1 citations · 1 across the 7 of their papers we have counts for
7 papers
Noncooperative Human-AI Agent Dynamics
Dylan Waldner, Vyacheslav Kungurtsev, Mitchelle Ashimosi
This paper investigates the dynamics of noncooperative interactions between artificial intelligence agents and human decision-makers in strategic environments. In particular, motiv…
Multistage Stochastic Programming for Rare Event Risk Mitigation in Power Systems Management
Daniel Mastropietro, Vyacheslav Kungurtsev
High intermittent renewable penetration in the energy mix presents challenges in robustness for the management of power systems' operation. If a tail realization of the distributio…
Towards Tsallis Fully Probabilistic Design
Vyacheslav Kungurtsev, Giovanni Russo
Fully Probabilistic design (FPD) is a powerful framework offering an elegant and unifying account of stochastic control, learning and decision-making. Here we introduce a generaliz…
Mission-Aligned Learning-Informed Control of Autonomous Systems: Formulation and Foundations
Vyacheslav Kungurtsev, Alessandro Di Frenna, Gustav Sir +5
Research, innovation and practical capital investment have been increasing rapidly toward the realization of autonomous physical agents. This includes industrial and service robots…
"Cause" is Mechanistic Narrative within Scientific Domains: An Ordinary Language Philosophical Critique of "Causal Machine Learning"
Vyacheslav Kungurtsev, Leonardo Christov Moore, Gustav Sir +1
Causal Learning has emerged as a major theme of research in statistics and machine learning in recent years, promising computational techniques to reveal ``true'' causality. In thi…
Towards Diverse Device Heterogeneous Federated Learning via Task Arithmetic Knowledge Integration
Mahdi Morafah, Vyacheslav Kungurtsev, Hojin Chang +2
Federated Learning has emerged as a promising paradigm for collaborative machine learning, while preserving user data privacy. Despite its potential, standard FL lacks support for…
Probabilistic Iterative Hard Thresholding for Sparse Learning
Matteo Bergamaschi, Andrea Cristofari, Vyacheslav Kungurtsev +1
For statistical modeling wherein the data regime is unfavorable in terms of dimensionality relative to the sample size, finding hidden sparsity in the ground truth can be critical…