1 citations · 1 across the 2 of their papers we have counts for
5 papers
Distributed Team Orchestration via Supervisor Networks: Convergence, Optimality, and Resilience
Juntian Zhu, Guanpu Chen, Tongtian Zhu +3
In this paper, we study zero-sum potential team games with a supervisor network, where agents rely on supervisor-provided belief information rather than accurate common beliefs. Th…
Bayesian Mixture Models for Heterogeneous Extremes
Viviana Carcaiso, Miguel de Carvalho, Ilaria Prosdocimi +1
The conventional use of the Generalized Extreme Value (GEV) distribution to model block maxima may be inappropriate when extremes are actually structured into multiple heterogeneou…
On the Kolmogorov Superposition Theorem and Regular Means
Miguel de Carvalho
While Kolmogorov's probability axioms are widely recognized, it is less well known that in an often-overlooked 1930 note, Kolmogorov proposed an axiomatic framework for a unifying…
When a Reinforcement Learning Agent Encounters Unknown Unknowns
Juntian Zhu, Miguel de Carvalho, Zhouwang Yang +1
An AI agent might surprisingly find she has reached an unknown state which she has never been aware of -- an unknown unknown. We mathematically ground this scenario in reinforcemen…
Heavy-Tailed NGG Mixture Models
Vianey Palacios Ramirez, Miguel de Carvalho, Luis Gutierrez Inostroza
Heavy tails are often found in practice, and yet they are an Achilles heel of a variety of mainstream random probability measures such as the Dirichlet process (DP). The first cont…