29 citations · 106 across the 19 of their papers we have counts for
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cs.DS2020
The smoothed complexity of Frank-Wolfe methods via conditioning of random matrices and polytopes
Luis Rademacher, Chang Shu
Frank-Wolfe methods are popular for optimization over a polytope. One of the reasons is because they do not need projection onto the polytope but only linear optimization over it.…
cs.DS2011★ 2 cited
Lower Bounds for the Average and Smoothed Number of Pareto Optima
Navin Goyal, Luis Rademacher
Smoothed analysis of multiobjective 0-1 linear optimization has drawn considerable attention recently. The number of Pareto-optimal solutions (i.e., solutions with the property tha…
cs.DS2010★ 10 cited
Efficient volume sampling for row/column subset selection
Amit Deshpande, Luis Rademacher
We give efficient algorithms for volume sampling, i.e., for picking -subsets of the rows of any given matrix with probabilities proportional to the squared volumes of the simpli…