Zobrazeno 1 - 10
of 21
pro vyhledávání: '"Heydaribeni, Nasimeh"'
Autor:
de Arruda, Guilherme Ferraz, He, Wan, Heydaribeni, Nasimeh, Javidi, Tara, Moreno, Yamir, Eliassi-Rad, Tina
We propose a team assignment algorithm based on a hypergraph approach focusing on resilience and diffusion optimization. Specifically, our method is based on optimizing the algebraic connectivity of the Laplacian matrix of an edge-dependent vertex-we
Externí odkaz:
http://arxiv.org/abs/2403.04063
Scalable addressing of high dimensional constrained combinatorial optimization problems is a challenge that arises in several science and engineering disciplines. Recent work introduced novel application of graph neural networks for solving quadratic
Externí odkaz:
http://arxiv.org/abs/2311.09375
Autor:
Chang, Jung-Woo, Sun, Ke, Heydaribeni, Nasimeh, Hidano, Seira, Zhang, Xinyu, Koushanfar, Farinaz
Machine Learning (ML) has been instrumental in enabling joint transceiver optimization by merging all physical layer blocks of the end-to-end wireless communication systems. Although there have been a number of adversarial attacks on ML-based wireles
Externí odkaz:
http://arxiv.org/abs/2311.00207
In this work, we introduce SureFED, a novel framework for byzantine robust federated learning. Unlike many existing defense methods that rely on statistically robust quantities, making them vulnerable to stealthy and colluding attacks, SureFED establ
Externí odkaz:
http://arxiv.org/abs/2308.02747
Autor:
Heydaribeni, Nasimeh, Savla, Ketan
We study an information design problem for a non-atomic service scheduling game. The service starts at a random time and there is a continuum of agent population who have a prior belief about the service start time but do not observe the actual reali
Externí odkaz:
http://arxiv.org/abs/2110.00090
We consider a queue with an unobservable backlog by the incoming users. There is an information designer that observes the queue backlog and makes recommendations to the users arriving at the queue whether to join or not to join the queue. The arrivi
Externí odkaz:
http://arxiv.org/abs/2109.14673
We consider a dynamic game with asymmetric information where each player observes privately a noisy version of a (hidden) state of the world V, resulting in dependent private observations. We study structured perfect Bayesian equilibria that use priv
Externí odkaz:
http://arxiv.org/abs/2009.04253
We consider a non-zero-sum linear quadratic Gaussian (LQG) dynamic game with asymmetric information. Each player observes privately a noisy version of a (hidden) state of the world $V$, resulting in dependent private observations. We study perfect Ba
Externí odkaz:
http://arxiv.org/abs/1909.04834
We consider an environment where players need to decide whether to buy a certain product (or adopt a technology) or not. The product is either good or bad, but its true value is unknown to the players. Instead, each player has her own private informa
Externí odkaz:
http://arxiv.org/abs/1905.01327
In the standard Mechanism Design framework, agents' messages are gathered at a central point and allocation/tax functions are calculated in a centralized manner, i.e., as functions of all network agents' messages. This requirement may cause communica
Externí odkaz:
http://arxiv.org/abs/1904.01222