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2020 – today
- 2023
[c21]Adam B. Cobb, Anirban Roy, Daniel Elenius, F. Michael Heim, Brian Swenson, Sydney Whittington, James D. Walker, Theodore Bapty, Joseph Hite, Karthik Ramani, Christopher McComb, Susmit Jha:
AircraftVerse: A Large-Scale Multimodal Dataset of Aerial Vehicle Designs. NeurIPS 2023- [i14]Adam D. Cobb, Anirban Roy, Daniel Elenius, F. Michael Heim, Brian Swenson, Sydney Whittington, James D. Walker, Theodore Bapty, Joseph Hite, Karthik Ramani, Christopher McComb, Susmit Jha:
AircraftVerse: A Large-Scale Multimodal Dataset of Aerial Vehicle Designs. CoRR abs/2306.05562 (2023) - 2022
- [j9]Brian Swenson, Ryan Murray, H. Vincent Poor, Soummya Kar:
Distributed Stochastic Gradient Descent: Nonconvexity, Nonsmoothness, and Convergence to Local Minima. J. Mach. Learn. Res. 23: 328:1-328:62 (2022) - [j8]Brian Swenson
, Ryan W. Murray, H. Vincent Poor, Soummya Kar:
Distributed Gradient Flow: Nonsmoothness, Nonconvexity, and Saddle Point Evasion. IEEE Trans. Autom. Control. 67(8): 3949-3964 (2022) - 2020
- [j7]Brian Swenson, Ryan W. Murray, Soummya Kar:
Regular potential games. Games Econ. Behav. 124: 432-453 (2020) - [c20]Brian Swenson, Anirudh Sridhar, H. Vincent Poor:
On Distributed Stochastic Gradient Algorithms for Global Optimization. ICASSP 2020: 8594-8598 - [c19]Meng Zhang, Brian Swenson, Jianwei Huang, H. Vincent Poor:
Truthful mobile crowd sensing with interdependent valuations. MobiHoc 2020: 91-100 - [i13]Brian Swenson, Ryan W. Murray, H. Vincent Poor, Soummya Kar:
Distributed Gradient Flow: Nonsmoothness, Nonconvexity, and Saddle Point Evasion. CoRR abs/2008.05387 (2020)
2010 – 2019
- 2019
- [j6]Ryan W. Murray, Brian Swenson, Soummya Kar:
Revisiting Normalized Gradient Descent: Fast Evasion of Saddle Points. IEEE Trans. Autom. Control. 64(11): 4818-4824 (2019) - [c18]Brian Swenson, H. Vincent Poor:
Smooth Fictitious Play in N × 2 Potential Games. ACSSC 2019: 1739-1743 - [c17]Brian Swenson, Ryan W. Murray, H. Vincent Poor, Soummya Kar:
Distributed Gradient Descent: Nonconvergence to Saddle Points and the Stable-Manifold Theorem. Allerton 2019: 595-601 - [c16]Brian Swenson, Soummya Kar, H. Vincent Poor, José M. F. Moura:
Distributed Global Optimization by Annealing. CAMSAP 2019: 181-185 - [c15]Brian Swenson, Soummya Kar, H. Vincent Poor, José M. F. Moura:
Annealing for Distributed Global Optimization. CDC 2019: 3018-3025 - [c14]Carmel Fiscko, Brian Swenson, Soummya Kar, Bruno Sinopoli:
Control of Parametric Games. ECC 2019: 1036-1042 - [i12]Soummya Kar, Brian Swenson:
Clustering with Distributed Data. CoRR abs/1901.00214 (2019) - [i11]Brian Swenson, Soummya Kar, H. Vincent Poor, José M. F. Moura:
Distributed Global Optimization by Annealing. CoRR abs/1907.08802 (2019) - [i10]Brian Swenson, Ryan W. Murray, H. Vincent Poor, Soummya Kar:
Distributed Gradient Descent: Nonconvergence to Saddle Points and the Stable-Manifold Theorem. CoRR abs/1908.02747 (2019) - [i9]Brian Swenson, Anirudh Sridhar, H. Vincent Poor:
On Distributed Stochastic Gradient Algorithms for Global Optimization. CoRR abs/1910.09587 (2019) - [i8]Brian Swenson, H. Vincent Poor:
Smooth Fictitious Play in N×2 Potential Games. CoRR abs/1912.00251 (2019) - 2018
- [j5]Brian Swenson, Ryan W. Murray, Soummya Kar:
On Best-Response Dynamics in Potential Games. SIAM J. Control. Optim. 56(4): 2734-2767 (2018) - [j4]Brian Swenson, Ceyhun Eksin, Soummya Kar, Alejandro Ribeiro:
Distributed Inertial Best-Response Dynamics. IEEE Trans. Autom. Control. 63(12): 4294-4300 (2018) - [c13]Brian Swenson, Ryan W. Murray, Soummya Kar, H. Vincent Poor:
Best-Response Dynamics in Continuous Potential Games: Non-Convergence to Saddle Points. ACSSC 2018: 310-315 - 2017
- [b1]Brian Swenson:
