1.5k citations · 1.6k across the 23 of their papers we have counts for
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Quasi-Self-Concordant Optimization with Lewis Weights
Alina Ene, Ta Duy Nguyen, Adrian Vladu
In this paper, we study the problem for a quasi-self-concordant function , where are $…
Adaptive Sparsification for Linear Programming
Étienne Objois, Adrian Vladu
We introduce a generic framework for solving linear programs (LPs) with many constraints via adaptive sparsification. Our approach provides a principled generalization…
Improved Regression via Iteratively Reweighted Least Squares
Alina Ene, Ta Duy Nguyen, Adrian Vladu
We introduce fast algorithms for solving regression problems using the iteratively reweighted least squares (IRLS) method. Our approach achieves state-of-the-art iterati…
Fixed-Parameter Tractable Submodular Maximization over a Matroid
Shamisa Nematollahi, Adrian Vladu, Junyao Zhao
In this paper, we design fixed-parameter tractable (FPT) algorithms for (non-monotone) submodular maximization subject to a matroid constraint, where the matroid rank is treate…
Solving Linear Programs with Differential Privacy
Alina Ene, Huy Le Nguyen, Ta Duy Nguyen +1
We study the problem of solving linear programs of the form , with differential privacy. For homogeneous LPs , we give an efficient -differentially…
Breaking the Barrier of Self-Concordant Barriers: Faster Interior Point Methods for M-Matrices
Adrian Vladu
We study two fundamental optimization problems: (1) scaling a symmetric positive definite matrix by a positive diagonal matrix so that the resulting matrix has row and column sums…
Approximating Norms of Non-Negative Matrices in Nearly-Linear Time
Étienne Objois, Adrian Vladu
We provide the first nearly-linear time algorithm for approximating -norms of non-negative matrices, for . Our algorithm returns a $(1-\var…