Ioannis Panageas

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Georgios PiliourasGoogle DeepMind, Singapore University of Technology and Design確認したメールアドレス: google.com
Constantinos DaskalakisProfessor of Computer Science, MIT確認したメールアドレス: csail.mit.edu
Xiao WangShanghai University of Finance and Economics確認したメールアドレス: sufe.edu.cn
Sai Ganesh NagarajanPostdoctoral Researcher, Zuse Institute Berlin確認したメールアドレス: zib.de
Ioannis AnagnostidesPhD student, Carnegie Mellon University確認したメールアドレス: andrew.cmu.edu
Ruta MehtaDept. of Computer Science, University of Illinois at Urbana-Champaign確認したメールアドレス: cs.illinois.edu
Vijay VaziraniDistinguished Professor, Dept. of Computer Science, University of California, Irvine.確認したメールアドレス: ics.uci.edu
William OvermanPhD Student, Stanford GSB確認したメールアドレス: stanford.edu
Fivos KalogiannisPhD student, UCSD確認したメールアドレス: ucsd.edu
Stefanos LeonardosLecturer in machine learning, King's College London確認したメールアドレス: kcl.ac.uk
Tuomas SandholmAngel Jordan University Professor of Computer Science, Carnegie Mellon University確認したメールアドレス: cs.cmu.edu
Gabriele FarinaAssistant Professor of Computer Science, MIT確認したメールアドレス: mit.edu
Vaggos ChatziafratisUniversity of California, Santa Cruz確認したメールアドレス: cs.stanford.edu
Jason D. LeeAssociate Professor of Electrical Engineering and Computer Science, Princeton University確認したメールアドレス: princeton.edu
Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC Berkeley確認したメールアドレス: cs.berkeley.edu
Benjamin RechtProfessor of EECS, University of California, Berkeley確認したメールアドレス: eecs.berkeley.edu
Stephen McAleerOpenAI確認したメールアドレス: openai.com
Prasad TetaliHead, Department of Mathematical Sciences, Carnegie Mellon University確認したメールアドレス: andrew.cmu.edu
Stratis SkoulakisÉcole Polytechnique Fédérale de Lausanne確認したメールアドレス: epfl.ch
Yi FengShanghai University of Finance and Economics確認したメールアドレス: live.sufe.edu.cn

フォロー

Ioannis Panageas

Assistant Professor, University of California, Irvine

確認したメールアドレス: ics.uci.edu - ホームページ

Algorithms Optimization Learning in Games Multi-agent RL Statistics


タイトル引用回数順公開年順タイトル順	引用先引用先	年
First-order methods almost always avoid strict saddle points JD Lee, I Panageas, G Piliouras, M Simchowitz, MI Jordan, B Recht Mathematical programming 176 (1-2), 311-337, 2019	365	2019
The limit points of (optimistic) gradient descent in min-max optimization C Daskalakis, I Panageas Advances in Neural Information Processing Systems 31, 9236-9246, 2018	301	2018
Gradient descent only converges to minimizers: Non-isolated critical points and invariant regions I Panageas, G Piliouras Proceedings of the Conference on Innovations in Theoretical Computer Science, 2017	192*	2017
Last-iterate convergence: Zero-sum games and constrained min-max optimization C Daskalakis, I Panageas Proceedings of the Conference on Innovations in Theoretical Computer Science, 2019	177	2019
Multiplicative Weights Update with Constant Step-Size in Congestion Games: Convergence, Limit Cycles and Chaos G Palaiopanos, I Panageas, G Piliouras 31st Annual Conference on Neural Information Processing Systems, 2017	140	2017
Global convergence of multi-agent policy gradient in markov potential games S Leonardos, W Overman, I Panageas, G Piliouras arXiv preprint arXiv:2106.01969, 2021	130	2021
First-order methods almost always avoid saddle points: The case of vanishing step-sizes I Panageas, G Piliouras, X Wang Advances in Neural Information Processing Systems 32, 2019	64	2019
Natural selection as an inhibitor of genetic diversity: Multiplicative weights updates algorithm and a conjecture of haploid genetics [working paper abstract] R Mehta, I Panageas, G Piliouras Proceedings of the 2015 Conference on Innovations in Theoretical Computer …, 2015	61	2015
Independent natural policy gradient always converges in markov potential games R Fox, SM Mcaleer, W Overman, I Panageas International Conference on Artificial Intelligence and Statistics, 4414-4425, 2022	55	2022
Last iterate convergence in no-regret learning: constrained min-max optimization for convex-concave landscapes Q Lei, SG Nagarajan, I Panageas, X Wang International Conference on Artificial Intelligence and Statistics, 1441-1449, 2021	49	2021
Average case performance of replicator dynamics in potential games via computing regions of attraction I Panageas, G Piliouras Proceedings of the 2016 ACM Conference on Economics and Computation, 703-720, 2016	49*	2016
On last-iterate convergence beyond zero-sum games I Anagnostides, I Panageas, G Farina, T Sandholm International Conference on Machine Learning, 536-581, 2022	42	2022
Regression from dependent observations C Daskalakis, N Dikkala, I Panageas Proceedings of the 51st Annual ACM symposium on Theory of Computing, 2019	40	2019
Depth-width trade-offs for relu networks via sharkovsky's theorem V Chatziafratis, SG Nagarajan, I Panageas, X Wang arXiv preprint arXiv:1912.04378, 2019	31	2019
Cycles in zero-sum differential games and biological diversity T Mai, M Mihail, I Panageas, W Ratcliff, V Vazirani, P Yunker Proceedings of the 2018 ACM Conference on Economics and Computation, 339-350, 2018	23*	2018
Fast convergence of langevin dynamics on manifold: Geodesics meet log-sobolev X Wang, Q Lei, I Panageas Advances in Neural Information Processing Systems 33, 18894-18904, 2020	22	2020
On the Analysis of EM for truncated mixtures of two Gaussians SG Nagarajan, I Panageas Algorithmic Learning Theory, 634-659, 2020	21	2020
Multiplicative Weights Updates as a distributed constrained optimization algorithm: Convergence to second-order stationary points almost always I Panageas, G Piliouras, X Wang Proceedings of the 36th International Conference on Machine Learning, 4961-4969, 2019	18	2019
Mutation, sexual reproduction and survival in dynamic environments R Mehta, I Panageas, G Piliouras, P Tetali, VV Vazirani Proceedings of the 2017 Conference on Innovations in Theoretical Computer …, 2015	18*	2015
On the convergence of no-regret learning dynamics in time-varying games I Anagnostides, I Panageas, G Farina, T Sandholm Advances in Neural Information Processing Systems 36, 2024	17	2024

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