Search Results for author: Adrian Vladu

Found 9 papers, 2 papers with code

AC/DC: Alternating Compressed/DeCompressed Training of Deep Neural Networks

1 code implementation NeurIPS 2021 Alexandra Peste, Eugenia Iofinova, Adrian Vladu, Dan Alistarh

The increasing computational requirements of deep neural networks (DNNs) have led to significant interest in obtaining DNN models that are sparse, yet accurate.

Network Pruning

Decomposable Submodular Function Minimization via Maximum Flow

no code implementations5 Mar 2021 Kyriakos Axiotis, Adam Karczmarz, Anish Mukherjee, Piotr Sankowski, Adrian Vladu

This paper bridges discrete and continuous optimization approaches for decomposable submodular function minimization, in both the standard and parametric settings.

Projection-Free Bandit Optimization with Privacy Guarantees

no code implementations22 Dec 2020 Alina Ene, Huy L. Nguyen, Adrian Vladu

We design differentially private algorithms for the bandit convex optimization problem in the projection-free setting.

Improved Convergence for $\ell_\infty$ and $\ell_1$ Regression via Iteratively Reweighted Least Squares

no code implementations18 Feb 2019 Alina Ene, Adrian Vladu

The iteratively reweighted least squares method (IRLS) is a popular technique used in practice for solving regression problems.

Data Structures and Algorithms

A Parallel Double Greedy Algorithm for Submodular Maximization

no code implementations4 Dec 2018 Alina Ene, Huy L. Nguyen, Adrian Vladu

We study parallel algorithms for the problem of maximizing a non-negative submodular function.

Towards Deep Learning Models Resistant to Adversarial Attacks

45 code implementations ICLR 2018 Aleksander Madry, Aleksandar Makelov, Ludwig Schmidt, Dimitris Tsipras, Adrian Vladu

Its principled nature also enables us to identify methods for both training and attacking neural networks that are reliable and, in a certain sense, universal.

Adversarial Attack Adversarial Defense +6

Multidimensional Binary Search for Contextual Decision-Making

no code implementations2 Nov 2016 Ilan Lobel, Renato Paes Leme, Adrian Vladu

We consider a multidimensional search problem that is motivated by questions in contextual decision-making, such as dynamic pricing and personalized medicine.

Decision Making

Tight Bounds for Approximate Carathéodory and Beyond

no code implementations ICML 2017 Vahab Mirrokni, Renato Paes Leme, Adrian Vladu, Sam Chiu-wai Wong

We give a deterministic nearly-linear time algorithm for approximating any point inside a convex polytope with a sparse convex combination of the polytope's vertices.

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