Zobrazeno 1 - 10
of 245
pro vyhledávání: '"Shanbhag, Uday V."'
We consider a class of hierarchical multi-agent optimization problems over networks where agents seek to compute an approximate solution to a single-stage stochastic mathematical program with equilibrium constraints (MPEC). MPECs subsume several impo
Externí odkaz:
http://arxiv.org/abs/2310.09356
Motivated by the emergence of federated learning (FL), we design and analyze federated methods for addressing: (i) Nondifferentiable nonconvex optimization; (ii) Bilevel optimization; (iii) Minimax problems; and (iv) Two-stage stochastic mathematical
Externí odkaz:
http://arxiv.org/abs/2309.13024
We consider a class of nonsmooth aggregative games over networks in stochastic regimes, where each player is characterized by a composite cost function $f_i+r_i$, $f_i$ is a smooth expectation-valued function dependent on its own strategy and an aggr
Externí odkaz:
http://arxiv.org/abs/2304.03651
We consider an N-player hierarchical game in which the i-th player's objective comprises of an expectation-valued term, parametrized by rival decisions, and a hierarchical term. Such a framework allows for capturing a broad range of stochastic hierar
Externí odkaz:
http://arxiv.org/abs/2302.06497
In this paper, we consider a distributed learning problem in a subnetwork zero-sum game, where agents are competing in different subnetworks. These agents are connected through time-varying graphs where each agent has its own cost function and can re
Externí odkaz:
http://arxiv.org/abs/2108.02144
Publikováno v:
Computational Optimization and Applications, 2022
We consider monotone inclusions defined on a Hilbert space where the operator is given by the sum of a maximal monotone operator $T$ and a single-valued monotone, Lipschitz continuous, and expectation-valued operator $V$. We draw motivation from the
Externí odkaz:
http://arxiv.org/abs/2107.10335
Autor:
Shanbhag, Uday V., Yousefian, Farzad
We consider the minimization of an $L_0$-Lipschitz continuous and expectation-valued function, denoted by $f$ and defined as $f(x)\triangleq \mathbb{E}[\tilde{f}(x,\omega)]$, over a Cartesian product of closed and convex sets with a view towards obta
Externí odkaz:
http://arxiv.org/abs/2107.07174
Stochastic MPECs have found increasing relevance for modeling a broad range of settings in engineering and statistics. Yet, there seem to be no efficient first/zeroth-order schemes equipped with non-asymptotic rate guarantees for resolving even deter
Externí odkaz:
http://arxiv.org/abs/2104.08406
Autor:
Cui, Shisheng, Shanbhag, Uday V.
We consider a class of hierarchical noncooperative $N$-player games where the $i$th player solves a parametrized stochastic mathematical program with equilibrium constraints (MPEC) with the caveat that the implicit form of the $i$th player's in MPEC
Externí odkaz:
http://arxiv.org/abs/2104.07860
In this paper we propose a new operator splitting algorithm for distributed Nash equilibrium seeking under stochastic uncertainty, featuring relaxation and inertial effects. Our work is inspired by recent deterministic operator splitting methods, des
Externí odkaz:
http://arxiv.org/abs/2103.13115