Author

Alex Yakovlev

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Preprint Aug 2026

A Real-Time Tsetlin Machine-based Non-intrusive Load Monitoring System on MCUs

Non-Intrusive Load Monitoring (NILM) systems estimate individual appliance energy consumption from a single aggregate meter, without requiring separate sensors for each device. By installing a single meter that measures a building's total electricity consumption, NILM algorithms can determine the active status of each...

Han Wu, Tian-Hang Tan, Shengyu Duan et al. · 0 citations

#machine learning Preprint Oct 2026

CRISP: A Framework for Clause-Reconstructed Interpretable NeuroSymbolic Propositions

Deep neural networks achieve high accuracy through layered numerical transformations, yet their decisions remain difficult to audit because decision evidence is encoded in hidden activations rather than explicit rules. This paper introduces CRISP, a framework that reconstructs the last-layer activation vector (LLAV) of...

Alex Chan, Shafi Muhtasim Chowdhury, Ekin Can Erkuş et al. · 0 citations

Open access Jul 2026

Sensor-Modality-Aware Human Activity Recognition with the Convolutional Tsetlin Machine: Interpretable and Resource-Efficient Neuro-Symbolic Learning

This work investigates the Convolutional Tsetlin Machine for multimodal HAR using only the raw inertial signals of the UCI-HAR dataset, rather than its pre-computed 561-feature representation, to address predictive performance, interpretability and suitability for embedded and mobile platforms.

O. Tarasyuk, A. Gorbenko, O. Gordieiev et al. · Italian National Conference... · 0 citations