Towards deep learning models resistant to adversarial attacks A Madry, A Makelov, L Schmidt, D Tsipras, A Vladu Proceedings of the International Conference on Representation Learning (ICLR …, 2017 | 12377 | 2017 |

Matrix scaling and balancing via box constrained Newton's method and interior point methods MB Cohen, A Madry, D Tsipras, A Vladu 2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS …, 2017 | 127 | 2017 |

Negative-Weight Shortest Paths and Unit Capacity Minimum Cost Flow in Õ(m^{10/7} log W) Time MB Cohen, A Mądry, P Sankowski, A Vladu Proceedings of the Twenty-Eighth Annual ACM-SIAM Symposium on Discrete …, 2017 | 115 | 2017 |

Almost-linear-time algorithms for markov chains and new spectral primitives for directed graphs MB Cohen, J Kelner, J Peebles, R Peng, AB Rao, A Sidford, A Vladu Proceedings of the 49th Annual ACM SIGACT Symposium on Theory of Computing …, 2017 | 114 | 2017 |

Improved parallel algorithms for spanners and hopsets GL Miller, R Peng, A Vladu, SC Xu Proceedings of the 27th Annual ACM Symposium on Parallelism in Algorithms …, 2013 | 89 | 2013 |

Multidimensional binary search for contextual decision-making I Lobel, RP Leme, A Vladu Operations Research 66 (5), 1346-1361, 2018 | 72 | 2018 |

Faster algorithms for computing the stationary distribution, simulating random walks, and more MB Cohen, J Kelner, J Peebles, R Peng, A Sidford, A Vladu 2016 IEEE 57th annual symposium on foundations of computer science (FOCS …, 2016 | 68 | 2016 |

AC/DC: Alternating compressed/decompressed training of deep neural networks A Peste, E Iofinova, A Vladu, D Alistarh Advances in Neural Information Processing Systems 34, 2021 | 59 | 2021 |

Phenotypic profiling reveals that Candida albicans opaque cells represent a metabolically specialized cell state compared to default white cells IV Ene, MB Lohse, AV Vladu, J Morschhäuser, AD Johnson, RJ Bennett MBio 7 (6), 10.1128/mbio. 01269-16, 2016 | 52 | 2016 |

Circulation Control for Faster Minimum Cost Flow in Unit-Capacity Graphs K Axiotis, A Mądry, A Vladu 2020 IEEE 61st Annual Symposium on Foundations of Computer Science (FOCS), 2020 | 47 | 2020 |

Submodular maximization with matroid and packing constraints in parallel A Ene, HL Nguyen, A Vladu Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing, 2018 | 42 | 2018 |

Tight Bounds for Approximate Caratheodory and Beyond V Mirrokni, R Paes Leme, A Vladu, SC Wong Proceedings of the 34th International Conference on Machine Learning, 2017, 2015 | 39 | 2015 |

Faster Sparse Minimum Cost Flow by Electrical Flow Localization K Axiotis, A Mądry, A Vladu 2021 IEEE 62nd Annual Symposium on Foundations of Computer Science (FOCS), 2021 | 29 | 2021 |

Adaptive Gradient Methods for Constrained Convex Optimization and Variational Inequalities A Ene, HL Nguyen, A Vladu 35th AAAI Conference on Artificial Intelligence, 2021, 2020 | 29 | 2020 |

Improved Convergence for and Regression via Iteratively Reweighted Least Squares A Ene, A Vladu Proceedings of the 36th International Conference on Machine Learning, 2019 …, 2019 | 29 | 2019 |

Decomposable Submodular Function Minimization via Maximum Flow K Axiotis, A Karczmarz, A Mukherjee, P Sankowski, A Vladu Proceedings of the 38th International Conference on Machine Learning, 2021, 2021 | 12 | 2021 |

Cram: A compression-aware minimizer A Peste, A Vladu, E Kurtic, CH Lampert, D Alistarh ICLR 2023, 2022 | 8 | 2022 |

How to elect a leader faster than a tournament D Alistarh, R Gelashvili, A Vladu Proceedings of the 2015 ACM Symposium on Principles of Distributed Computing …, 2015 | 7 | 2015 |

A parallel double greedy algorithm for submodular maximization A Ene, HL Nguyen, A Vladu arXiv preprint arXiv:1812.01591, 2018 | 6 | 2018 |

Quantized Distributed Training of Large Models with Convergence Guarantees I Markov, A Vladu, Q Guo, D Alistarh ICML 2023, 2023 | 5 | 2023 |