no code implementations • 15 May 2024 • Jonathan Gornet, Bruno Sinopoli
A specific variation of the stochastic multi-armed bandit problem is the restless bandit, where the reward for each action is sampled from a Markov chain.
Decision Making Under Uncertainty Hyperparameter Optimization
no code implementations • 15 Nov 2023 • Bahram Yaghooti, Netanel Raviv, Bruno Sinopoli
Specifically, by applying the GS process over a family of functions which presumably captures the nonlinear dependencies in the data, we construct a series of covariance matrices that can either be used to identify new large-variance directions, or to remove those dependencies from the principal components.
no code implementations • 21 Oct 2023 • Carmel Fiscko, Aayushya Agarwal, Yihan Ruan, Soummya Kar, Larry Pileggi, Bruno Sinopoli
We present a stochastic first-order optimization method specialized for deep neural networks (DNNs), ECCO-DNN.
no code implementations • 24 Apr 2023 • Carmel Fiscko, Soummya Kar, Bruno Sinopoli
The controller's objective is to find an optimal policy that maximizes the value of the expected system given a priori knowledge of the agents' dropout probabilities.
no code implementations • 5 Feb 2023 • Carmel Fiscko, Soummya Kar, Bruno Sinopoli
In this work we investigate an importance sampling approach for evaluating policies for a structurally time-varying factored Markov decision process (MDP), i. e. the policy's value is estimated with a high-probability confidence interval.
no code implementations • 15 Nov 2022 • Aayushya Agarwal, Carmel Fiscko, Soummya Kar, Larry Pileggi, Bruno Sinopoli
To find the value of the critical point, we propose a time step search routine for Forward Euler discretization that controls the local truncation error, a method adapted from circuit simulation ideas.
no code implementations • 30 Jul 2022 • Paul Griffioen, Raffaele Romagnoli, Bruce H. Krogh, Bruno Sinopoli
Decentralized control systems are widely used in a number of situations and applications.
no code implementations • 11 Jul 2022 • Carmel Fiscko, Soummya Kar, Bruno Sinopoli
To efficiently find a policy in this rapidly scaling space, we propose a clustered Bellman operator that optimizes over the action space for one cluster at any evaluation.
no code implementations • 1 May 2022 • Paul Griffioen, Bruce H. Krogh, Bruno Sinopoli
To counter such attackers, a response scheme must be implemented that keeps the attacker from corrupting the inputs and outputs of the system for certain periods of time.
no code implementations • 6 Apr 2022 • Jonathan Gornet, Mehdi Hosseinzadeh, Bruno Sinopoli
The proposed strategy for this stochastic multi-armed bandit variant is to learn a model of the dynamical system while choosing the optimal action based on the learned model.
no code implementations • 1 Feb 2022 • Dario Stabili, Raffaele Romagnoli, Mirco Marchetti, Bruno Sinopoli, Michele Colajanni
This paper proposes a novel approach for the study of cyber-attacks against the powertrain of a generic vehicle.
no code implementations • 9 Feb 2021 • Mehdi Hosseinzadeh, Bruno Sinopoli, Aaron F. Bobick
It is shown that based upon the danger awareness coefficient and the proposed learning method, the robot can build a predictive human model to anticipate the human's future actions.
Robotics Systems and Control Systems and Control