Search Results - 68T05 Learning and adaptive systems in artificial intelligence

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  1. 1

    The role of diversity and ensemble learning in credit card fraud detection by Paldino, Gian Marco, Lebichot, Bertrand, Le Borgne, Yann-Aël, Siblini, Wissam, Oblé, Frédéric, Boracchi, Giacomo, Bontempi, Gianluca

    ISSN: 1862-5347, 1862-5355
    Published: Germany Springer Nature B.V 01.03.2024
    “… The ability to precisely detect fraudulent transactions is increasingly important, and machine learning models are now a key component of the detection process…”
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    Journal Article
  2. 2

    Machine learning approach for phishing website detection : A literature survey by Patil, Rutuja R., Kaur, Gagandeep, Jain, Himank, Tiwari, Ayush, Joshi, Soham, Rao, Keshav, Sharma, Amit

    ISSN: 0972-0529, 2169-0065
    Published: Taylor & Francis 03.04.2022
    “… Timely detection of phishing attacks has become more crucial than ever. Hence in this paper, we provide a thorough literature survey of the various machine learning methods used for phishing detection…”
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    Journal Article
  3. 3

    Artificial Intelligence: A Child’s Play by Kashyap, Ravi

    ISSN: 0040-1625, 1873-5509
    Published: Elsevier Inc 01.05.2021
    Published in Technological forecasting & social change (01.05.2021)
    “…•Conceptual modifications to Turing Test and Searle's Chinese room argument. We discuss the objectives of any endeavor in creating artificial intelligence, AI, and provide a possible alternative…”
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    Journal Article
  4. 4

    Learning customized and optimized lists of rules with mathematical programming by Rudin, Cynthia, Ertekin, Şeyda

    ISSN: 1867-2949, 1867-2957
    Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.12.2018
    Published in Mathematical programming computation (01.12.2018)
    “…We introduce a mathematical programming approach to building rule lists, which are a type of interpretable, nonlinear, and logical machine learning classifier involving IF-THEN rules…”
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  5. 5

    Creating herd behavior by virtual agents using neural networks by Markowska-Kaczmar, Urszula, Slimak, Adrian

    ISSN: 1877-0509, 1877-0509
    Published: Elsevier B.V 2021
    Published in Procedia computer science (2021)
    “…The paper focuses on simulating an artificial life in which neural networks (recurrent (RNN) and Long Short Term Memory…”
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  6. 6

    Utterance Style Transfer Using Deep Models by Popek, Daniel, Markowska-Kaczmar, Urszula

    ISSN: 1877-0509, 1877-0509
    Published: Elsevier B.V 2021
    Published in Procedia computer science (2021)
    “… Siamese network is responsible for learning the content embeddings. The models can perform the style transfer between any two speakers with a satisfactory result…”
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  7. 7

    An Intelligent System for Identifying Influential Words in Real-Estate Classifieds by Abdallah Sherief

    ISSN: 0334-1860, 2191-026X
    Published: De Gruyter 01.04.2018
    Published in Journal of intelligent systems (01.04.2018)
    “…This paper focuses on the problem of quantifying how certain words in a text affect, positively or negatively, some numeric signal. These words can lead to…”
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  8. 8

    Mining Dynamics: Using Data Mining Techniques to Analyze Multi-agent Learning by Sherief, Abdallah

    ISSN: 0334-1860, 2191-026X
    Published: Berlin De Gruyter 01.10.2017
    Published in Journal of intelligent systems (01.10.2017)
    “…Analyzing the learning dynamics in multi-agent systems (MASs) has received growing attention in recent years…”
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    Journal Article
  9. 9

    When unlearning helps by Baliga, Ganesh, Case, John, Merkle, Wolfgang, Stephan, Frank, Wiehagen, Rolf

    ISSN: 0890-5401, 1090-2651
    Published: San Diego, CA Elsevier Inc 01.05.2008
    Published in Information and computation (01.05.2008)
    “…Overregularization seen in child language learning, for example, verb tense constructs, involves abandoning correct behaviours for incorrect ones and later reverting to correct behaviours…”
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  10. 10

    Stability of Neural Networks for Slightly Perturbed Training Data Sets by Berhane, Indrias, Srinivasan, C.

    ISSN: 0361-0926, 1532-415X
    Published: Philadelphia, PA Taylor & Francis Group 31.12.2004
    “…In learning models of artificial neural networks, that randomness comes from the distribution of the training data…”
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  11. 11

    Realizing self-adaptive systems via online reinforcement learning and feature-model-guided exploration by Metzger, Andreas, Quinton, Clément, Mann, Zoltán Ádám, Baresi, Luciano, Pohl, Klaus

    ISSN: 0010-485X, 1436-5057
    Published: Vienna Springer Vienna 01.04.2024
    Published in Computing (01.04.2024)
    “… To realize self-adaptive systems in the presence of design time uncertainty, online machine learning, i.e…”
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  12. 12

    Deep Reinforcement Learning from Self-Play in No-limit Texas Hold'em Poker by Pricope, T.-V.

