Author

Konstantinos Slavakis

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#machine learning Preprint Sep 2026

Quantum-Inspired Trainable and Parameter-Efficient Tensor Networks for Image Inpainting

This work introduces quantum-inspired tensor-network circuits as trainable transforms for image inpainting. Among the proposed architectures, the diagonal quantum Fourier transform (QFT) relaxation is invertible with $O(N^2 \log N)$ computational cost for $N\times N$ images, inherently preserving minimum coherence thro...

Shi-Wen An, Konstantinos Slavakis · 0 citations

Jul 2026

Sparse Gaussian-Mixture-Model Q-Functions via Hadamard Overparametrization for Online Reinforcement Learning

This paper develops an online, off-policy policy-iteration framework for reinforcement learning (RL), based on sparse Gaussian-mixture-model Q-functions (S-GMM-QFs), enabling interpretable sparsification through smooth regularization that facilitates Riemannian-based optimization.

Minh Vu, Konstantinos Slavakis · arXiv.org · 0 citations