257 citations · 519 across the 43 of their papers we have counts for
48 papers
The Price of Simplicity: Analyzing Decoupled Policies for Multi-Location Inventory Control
Yohan John, Vade Shah, James A. Preiss +2
What is the performance cost of using simple, decoupled control policies in inherently coupled systems? Motivated by industrial refrigeration systems, where centralized compressors…
A Safe First-Order Method for Pricing-Based Resource Allocation in Safety-Critical Networks
Berkay Turan, Spencer Hutchinson, Mahnoosh Alizadeh
We introduce a novel algorithm for solving network utility maximization (NUM) problems that arise in resource allocation schemes over networks with known safety-critical constraint…
Reinforcement Strategies in General Lotto Games
Keith Paarporn, Rahul Chandan, Mahnoosh Alizadeh +1
Strategic decisions are often made over multiple periods of time, wherein decisions made earlier impact a competitor's success in later stages. In this paper, we study these dynami…
Directional Optimism for Safe Linear Bandits
Spencer Hutchinson, Berkay Turan, Mahnoosh Alizadeh
The safe linear bandit problem is a version of the classical stochastic linear bandit problem where the learner's actions must satisfy an uncertain constraint at all rounds. Due it…
Safe Pricing Mechanisms for Distributed Resource Allocation with Bandit Feedback
Spencer Hutchinson, Berkay Turan, Mahnoosh Alizadeh
In societal-scale infrastructures, such as electric grids or transportation networks, pricing mechanisms are often used as a way to shape users' demand in order to lower operating…
The Impact of the Geometric Properties of the Constraint Set in Safe Optimization with Bandit Feedback
Spencer Hutchinson, Berkay Turan, Mahnoosh Alizadeh
We consider a safe optimization problem with bandit feedback in which an agent sequentially chooses actions and observes responses from the environment, with the goal of maximizing…
Predicting Parameters for Modeling Traffic Participants
Ahmadreza Moradipari, Sangjae Bae, Mahnoosh Alizadeh +2
Accurately modeling the behavior of traffic participants is essential for safely and efficiently navigating an autonomous vehicle through heavy traffic. We propose a method, based…
Strategic investments in multi-stage General Lotto games
Rahul Chandan, Keith Paarporn, Mahnoosh Alizadeh +1
In adversarial interactions, one is often required to make strategic decisions over multiple periods of time, wherein decisions made earlier impact a player's competitive standing…
Safe Dual Gradient Method for Network Utility Maximization Problems
Berkay Turan, Mahnoosh Alizadeh
In this paper, we introduce a novel first-order dual gradient algorithm for solving network utility maximization problems that arise in resource allocation schemes over networks wi…
A Deployable Online Optimization Framework for EV Smart Charging with Real-World Test Cases
Nathaniel Tucker, Mahnoosh Alizadeh
We present a customizable online optimization framework for real-time EV smart charging to be readily implemented at real large-scale charging facilities. Notably, due to real-worl…
Collaborative Multi-agent Stochastic Linear Bandits
Ahmadreza Moradipari, Mohammad Ghavamzadeh, Mahnoosh Alizadeh
We study a collaborative multi-agent stochastic linear bandit setting, where agents that form a network communicate locally to minimize their overall regret. In this setting, e…
Multi-Environment Meta-Learning in Stochastic Linear Bandits
Ahmadreza Moradipari, Mohammad Ghavamzadeh, Taha Rajabzadeh +2
In this work we investigate meta-learning (or learning-to-learn) approaches in multi-task linear stochastic bandit problems that can originate from multiple environments. Inspired…
Real-Time Electric Vehicle Smart Charging at Workplaces: A Real-World Case Study
Nathaniel Tucker, Gustavo Cezar, Mahnoosh Alizadeh
We study a real-time smart charging algorithm for electric vehicles (EVs) at a workplace parking lot in order to minimize electricity cost from time-of-use electricity rates and de…
Strategically revealing intentions in General Lotto games
Keith Paarporn, Rahul Chandan, Dan Kovenock +2
Strategic decision-making in uncertain and adversarial environments is crucial for the security of modern systems and infrastructures. A salient feature of many optimal decision-ma…
An Online Scheduling Algorithm for a Community Energy Storage System
Nathaniel Tucker, Mahnoosh Alizadeh
In this paper, we consider a community energy storage (CES) system that is shared by various electricity consumers who want to charge and discharge the CES throughout a given time…
Robust Distributed Optimization With Randomly Corrupted Gradients
Berkay Turan, Cesar A. Uribe, Hoi-To Wai +1
In this paper, we propose a first-order distributed optimization algorithm that is provably robust to Byzantine failures-arbitrary and potentially adversarial behavior, where all t…
A General Lotto game with asymmetric budget uncertainty
Keith Paarporn, Rahul Chandan, Mahnoosh Alizadeh +1
The General Lotto game is a popular variant of the famous Colonel Blotto game, in which two opposing players allocate limited resources over many battlefields. In this paper, we co…
Feature and Parameter Selection in Stochastic Linear Bandits
Ahmadreza Moradipari, Berkay Turan, Yasin Abbasi-Yadkori +2
We study two model selection settings in stochastic linear bandits (LB). In the first setting, which we refer to as feature selection, the expected reward of the LB problem is in t…
The Division of Assets in Multiagent Systems: A Case Study in Team Blotto Games
Keith Paarporn, Rahul Chandan, Mahnoosh Alizadeh +1
Multi-agent systems are designed to concurrently accomplish a diverse set of tasks at unprecedented scale. Here, the central problems faced by a system operator are to decide (i) h…
Stage-wise Conservative Linear Bandits
Ahmadreza Moradipari, Christos Thrampoulidis, Mahnoosh Alizadeh
We study stage-wise conservative linear stochastic bandits: an instance of bandit optimization, which accounts for (unknown) safety constraints that appear in applications such as…
On Robustness of the Normalized Subgradient Method with Randomly Corrupted Subgradients
Berkay Turan, Cesar A. Uribe, Hoi-To Wai +1
Numerous modern optimization and machine learning algorithms rely on subgradient information being trustworthy and hence, they may fail to converge when such information is corrupt…
Competition in Electric Autonomous Mobility on Demand Systems
Berkay Turan, Mahnoosh Alizadeh
This paper investigates the impacts of competition in autonomous mobility-on-demand systems. By adopting a network-flow based formulation, we first determine the optimal strategies…
Regret Bounds for Safe Gaussian Process Bandit Optimization
Sanae Amani, Mahnoosh Alizadeh, Christos Thrampoulidis
Many applications require a learner to make sequential decisions given uncertainty regarding both the system's payoff function and safety constraints. In safety-critical systems, i…
Resilient Primal-Dual Optimization Algorithms for Distributed Resource Allocation
Berkay Turan, Cesar A. Uribe, Hoi-To Wai +1
Distributed algorithms for multi-agent resource allocation can provide privacy and scalability over centralized algorithms in many cyber-physical systems. However, the distributed…