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cs.CV2023
Projected Stochastic Gradient Descent with Quantum Annealed Binary Gradients
Maximilian Krahn, Michele Sasdelli, Fengyi Yang +4
We present, QP-SBGD, a novel layer-wise stochastic optimiser tailored towards training neural networks with binary weights, known as binary neural networks (BNNs), on quantum hardw…
cs.CV2021
Convex Joint Graph Matching and Clustering via Semidefinite Relaxations
Maximilian Krahn, Florian Bernard, Vladislav Golyanik
This paper proposes a new algorithm for simultaneous graph matching and clustering. For the first time in the literature, these two problems are solved jointly and synergetically w…