1.9k citations · 6.5k across the 132 of their papers we have counts for
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stat.ML2016★ 241 cited
Global Optimality of Local Search for Low Rank Matrix Recovery
Srinadh Bhojanapalli, Behnam Neyshabur, Nathan Srebro
We show that there are no spurious local minima in the non-convex factorized parametrization of low-rank matrix recovery from incoherent linear measurements. With noisy measurement…
stat.ML2016★ 42 cited
Efficient Distributed Learning with Sparsity
Jialei Wang, Mladen Kolar, Nathan Srebro +1
We propose a novel, efficient approach for distributed sparse learning in high-dimensions, where observations are randomly partitioned across machines. Computationally, at each rou…