Adrian Vladu

Publication Activity (10 Years)

Years Active: 2010-2023
Publications (10 Years): 40

Top Topics

Convex Optimization

Reweighted Least Squares

Top Venues

Publications

Ilia Markov, Adrian Vladu, Qi Guo, Dan Alistarh
Quantized Distributed Training of Large Models with Convergence Guarantees. CoRR (2023)
Lucas Pesenti, Adrian Vladu
Discrepancy Minimization via Regularization. SODA (2023)
Adrian Vladu
Interior Point Methods with a Gradient Oracle. CoRR (2023)
Alexandra Peste, Adrian Vladu, Eldar Kurtic, Christoph H. Lampert, Dan Alistarh
CrAM: A Compression-Aware Minimizer. ICLR (2023)
Ilia Markov, Adrian Vladu, Qi Guo, Dan Alistarh
Quantized Distributed Training of Large Models with Convergence Guarantees. ICML (2023)
Adrian Vladu
Interior Point Methods with a Gradient Oracle. STOC (2023)
Kyriakos Axiotis, Aleksander Madry, Adrian Vladu
Faster Sparse Minimum Cost Flow by Electrical Flow Localization. FOCS (2022)
Alexandra Peste, Adrian Vladu, Dan Alistarh, Christoph H. Lampert
CrAM: A Compression-Aware Minimizer. CoRR (2022)
Lucas Pesenti, Adrian Vladu
Discrepancy Minimization via Regularization. CoRR (2022)
Kyriakos Axiotis, Aleksander Madry, Adrian Vladu
Faster Sparse Minimum Cost Flow by Electrical Flow Localization. FOCS (2021)
Kyriakos Axiotis, Adam Karczmarz, Anish Mukherjee, Piotr Sankowski, Adrian Vladu
Decomposable Submodular Function Minimization via Maximum Flow. ICML (2021)
Kyriakos Axiotis, Aleksander Madry, Adrian Vladu
Faster Sparse Minimum Cost Flow by Electrical Flow Localization. CoRR (2021)
Alina Ene, Huy L. Nguyen, Adrian Vladu
Projection-Free Bandit Optimization with Privacy Guarantees. AAAI (2021)
Alexandra Peste, Eugenia Iofinova, Adrian Vladu, Dan Alistarh
AC/DC: Alternating Compressed/DeCompressed Training of Deep Neural Networks. NeurIPS (2021)
Alexandra Peste, Eugenia Iofinova, Adrian Vladu, Dan Alistarh
AC/DC: Alternating Compressed/DeCompressed Training of Deep Neural Networks. CoRR (2021)
Kyriakos Axiotis, Adam Karczmarz, Anish Mukherjee, Piotr Sankowski, Adrian Vladu
Decomposable Submodular Function Minimization via Maximum Flow. CoRR (2021)
Alina Ene, Huy L. Nguyen, Adrian Vladu
Adaptive Gradient Methods for Constrained Convex Optimization and Variational Inequalities. AAAI (2021)
Kyriakos Axiotis, Aleksander Madry, Adrian Vladu
Circulation Control for Faster Minimum Cost Flow in Unit-Capacity Graphs. CoRR (2020)
Alina Ene, Huy L. Nguyen, Adrian Vladu
Projection-Free Bandit Optimization with Privacy Guarantees. CoRR (2020)
Kyriakos Axiotis, Aleksander Madry, Adrian Vladu
Circulation Control for Faster Minimum Cost Flow in Unit-Capacity Graphs. FOCS (2020)
Alina Ene, Huy L. Nguyen, Adrian Vladu
Adaptive Gradient Methods for Constrained Convex Optimization. CoRR (2020)
Alina Ene, Adrian Vladu
Improved Convergence for $\ell_1$ and $\ell_∞$ Regression via Iteratively Reweighted Least Squares. ICML (2019)
Alina Ene, Adrian Vladu
Improved Convergence for $\ell_\infty$ and $\ell_1$ Regression via Iteratively Reweighted Least Squares. CoRR (2019)
Alina Ene, Huy L. Nguyen, Adrian Vladu
