “…It contributes to the literature by identifying the four OR innovations to typify the recent advances in SC optimization: new modeling conditions, new inputs, new decisions, and new algorithms. Furthermore, we recommend four promising research avenues in this interplay: (1) incorporating new decisions relevant to data-enabled SC decisions, (2) developing data-enabled modeling approaches, (3) preprocessing parameters, and (4) developing data-enabled algorithms. …”
  15. 35

    Recursive Parameter Identification Of A Class Of Nonlinear Systems From Noisy Measurements by Emara-Shabaik, Husam

    Published 2020
    “…The model structure is made up of two linear dynamic elements separated by a nonlinear static one. The nonlinear element is assumed to be of the polynomial type with known order; The identification is based on input/output data where the output is contaminated with measurement noise. …”
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    article
  16. 36

    Impact Of Multidisciplinary Maternal Resuscitation Training Program on Improving the Front-Line Care Provider’s Readiness to Manage Maternal Cardiac Arrest: A Pre-test/Post-test St... by Mohamed Elsayed Saad Aboudonya (18466385)

    Published 2024
    “…Hamad International Training Center not only offers formal resuscitation training like Advanced Life Support Obstetrics and Neonatal Resuscitation Program courses but also ensures the frontline care providers’ readiness for managing cardiac arrest events in Hamad Medical Corporation facilities through regular mock drills and monitoring the relevant Key Performance Indicators (KPIs). The study aimed to explore the impact of a multidisciplinary maternal resuscitation training program and the introduction of the maternal resuscitation algorithm pathway (Figure 1) on the relevant seven KPIs.…”
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    A hybrid approach for XML similarity by Tekli, Joe

    Published 2007
    “…Various algorithms for comparing hierarchically structured data, e.g. …”
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    conferenceObject
  18. 38

    On the complexity of multi-parameterized cluster editing by Abu-Khzam, Faisal

    Published 2017
    “…In other words, Cluster Editing can be solved efficiently when the number of false positives/negatives per single data element is expected to be small compared to the minimum cluster size. …”
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    article
  19. 39

    Artificial Intelligence in Predicting Cardiac Arrest: Scoping Review by Asma Alamgir (18288895)

    Published 2021
    “…Data extracted from the included studies were synthesized narratively.…”
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    A conjugate self-organizing migration (CSOM) and reconciliate multi-agent Markov learning (RMML) based cyborg intelligence mechanism for smart city security by S. Shitharth (12017480)

    Published 2023
    “…Then, the Conjugate Self-Organizing Migration (CSOM) optimization algorithm is deployed to select the most relevant features to train the classifier, which also supports increased detection accuracy. …”