most citedImproved large-scale graph learning through ridge spectral sparsification

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cs.LG2026★ 9 cited

Improved large-scale graph learning through ridge spectral sparsification

Daniele Calandriello, Ioannis Koutis, Alessandro Lazaric +1

Graph-based techniques and spectral graph theory have enriched the field of machine learning with a variety of critical advances. A central object in the analysis is the graph Lapl…

cs.LG2026★ 8 cited

Sample Complexity Bounds for Stochastic Shortest Path with a Generative Model

Jean Tarbouriech, Matteo Pirotta, Michal Valko +1

We study the sample complexity of learning an -optimal policy in the Stochastic Shortest Path (SSP) problem. We first derive sample complexity bounds when the learner has acces…