    ISSN: 1224-869X, 2065-9601
    Published: Babes-Bolyai University, Cluj-Napoca 15.12.2021
    “… This particular set of problems is challenging due to the random factor that makes even adaptive methods fail to correctly model the problem and find the best solution…”
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  13. 13

    Adaptive vertical federated learning via feature map transferring in mobile edge computing by Li, Yuanzhang, Sha, Tianchi, Baker, Thar, Yu, Xiao, Shi, Zhiwei, Hu, Sikang

    ISSN: 0010-485X, 1436-5057
    Published: Vienna Springer Vienna 01.04.2024
    Published in Computing (01.04.2024)
    “…To bring more intelligence to edge systems, Federated Learning (FL) is proposed to provide a privacy-preserving mechanism to train a globally shared model by utilizing a massive amount of user-generated data on devices…”
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  14. 14

    An AI and 6G-IoT enabled computational framework for intelligent medical resource allocation and adaptive personalized healthcare by Almadhor, Ahmad, Ayari, Mohamed, Alqahtani, Abdullah, Al Hejaili, Abdullah, Bouallegue, Belgacem, Juanatas, Roben A., Sampedro, Gabriel Avelino

    ISSN: 0010-485X, 1436-5057
    Published: Vienna Springer Vienna 01.12.2025
    Published in Computing (01.12.2025)
    “…The integration of sixth-generation (6G) networks with the Internet of Things (IoT) is transforming smart healthcare by enabling ultra-low latency, high bandwidth, and intelligent connectivity across medical systems…”
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  15. 15

    An adaptive online reinforcement learning approach for optimizing computation offloading in connected vehicle networks by Mohammadi, Laya, Khajehvand, Vahid, Nobandegani, Khashayar Salehi, Zeinali, Esmaeil

    ISSN: 0010-485X, 1436-5057
    Published: Vienna Springer Vienna 01.08.2025
    Published in Computing (01.08.2025)
    “… This paper proposes a model-free, adaptive online reinforcement learning approach based on the Q-learning algorithm for computation offloading in connected vehicle networks (CVNs…”
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  16. 16

    Scene-adaptive radar tracking with deep reinforcement learning by Stephan, Michael, Servadei, Lorenzo, Arjona-Medina, José, Santra, Avik, Wille, Robert, Fischer, Georg

    ISSN: 2666-8270, 2666-8270
    Published: Elsevier Ltd 15.06.2022
    Published in Machine learning with applications (15.06.2022)
    “… In this context, scene-adaptive radar processing refers to algorithms that can sense, understand and learn information related to detected targets as well as the environment and adapt its tracking…”
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  17. 17

    Improving battery voltage prediction in an electric bicycle using altitude measurements and kernel adaptive filters by Tobar, Felipe, Castro, Iván, Silva, Jorge, Orchard, Marcos

    ISSN: 0167-8655, 1872-7344
    Published: Amsterdam Elsevier B.V 01.04.2018
    Published in Pattern recognition letters (01.04.2018)
    “…•Novel kernel adaptive filter outperforms existing ones in electric bicycle case study…”
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  18. 18

    Robot motion adaptation through user intervention and reinforcement learning by Jevtić, Aleksandar, Colomé, Adrià, Alenyà, Guillem, Torras, Carme

    ISSN: 0167-8655, 1872-7344
    Published: Amsterdam Elsevier B.V 01.04.2018
    Published in Pattern recognition letters (01.04.2018)
    “…•Three versions of an interactive framework for robot motion learning are proposed…”
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  19. 19

    On the antiderivatives of xp/(1 − x) with an application to optimize loss functions for classification with neural networks by Knoblauch, Andreas

    ISSN: 1012-2443, 1573-7470
    Published: Cham Springer International Publishing 01.04.2022
    “…Supervised learning in neural nets means optimizing synaptic weights W such that outputs y ( x ; W…”
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  20. 20

    pART2: using adaptive resonance theory for web caching prefetching by Feng, Wenying, Kazi, Toufiq Hossain, Hu, Gongzhu, Huang, Jimmy Xiangji

    ISSN: 0941-0643, 1433-3058
    Published: London Springer London 01.12.2017
    Published in Neural computing & applications (01.12.2017)
    “… In this paper, we propose a new prefetching model pART2, which is based on the adaptive resonance theory (ART…”
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    Journal Article