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  1. No Access

    Chapter and Conference Paper

    Deep Learning Based Solution for Appliance Operational State Detection and Power Estimation in Non-intrusive Load Monitoring

    This paper introduces a novel NILM algorithm that utilizes deep learning Temporal Convolutional Networks (TCN) for the regression and classification NILM tasks. The deep TCN layers in the proposed architecture...

    Mohammad Kaosain Akbar, Manar Amayri in Advances and Trends in Artificial Intellig… (2023)

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    Chapter and Conference Paper

    A Selective Supervised Latent Beta-Liouville Allocation for Document Classification

    We propose a novel model, selective supervised Latent Beta-Liouville (ssLBLA), that improves the performance and generative process of supervised probabilistic topic models with a more flexible prior and simpl...

    Zhiwen Luo, Manar Amayri, Wentao Fan in Advances and Trends in Artificial Intellig… (2023)

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    Chapter and Conference Paper

    Enhanced Energy Characterization and Feature Selection Using Explainable Non-parametric AGGMM

    In this paper, we propose an asymmetric generalized Gaussian mixture model (AGGMM) with simultaneous feature selection for efficient and interpretable energy characterization in the context of demand response ...

    Hussein Al-Bazzaz, Muhammad Azam in Recent Challenges in Intelligent Informati… (2023)

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    Chapter and Conference Paper

    Novel Topic Models for Parallel Topics Extraction from Multilingual Text

    In this work, we propose novel topic models to extract topics from multilingual documents. We add more flexibility to conventional LDA by relaxing some constraints in its prior. We apply other alternative prio...

    Kamal Maanicshah, Narges Manouchehri in Intelligent Information and Database Syste… (2023)

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    Chapter and Conference Paper

    Stochastic Expectation Propagation Learning for Unsupervised Feature Selection

    We introduce a statistical procedure for the simultaneous clustering and feature selection of positive vectors. The proposed method is based on well-principled infinite generalized inverted Dirichlet (GID) mix...

    Wentao Fan, Manar Amayri, Nizar Bouguila in Advances in Computational Collective Intel… (2022)

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    Chapter and Conference Paper

    A Generalized Inverted Dirichlet Predictive Model for Activity Recognition Using Small Training Data

    In this paper, we develop the predictive distribution of the generalized inverted Dirichlet (GID) mixture model using local variational inference. The main goal is to be able to tackle classification problems ...

    Jiaxun Guo, Manar Amayri, Wentao Fan in Advances and Trends in Artificial Intellig… (2022)

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    Chapter and Conference Paper

    Interactive Generalized Dirichlet Mixture Allocation Model

    A lot of efforts have been put in recent times for research in the field of natural language processing. Extracting topics is undoubtedly one of the most important tasks in this area of research. Latent Dirich...

    Kamal Maanicshah, Manar Amayri in Structural, Syntactic, and Statistical Pat… (2022)