Distributed learning in large-scale multi-agent games: A modified fictitious play approach. - Brian Swenson; Soummya Kar; João Manuel Freitas Xavier (ACSCC, 2012)

Mean-centric equilibrium: An equilibrium concept for learning in large-scale games. - Brian Swenson; Soummya Kar; João M. F. Xavier (GlobalSIP, 2013)

Game-theoretic learning in a distributed-information setting: Distributed convergence to mean-centric equilibria. - Brian Swenson; Soummya Kar; João Xavier 001 (ACSSC, 2014)

Strong convergence to mixed equilibria in fictitious play. - Brian Swenson; Soummya Kar; João Manuel Freitas Xavier (CISS, 2014)

Offload Destination Selection to Enable Distributed Computation on Battlefields. - Tamim Sookoor; David Doria; David Bruno; Dale R. Shires; Brian Swenson; Lori L. Pollock (MILCOM, 2014)

On asynchronous implementations of fictitious play for distributed learning. - Brian Swenson; Soummya Kar; João Xavier 001 (ACSSC, 2015)

On robustness properties in Empirical Centroid Fictitious Play. - Brian Swenson; Soummya Kar; João Xavier 001 (CDC, 2015)

A computationally efficient implementation of fictitious play in a distributed setting. - Brian Swenson; Soummya Kar; João Xavier 001 (EUSIPCO, 2015)

From Weak Learning to Strong Learning in Fictitious Play Type Algorithms. - Brian Swenson; Soummya Kar; João Xavier 001 (CoRR, 2015)

A Computationally Efficient Implementation of Fictitious Play for Large-Scale Games. - Brian Swenson; Soummya Kar; João M. F. Xavier (CoRR, 2015)

Empirical Centroid Fictitious Play: An Approach for Distributed Learning in Multi-Agent Games. - Brian Swenson; Soummya Kar; João Xavier 001 (IEEE Trans. Signal Process., 2015)

Computationally efficient learning in large-scale games: Sampled fictitious play revisited. - Brian Swenson; Soummya Kar; João Xavier 001 (ACSSC, 2016)

Learning pure-strategy Nash equilibria in networked multi-agent systems with uncertainty. - Ceyhun Eksin; Brian Swenson; Soummya Kar; Alejandro Ribeiro (CDC, 2016)

On the design of phase locked loop oscillatory neural networks: Mitigation of transmission delay effects. - Rongye Shi; Thomas C. Jackson; Brian Swenson; Soummya Kar; Lawrence T. Pileggi (IJCNN, 2016)

Fictitious Play with Inertia Learns Pure Equilibria in Distributed Games with Incomplete Information. - Brian Swenson; Ceyhun Eksin; Soummya Kar; Alejandro Ribeiro (CoRR, 2016)

On the exponential rate of convergence of fictitious play in potential games. - Brian Swenson; Soummya Kar (Allerton, 2017)

Fictitious Play in Potential Games. - Brian Swenson; Ryan W. Murray; Soummya Kar (CoRR, 2017)

Robustness Properties in Fictitious-Play-Type Algorithms. - Brian Swenson; Soummya Kar; João Xavier 001; David S. Leslie (SIAM J. Control. Optim., 2017)

Single Sample Fictitious Play. - Brian Swenson; Soummya Kar; João Xavier 001 (IEEE Trans. Autom. Control., 2017)

Myopic Best-Response Learning in Large-Scale Games. - Brian Swenson (2017)

Best-Response Dynamics in Continuous Potential Games: Non-Convergence to Saddle Points. - Brian Swenson; Ryan W. Murray; Soummya Kar; H. Vincent Poor (ACSSC, 2018)

On Best-Response Dynamics in Potential Games. - Brian Swenson; Ryan W. Murray; Soummya Kar (SIAM J. Control. Optim., 2018)

Distributed Inertial Best-Response Dynamics. - Brian Swenson; Ceyhun Eksin; Soummya Kar; Alejandro Ribeiro (IEEE Trans. Autom. Control., 2018)

Smooth Fictitious Play in N × 2 Potential Games. - Brian Swenson; H. Vincent Poor (ACSSC, 2019)

Distributed Gradient Descent: Nonconvergence to Saddle Points and the Stable-Manifold Theorem. - Brian Swenson; Ryan W. Murray; H. Vincent Poor; Soummya Kar (Allerton, 2019)

Distributed Global Optimization by Annealing. - Brian Swenson; Soummya Kar; H. Vincent Poor; José M. F. Moura (CAMSAP, 2019)

Annealing for Distributed Global Optimization. - Brian Swenson; Soummya Kar; H. Vincent Poor; José M. F. Moura (CDC, 2019)

Control of Parametric Games. - Carmel Fiscko; Brian Swenson; Soummya Kar; Bruno Sinopoli (ECC, 2019)

Clustering with Distributed Data. - Soummya Kar; Brian Swenson (CoRR, 2019)

Revisiting Normalized Gradient Descent: Fast Evasion of Saddle Points. - Ryan W. Murray; Brian Swenson; Soummya Kar (IEEE Trans. Autom. Control., 2019)

On Distributed Stochastic Gradient Algorithms for Global Optimization. - Brian Swenson; Anirudh Sridhar; H. Vincent Poor (ICASSP, 2020)

Truthful mobile crowd sensing with interdependent valuations. - Meng Zhang 013; Brian Swenson; Jianwei Huang 001; H. Vincent Poor (MobiHoc, 2020)

Regular potential games. - Brian Swenson; Ryan W. Murray; Soummya Kar (Games Econ. Behav., 2020)

Distributed Stochastic Gradient Descent: Nonconvexity, Nonsmoothness, and Convergence to Local Minima. - Brian Swenson; Ryan Murray 001; H. Vincent Poor; Soummya Kar (J. Mach. Learn. Res., 2022)

Distributed Gradient Flow: Nonsmoothness, Nonconvexity, and Saddle Point Evasion. - Brian Swenson; Ryan W. Murray; H. Vincent Poor; Soummya Kar (IEEE Trans. Autom. Control., 2022)

AircraftVerse: A Large-Scale Multimodal Dataset of Aerial Vehicle Designs. - 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 (NeurIPS, 2023)