Vladu, Adrian

10 publications

NeurIPS 2025 Quasi-Self-Concordant Optimization with $\ell_{\infty}$ Lewis Weights Alina Ene, Ta Duy Nguyen, Adrian Vladu

ICLR 2023 CrAM: A Compression-Aware Minimizer Alexandra Peste, Adrian Vladu, Eldar Kurtic, Christoph H Lampert, Dan Alistarh

ICML 2023 Quantized Distributed Training of Large Models with Convergence Guarantees Ilia Markov, Adrian Vladu, Qi Guo, Dan Alistarh

NeurIPS 2021 AC/DC: Alternating Compressed/DeCompressed Training of Deep Neural Networks Alexandra Peste, Eugenia Iofinova, Adrian Vladu, Dan Alistarh

AAAI 2021 Adaptive Gradient Methods for Constrained Convex Optimization and Variational Inequalities Alina Ene, Huy L. Nguyen, Adrian Vladu

ICML 2021 Decomposable Submodular Function Minimization via Maximum Flow Kyriakos Axiotis, Adam Karczmarz, Anish Mukherjee, Piotr Sankowski, Adrian Vladu

AAAI 2021 Projection-Free Bandit Optimization with Privacy Guarantees Alina Ene, Huy L. Nguyen, Adrian Vladu

ICML 2019 Improved Convergence for $\ell_1$ and $\ell_∞$ Regression via Iteratively Reweighted Least Squares Alina Ene, Adrian Vladu

ICLR 2018 Towards Deep Learning Models Resistant to Adversarial Attacks Aleksander Madry, Aleksandar Makelov, Ludwig Schmidt, Dimitris Tsipras, Adrian Vladu

ICML 2017 Tight Bounds for Approximate Carathéodory and Beyond Vahab Mirrokni, Renato Paes Leme, Adrian Vladu, Sam Chiu-wai Wong