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Search results for: INTERPRETABLE AI, NEURAL KNOWLEDGE DNA, DECISION TREES, DEEP REINFORCEMENT LEARNING

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Search results for: INTERPRETABLE AI, NEURAL KNOWLEDGE DNA, DECISION TREES, DEEP REINFORCEMENT LEARNING

  • Katedra Elektrotechniki, Systemów Sterowania i Informatyki

    W Katedrze Elektrotechniki, Systemów Sterowania i Informatyki prowadzone są badania w tematyce podstaw elektrotechniki, zaawansowanych systemów sterowania, prototypowania dedykowanych rozwiązań sprzętowych w FPGA. Prowadzone badania skupiają się również na wykorzystaniu zaawansowanych technik analizy komputerowej w systemach sterowania oraz elektrotechniki.

  • KatedrA Chemii Fizycznej

    1.Termodynamika i struktura roztworów, oddziaływania międzycząsteczkowe w roztworach - badania termodynamiczne, spektroskopowe i teoretyczne. 2. Fizykochemiczne podstawy analizy środowiskowej.

  • Katedra Chemii Analitycznej

    Zespół naukowo-badawczy z Katedry Chemii Analitycznej prowadzi badania podstawowe w zakresie: -opracowania nowych procedur analitycznych przeznaczonych do wykrywania, identyfikacji oraz oznaczenia szerokiego spectrum analitów w próbkach różnego typu materiałów charakteryzujących się złożonym a często także zmiennym składem matrycy, -budowy i badań charakterystyki analitycznej nowych typów elektronicznych nosów, -oszacowania wpływu...

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Search results for: INTERPRETABLE AI, NEURAL KNOWLEDGE DNA, DECISION TREES, DEEP REINFORCEMENT LEARNING

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Search results for: INTERPRETABLE AI, NEURAL KNOWLEDGE DNA, DECISION TREES, DEEP REINFORCEMENT LEARNING

  • Adding Interpretability to Neural Knowledge DNA

    Publication

    - CYBERNETICS AND SYSTEMS - Year 2022

    This paper proposes a novel approach that adds the interpretability to Neural Knowledge DNA (NK-DNA) via generating a decision tree. The NK-DNA is a promising knowledge representation approach for acquiring, storing, sharing, and reusing knowledge among machines and computing systems. We introduce the decision tree-based generative method for knowledge extraction and representation to make the NK-DNA more explainable. We examine...

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  • Toward Intelligent Recommendations Using the Neural Knowledge DNA

    Publication

    - CYBERNETICS AND SYSTEMS - Year 2021

    In this paper we propose a novel recommendation approach using past news click data and the Neural Knowledge DNA (NK-DNA). The Neural Knowledge DNA is a novel knowledge representation method designed to support discovering, storing, reusing, improving, and sharing knowledge among machines and computing systems. We examine our approach for news recommendation tasks on the MIND benchmark dataset. By taking advantages of NK-DNA, deep...

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  • Interpretable Deep Learning Model for the Detection and Reconstruction of Dysarthric Speech

    Publication
    • D. Korzekwa
    • R. Barra-Chicote
    • B. Kostek
    • T. Drugman
    • M. Łajszczak

    - Year 2019

    We present a novel deep learning model for the detection and reconstruction of dysarthric speech. We train the model with a multi-task learning technique to jointly solve dysarthria detection and speech reconstruction tasks. The model key feature is a low-dimensional latent space that is meant to encode the properties of dysarthric speech. It is commonly believed that neural networks are black boxes that solve problems but do not...

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  • When Neural Networks Meet Decisional DNA: A Promising New Perspective for Knowledge Representation and Sharing

    Publication

    - CYBERNETICS AND SYSTEMS - Year 2016

    ABSTRACT In this article, we introduce a novel concept combining neural network technology and Decisional DNA for knowledge representation and sharing. Instead of using traditional machine learning and knowledge discovery methods, this approach explores the way of knowledge extraction through deep learning processes based on a domain’s past decisional events captured by Decisional DNA. We compare our approach with kNN (k-nearest...

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  • The Neural Knowledge DNA Based Smart Internet of Things

    Publication

    - CYBERNETICS AND SYSTEMS - Year 2020

    ABSTRACT The Internet of Things (IoT) has gained significant attention from industry as well as academia during the past decade. Smartness, however, remains a substantial challenge for IoT applications. Recent advances in networked sensor technologies, computing, and machine learning have made it possible for building new smart IoT applications. In this paper, we propose a novel approach: the Neural Knowledge DNA based Smart Internet...

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