# Self-Similar Magneto-Electric Nanocircuit Technology for Probabilistic Inference Engines

@article{Khasanvis2015SelfSimilarMN, title={Self-Similar Magneto-Electric Nanocircuit Technology for Probabilistic Inference Engines}, author={Santosh Khasanvis and Mingyu Li and Mostafizur Rahman and Mohammad Salehi Fashami and Ayan Kumar Biswas and Jayasimha Atulasimha and Supriyo Bandyopadhyay and Csaba Andras Moritz}, journal={IEEE Transactions on Nanotechnology}, year={2015}, volume={14}, pages={980-991} }

Probabilistic graphical models are powerful mathematical formalisms for machine learning and reasoning under uncertainty that are widely used for cognitive computing. However, they cannot be employed efficiently for large problems (with variables in the order of 100K or larger) on conventional systems, due to inefficiencies resulting from layers of abstraction and separation of logic and memory in CMOS implementations. In this paper, we present a magnetoelectric probabilistic technology… CONTINUE READING

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