About me
I am a permanent researcher at IRIF, affiliated with CNRS and Université Paris Cité.
I received my PhD from MIT Math in 2017, which was followed by a postdoc at Boston University.
I work on multiple aspects of convex and non-convex optimization. My work so far combined techniques from continuous optimization and convex geometry in order to obtain improved algorithms for classical discrete problems.
Presently, I am extremely interested in the science of deep learning, and I seek to use principled matematical tools to understand the power and limitations of modern ML models.
Interested in working with me? Please apply to our PhD program. Also consider the Parisian Master of Research in Computer Science, an elite research program after which students typically transition to a PhD.
Publications
Adrian Vladu
ACM Symposium on Theory of Computing (STOC 2023)
Ilia Markov, Adrian Vladu, Qi Guo, Dan Alistarh
International Conference on Machine Learning (ICML 2023)
Alexandra Peste, Adrian Vladu, Eldar Kurtic, Christoph H. Lampert, Dan Alistarh
International Conference on Learning Representations (ICLR 2023)
Lucas Pesenti, Adrian Vladu
ACM-SIAM Symposium on Discrete Algorithms (SODA 2023)
Kyriakos Axiotis, Aleksander Mądry, Adrian Vladu
Symposium on Foundations of Computer Science (FOCS 2021)
Alexandra Peste, Eugenia Iofinova, Adrian Vladu, Dan Alistarh
Conference on Neural Information Processing Systems (NeurIPS 2021)
Kyriakos Axiotis, Adam Karczmarz, Anish Mukherjee, Piotr Sankowski, Adrian Vladu
International Conference on Machine Learning (ICML 2021)
Alina Ene, Huy L. Nguyễn, Adrian Vladu
AAAI Conference on Artificial Intelligence (AAAI 2021)
Alina Ene, Huy L. Nguyễn, Adrian Vladu
AAAI Conference on Artificial Intelligence (AAAI 2021)
Kyriakos Axiotis, Aleksander Mądry, Adrian Vladu
Symposium on Foundations of Computer Science (FOCS 2020)
Alina Ene, Adrian Vladu
International Conference on Machine Learning (ICML 2019)
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Alina Ene, Huy L. Nguyễn, Adrian Vladu
ACM SIGACT Symposium on Theory of Computing (STOC 2019)
Aleksander Mądry, Aleksandar Makelov, Ludwig Schmidt, Dimitris Tsipras, Adrian Vladu
International Conference on Learning Representations (ICLR 2018)
Oral presentation at the Principled Approaches to Deep Learning workshop, ICML 2017
Michael B. Cohen, Aleksander Mądry, Dimitris Tsipras, Adrian Vladu
Symposium on Foundations of Computer Science (FOCS 2017)
Ilan Lobel, Renato Paes Leme, Adrian Vladu
ACM Conference on Economics and Computation (EC 2017)
Invited to the special issue
Appears in Operations Research
Michael B. Cohen, Jonathan A. Kelner, John Peebles, Richard Peng, Anup B. Rao, Aaron Sidford, Adrian Vladu
ACM SIGACT Symposium on Theory of Computing (STOC 2017)
Invited to the special issue
Appears in Highlights of Algorithms 2018
Michael B. Cohen, Aleksander Mądry, Piotr Sankowski, Adrian Vladu
ACM-SIAM Symposium on Discrete Algorithms (SODA 2017)
Appears in Highlights of Algorithms 2017
Vahab S. Mirrokni, Renato Paes Leme, Adrian Vladu, Sam Chiu-wai Wong
International Conference on Machine Learning (ICML 2017)
Oral presentation at the Informs Optimization Society Conference 2016
Michael B. Cohen, Jonathan A. Kelner, John Peebles, Richard Peng, Aaron Sidford, Adrian Vladu
Symposium on Foundations of Computer Science (FOCS 2016)
Gary L. Miller, Richard Peng, Adrian Vladu, Shen Chen Xu
ACM symposium on Parallelism in Algorithms and Architectures (SPAA 2015)
Dan Alistarh, Rati Gelashvili, Adrian Vladu
ACM Symposium on Principles of Distributed Computing (PODC 2015)
Claire Mathieu, Adrian Vladu
International Workshop on Approximation and Online Algorithms (WAOA 2010)
Other works
Alina Ene, Huy L. Nguyễn, Adrian Vladu
(by contribution) Iuliana Ene, Matthew Lohse, Adrian Vladu, Joachim Morschhäuser, Alexander Johnson, Richard Bennett
mBIO (2016)