Deployment of artificial intelligence models on edge devices: A tutorial brief

M Żyliński, A Nassibi, I Rakhmatulin… - … on Circuits and …, 2023 - ieeexplore.ieee.org
Artificial intelligence (AI) on an edge device has enormous potential, including advanced
signal filtering, event detection, optimization in communications and data compression …

The convolutional Tsetlin machine

OC Granmo, S Glimsdal, L Jiao, M Goodwin… - arxiv preprint arxiv …, 2019 - arxiv.org
Convolutional neural networks (CNNs) have obtained astounding successes for important
pattern recognition tasks, but they suffer from high computational complexity and the lack of …

Explainable tsetlin machine framework for fake news detection with credibility score assessment

B Bhattarai, OC Granmo, L Jiao - arxiv preprint arxiv:2105.09114, 2021 - arxiv.org
The proliferation of fake news, ie, news intentionally spread for misinformation, poses a
threat to individuals and society. Despite various fact-checking websites such as PolitiFact …

Field data analysis and risk assessment of gas kick during industrial deepwater drilling process based on supervised learning algorithm

Q Yin, J Yang, M Tyagi, X Zhou, X Hou… - Process Safety and …, 2021 - Elsevier
During industrial offshore deep-water drilling process, gas kick event occurs frequently due
to extremely narrow Mud Weight (MW) window (minimum 0.01 sg) and negligible safety …

Massively parallel and asynchronous tsetlin machine architecture supporting almost constant-time scaling

KD Abeyrathna, B Bhattarai… - International …, 2021 - proceedings.mlr.press
Using logical clauses to represent patterns, Tsetlin Machine (TM) have recently obtained
competitive performance in terms of accuracy, memory footprint, energy, and learning speed …

Extending the tsetlin machine with integer-weighted clauses for increased interpretability

KD Abeyrathna, OC Granmo, M Goodwin - IEEE Access, 2021 - ieeexplore.ieee.org
Building models that are both interpretable and accurate is an unresolved challenge for
many pattern recognition problems. In general, rule-based and linear models lack accuracy …

On the Convergence of Tsetlin Machines for the IDENTITY-and NOT Operators

X Zhang, L Jiao, OC Granmo… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
The Tsetlin Machine (TM) is a recent machine learning algorithm with several distinct
properties, such as interpretability, simplicity, and hardware-friendliness. Although …

Low-power audio keyword spotting using tsetlin machines

J Lei, T Rahman, R Shafik, A Wheeldon… - Journal of Low Power …, 2021 - mdpi.com
The emergence of artificial intelligence (AI) driven keyword spotting (KWS) technologies has
revolutionized human to machine interaction. Yet, the challenge of end-to-end energy …

On the convergence of tsetlin machines for the XOR operator

L Jiao, X Zhang, OC Granmo… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
The Tsetlin Machine (TM) is a novel machine learning algorithm with several distinct
properties, including transparent inference and learning using hardware-near building …

Building concise logical patterns by constraining Tsetlin Machine clause size

KD Abeyrathna, AAO Abouzeid, B Bhattarai… - arxiv preprint arxiv …, 2023 - arxiv.org
Tsetlin machine (TM) is a logic-based machine learning approach with the crucial
advantages of being transparent and hardware-friendly. While TMs match or surpass deep …