- (3/10)
**NEW PREPRINT**improving the running time for minimum cost flow in sparse graphs with unit capacities. See here. - (6/24) I talked at STOC about the adaptive complexity of submodular maximization. Three (!) different groups of researchers obtained similar results using amazingly different techniques. To get an idea, take a look at the slides.
- (6/12) I talked at ICML about a provably efficient version of IRLS, which finally explains this method for approximating max flow in a more principled (and slightly more efficient) way.
Alina Ene, Huy L. Nguyễn, Adrian Vladu Kyriakos Axiotis, Aleksander Mądry, Adrian Vladu Symposium on Foundations of Computer Science (FOCS 2020) _{∞} and ℓ_{1} Regression via Iteratively Reweighted Least SquaresAlina Ene, Adrian Vladu International Conference on Machine Learning (ICML 2019) [talk video] [slides] [poster] [code] Alina Ene, Huy L. Nguyễn, Adrian Vladu ACM SIGACT Symposium on Theory of Computing (STOC 2019) [slides] [poster] 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 2017Michael B. Cohen, Aleksander Mądry, Dimitris Tsipras, Adrian Vladu Symposium on Foundations of Computer Science (FOCS 2017) [slides] Ilan Lobel, Renato Paes Leme, Adrian Vladu ACM Conference on Economics and Computation (EC 2017) Invited to the special issueAppears in Operations Research [slides] [poster] 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 issueAppears in Highlights of Algorithms 2018^{10/7} log W) Time.Michael B. Cohen, Aleksander Mądry, Piotr Sankowski, Adrian Vladu ACM-SIAM Symposium on Discrete Algorithms (SODA 2017) Appears in Highlights of Algorithms 2017[slides] 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[slides] Michael B. Cohen, Jonathan A. Kelner, John Peebles, Richard Peng, Aaron Sidford, Adrian Vladu Symposium on Foundations of Computer Science (FOCS 2016) [slides] 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) [slides] Alina Ene, Huy L. Nguyễn, Adrian Vladu (by contribution) Iuliana Ene, Matthew Lohse, Adrian Vladu, Joachim Morschhäuser, Alexander Johnson, Richard Bennett mBIO (2016) ( * Per mathematical tradition, authors are written in alphabetic order unless stated otherwise.) |