Submodular maximization with matroid and packing constraints in parallel. STOC (2019)
Alina Ene, Huy L. Nguyen, Adrian Vladu
A Parallel Double Greedy Algorithm for Submodular Maximization. CoRR (2018)
Alina Ene, Huy L. Nguyen, Adrian Vladu
Submodular Maximization with Packing Constraints in Parallel. CoRR (2018)
Aleksander Madry, Aleksandar Makelov, Ludwig Schmidt, Dimitris Tsipras, Adrian Vladu
Towards Deep Learning Models Resistant to Adversarial Attacks. ICLR (Poster) (2018)
Ilan Lobel, Renato Paes Leme, Adrian Vladu
Multidimensional Binary Search for Contextual Decision-Making. Oper. Res. 66 (5) (2018)
Michael B. Cohen, Aleksander Madry, Piotr Sankowski, Adrian Vladu
) Time (Extended Abstract). SODA (2017)
Ilan Lobel, Renato Paes Leme, Adrian Vladu
Multidimensional Binary Search for Contextual Decision-Making. EC (2017)
Michael B. Cohen, Aleksander Madry, Dimitris Tsipras, Adrian Vladu
Matrix Scaling and Balancing via Box Constrained Newton's Method and Interior Point Methods. CoRR (2017)
Michael B. Cohen, Aleksander Madry, Dimitris Tsipras, Adrian Vladu
Matrix Scaling and Balancing via Box Constrained Newton's Method and Interior Point Methods. FOCS (2017)
Aleksander Madry, Aleksandar Makelov, Ludwig Schmidt, Dimitris Tsipras, Adrian Vladu
Towards Deep Learning Models Resistant to Adversarial Attacks. CoRR (2017)
Michael B. Cohen, Jonathan A. Kelner, John Peebles, Richard Peng, Anup B. Rao, Aaron Sidford, Adrian Vladu
Almost-linear-time algorithms for Markov chains and new spectral primitives for directed graphs. STOC (2017)
Vahab S. Mirrokni, Renato Paes Leme, Adrian Vladu, Sam Chiu-wai Wong
Tight Bounds for Approximate Carathéodory and Beyond. ICML (2017)
Michael B. Cohen, Aleksander Madry, Piotr Sankowski, Adrian Vladu
log W) Time. CoRR (2016)
Michael B. Cohen, Jonathan A. Kelner, John Peebles, Richard Peng, Anup B. Rao, Aaron Sidford, Adrian Vladu
Almost-Linear-Time Algorithms for Markov Chains and New Spectral Primitives for Directed Graphs. CoRR (2016)
Michael B. Cohen, Jonathan A. Kelner, John Peebles, Richard Peng, Aaron Sidford, Adrian Vladu
Faster Algorithms for Computing the Stationary Distribution, Simulating Random Walks, and More. CoRR (2016)
Ilan Lobel, Renato Paes Leme, Adrian Vladu
Multidimensional Binary Search for Contextual Decision-Making. CoRR (2016)
Michael B. Cohen, Jonathan A. Kelner, John Peebles, Richard Peng, Aaron Sidford, Adrian Vladu
Faster Algorithms for Computing the Stationary Distribution, Simulating Random Walks, and More. FOCS (2016)
Vahab S. Mirrokni, Renato Paes Leme, Adrian Vladu, Sam Chiu-wai Wong
Tight Bounds for Approximate Carathéodory and Beyond. CoRR (2015)
Dan Alistarh, Rati Gelashvili, Adrian Vladu
How To Elect a Leader Faster than a Tournament. PODC (2015)
Gary L. Miller, Richard Peng, Adrian Vladu, Shen Chen Xu
Improved Parallel Algorithms for Spanners and Hopsets. SPAA (2015)
Dan Alistarh, Rati Gelashvili, Adrian Vladu
How to Elect a Leader Faster than a Tournament. CoRR (2014)
Claire Mathieu, Adrian Vladu
Online Ranking for Tournament Graphs. WAOA (2010)