Author

D. Rachkovskij

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#machine learning Open access Mar 2026

Multiclass Linear Perceptrons With Multiplicative Margins.

Owing to their simplicity, minimalistic design, and computational efficiency, MMPerc classifiers are promising candidates for conventional machine learning tasks, linear evaluation of deep neural networks, integration with hyperdimensional computing and vector symbolic architecture representations, and deployment in re...

D. Rachkovskij, Evgeny Osipov, O. Volkov et al. · Neural Computation · 0 citations

#artificial intelligence Preprint Aug 2026

Real-Valued Hyperdimensional Sequence Representations with Hadamard Product Binding and Shift Equivariance

Three real-valued position-encoding variants are proposed: a real-valued baseline based on the inverse Fourier transform, a real-valued baseline based on the inverse Fourier transform, and Sinusoid and Cosine-only representations derived from Random Fourier Features.

Kenny Schlegel, D. Rachkovskij, D. Kleyko et al. · 0 citations