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cs.LG2025
Beyond Spectral Clustering: Probabilistic Cuts for Differentiable Graph Partitioning
Ayoub Ghriss
Probabilistic relaxations of graph cuts offer a differentiable alternative to spectral clustering, enabling end-to-end and online learning without eigendecompositions, yet prior wo…
cs.LG2025
Deep Clustering via Probabilistic Ratio-Cut Optimization
Ayoub Ghriss, Claire Monteleoni
We propose a novel approach for optimizing the graph ratio-cut by modeling the binary assignments as random variables. We provide an upper bound on the expected ratio-cut, as well…