75 citations · 820 across the 81 of their papers we have counts for
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stat.ML2016
Analysis of Kelner and Levin graph sparsification algorithm for a streaming setting
Daniele Calandriello, Alessandro Lazaric, Michal Valko
We derive a new proof to show that the incremental resparsification algorithm proposed by Kelner and Levin (2013) produces a spectral sparsifier in high probability. We rigorously…
stat.ML2016★ 1 cited
Incremental Spectral Sparsification for Large-Scale Graph-Based Semi-Supervised Learning
Daniele Calandriello, Alessandro Lazaric, Michal Valko +1
While the harmonic function solution performs well in many semi-supervised learning (SSL) tasks, it is known to scale poorly with the number of samples. Recent successful and scala…