Myopic Best-Response Learning in Large-Scale Games. Carnegie Mellon University, USA, 2017 - [j3]Brian Swenson, Soummya Kar, João Xavier, David S. Leslie:
Robustness Properties in Fictitious-Play-Type Algorithms. SIAM J. Control. Optim. 55(5): 3295-3318 (2017) - [j2]Brian Swenson, Soummya Kar, João Xavier:
Single Sample Fictitious Play. IEEE Trans. Autom. Control. 62(11): 6026-6031 (2017) - [c12]Brian Swenson, Soummya Kar:
On the exponential rate of convergence of fictitious play in potential games. Allerton 2017: 275-279 - [i7]Brian Swenson, Ryan W. Murray, Soummya Kar:
Fictitious Play in Potential Games. CoRR abs/1707.06465 (2017) - [i6]Brian Swenson, Ryan W. Murray, Soummya Kar:
Regular Potential Games. CoRR abs/1707.06466 (2017) - [i5]Brian Swenson, Soummya Kar:
On the Exponential Rate of Convergence of Fictitious Play in Potential Games. CoRR abs/1707.08055 (2017) - 2016
- [c11]Brian Swenson, Soummya Kar, João Xavier:
Computationally efficient learning in large-scale games: Sampled fictitious play revisited. ACSSC 2016: 1212-1215 - [c10]Ceyhun Eksin, Brian Swenson, Soummya Kar, Alejandro Ribeiro:
Learning pure-strategy Nash equilibria in networked multi-agent systems with uncertainty. CDC 2016: 5292-5297 - [c9]Rongye Shi, Thomas C. Jackson, Brian Swenson, Soummya Kar, Lawrence T. Pileggi:
On the design of phase locked loop oscillatory neural networks: Mitigation of transmission delay effects. IJCNN 2016: 2039-2046 - [e1]Thomas Henderson, Eric Gamess, Brian Swenson, Hajime Tazaki:
Proceedings of the Workshop on ns-3, WNS3 '16, Seattle, WA, USA, June 15-16, 2016. ACM 2016, ISBN 978-1-4503-4216-2 [contents] - [i4]Brian Swenson, Ceyhun Eksin, Soummya Kar, Alejandro Ribeiro:
Fictitious Play with Inertia Learns Pure Equilibria in Distributed Games with Incomplete Information. CoRR abs/1605.00601 (2016) - 2015
- [j1]Brian Swenson, Soummya Kar, João Xavier:
Empirical Centroid Fictitious Play: An Approach for Distributed Learning in Multi-Agent Games. IEEE Trans. Signal Process. 63(15): 3888-3901 (2015) - [c8]Brian Swenson, Soummya Kar, João Xavier:
On asynchronous implementations of fictitious play for distributed learning. ACSSC 2015: 1119-1124 - [c7]Brian Swenson, Soummya Kar, João Xavier:
On robustness properties in Empirical Centroid Fictitious Play. CDC 2015: 3324-3330 - [c6]Brian Swenson, Soummya Kar, João Xavier:
A computationally efficient implementation of fictitious play in a distributed setting. EUSIPCO 2015: 1043-1047 - [i3]Brian Swenson, Soummya Kar, João Xavier:
From Weak Learning to Strong Learning in Fictitious Play Type Algorithms. CoRR abs/1504.04920 (2015) - [i2]Brian Swenson, Soummya Kar, João M. F. Xavier:
A Computationally Efficient Implementation of Fictitious Play for Large-Scale Games. CoRR abs/1506.04320 (2015) - 2014
- [c5]Brian Swenson, Soummya Kar, João Xavier:
Game-theoretic learning in a distributed-information setting: Distributed convergence to mean-centric equilibria. ACSSC 2014: 1616-1620 - [c4]Brian Swenson, Soummya Kar, João Manuel Freitas Xavier:
Strong convergence to mixed equilibria in fictitious play. CISS 2014: 1-6 - [c3]Tamim Sookoor, David Doria, David Bruno, Dale R. Shires, Brian Swenson, Lori L. Pollock:
Offload Destination Selection to Enable Distributed Computation on Battlefields. MILCOM 2014: 841-848 - 2013
- [c2]Brian Swenson, Soummya Kar, João M. F. Xavier:
Mean-centric equilibrium: An equilibrium concept for learning in large-scale games. GlobalSIP 2013: 571-574 - [i1]Brian Swenson, Soummya Kar, João Manuel Freitas Xavier:
Empirical Centroid Fictitious Play: An Approach For Distributed Learning In Multi-Agent Games. CoRR abs/1304.4577 (2013) - 2012
- [c1]Brian Swenson, Soummya Kar, João Manuel Freitas Xavier:
Distributed learning in large-scale multi-agent games: A modified fictitious play approach. ACSCC 2012: 1490-1495
Coauthor Index
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