activity
20142025
most citedTwo-dimensional Parallel Tempering for Constrained Optimization

6 citations · 6 across the 5 of their papers we have counts for

collaborators

5 papers

eess.SY2025

Zero-sum turn games using Q-learning: finite computation with security guarantees

Sean Anderson, Chris Darken, João Hespanha

This paper addresses zero-sum ``turn'' games, in which only one player can make decisions at each state. We show that pure saddle-point state-feedback policies for turn games can b…

cs.LG20256 cited

Two-dimensional Parallel Tempering for Constrained Optimization

Corentin Delacour, M Mahmudul Hasan Sajeeb, Joao P. Hespanha +1

Sampling Boltzmann probability distributions plays a key role in machine learning and optimization, motivating the design of hardware accelerators such as Ising machines. While the…

math.OC2023

Event-triggered control cannot improve the gain of optimal periodic control and transmit at a smaller average rate

Duarte J. Antunes, J. P. Hespanha

We consider a standard discrete-time event-triggered control setting by which a scheduler collocated with the plant's sensors decides when to transmit sensor data to a remote contr…

math.OC2023

Optimal sampling schedules for and state-feedback control

Duarte J. Antunes, J. P. Hespanha

We consider a discrete-time linear system for which the control input is updated at every sampling time, but the state is measured at a slower rate. We allow the state to be sample…

q-bio.MN2014

Modular decomposition and analysis of biological networks

Hari Sivakumar, Stephen R. Proulx, João P. Hespanha

This paper addresses the decomposition of biochemical networks into functional modules that preserve their dynamic properties upon interconnection with other modules, which permits…