FastOmniTMAE parallelizes clause learning in Tsetlin Machine autoencoders to achieve up to 5x faster training with comparable embedding quality and low-footprint FPGA deployment.
Convergence analysis of Tsetlin machines under noise-free and noisy training conditions: From 2 bits to k bits
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FastOmniTMAE: Parallel Clause Learning for Scalable and Hardware-Efficient Tsetlin Embeddings
FastOmniTMAE parallelizes clause learning in Tsetlin Machine autoencoders to achieve up to 5x faster training with comparable embedding quality and low-footprint FPGA deployment.