| 2026 | ESA | Adaptive Sparsification for Linear Programming. | tienne Objois, Adrian Vladu |
| 2026 | STACS | Approximating q → p Norms of Non-Negative Matrices in Nearly-Linear Time. | tienne Objois, Adrian Vladu |
| 2025 | STOC | Breaking the Barrier of Self-Concordant Barriers: Faster Interior Point Methods for M-Matrices. | Adrian Vladu |
| 2023 | ICLR | CrAM: A Compression-Aware Minimizer. | Alexandra Peste, Adrian Vladu, Eldar Kurtic, Christoph H. Lampert, Dan Alistarh |
| 2023 | ICML | Quantized Distributed Training of Large Models with Convergence Guarantees. | Ilia Markov, Adrian Vladu, Qi Guo, Dan Alistarh |
| 2023 | SODA | Discrepancy Minimization via Regularization. | Lucas Pesenti, Adrian Vladu |
| 2023 | STOC | Interior Point Methods with a Gradient Oracle. | Adrian Vladu |
| 2021 | AAAI | Adaptive Gradient Methods for Constrained Convex Optimization and Variational Inequalities. | Alina Ene, Huy L. Nguyen, Adrian Vladu |
| 2021 | AAAI | Projection-Free Bandit Optimization with Privacy Guarantees. | Alina Ene, Huy L. Nguyen, Adrian Vladu |
| 2021 | FOCS | Faster Sparse Minimum Cost Flow by Electrical Flow Localization. | Kyriakos Axiotis, Aleksander Madry, Adrian Vladu |
| 2021 | ICML | Decomposable Submodular Function Minimization via Maximum Flow. | Kyriakos Axiotis, Adam Karczmarz, Anish Mukherjee, Piotr Sankowski, Adrian Vladu |
| 2020 | FOCS | Circulation Control for Faster Minimum Cost Flow in Unit-Capacity Graphs. | Kyriakos Axiotis, Aleksander Madry, Adrian Vladu |
| 2019 | ICML | Improved Convergence for $\ell_1$ and $\ell_∞$ Regression via Iteratively Reweighted Least Squares. | Alina Ene, Adrian Vladu |
| 2019 | STOC | Submodular maximization with matroid and packing constraints in parallel. | Alina Ene, Huy L. Nguyen, Adrian Vladu |
| 2018 | ICLR | Towards Deep Learning Models Resistant to Adversarial Attacks. | Aleksander Madry, Aleksandar Makelov, Ludwig Schmidt, Dimitris Tsipras, Adrian Vladu |
| 2017 | FOCS | Matrix Scaling and Balancing via Box Constrained Newton's Method and Interior Point Methods. | Michael B. Cohen, Aleksander Madry, Dimitris Tsipras, Adrian Vladu |
| 2017 | ICML | Tight Bounds for Approximate Carathodory and Beyond. | Vahab S. Mirrokni, Renato Paes Leme, Adrian Vladu, Sam Chiu-wai Wong |
| 2017 | SODA | Negative-Weight Shortest Paths and Unit Capacity Minimum Cost Flow in ( | Michael B. Cohen, Aleksander Madry, Piotr Sankowski, Adrian Vladu |
| 2017 | STOC | Almost-linear-time algorithms for Markov chains and new spectral primitives for directed graphs. | Michael B. Cohen, Jonathan A. Kelner, John Peebles, Richard Peng, Anup B. Rao, Aaron Sidford, Adrian Vladu |
| 2016 | FOCS | Faster Algorithms for Computing the Stationary Distribution, Simulating Random Walks, and More. | Michael B. Cohen, Jonathan A. Kelner, John Peebles, Richard Peng, Aaron Sidford, Adrian Vladu |
| 2015 | PODC | How To Elect a Leader Faster than a Tournament. | Dan Alistarh, Rati Gelashvili, Adrian Vladu |
| 2015 | SPAA | Improved Parallel Algorithms for Spanners and Hopsets. | Gary L. Miller, Richard Peng, Adrian Vladu, Shen Chen Xu |
| 2010 | WAOA | Online Ranking for Tournament Graphs. | Claire Mathieu, Adrian Vladu |