Zobrazeno 1 - 10
of 40
pro vyhledávání: '"Kollias, Kostas"'
Autor:
Karntikoon, Kritkorn, Shen, Yiheng, Gollapudi, Sreenivas, Kollias, Kostas, Schild, Aaron, Sinop, Ali
Solving optimization problems leads to elegant and practical solutions in a wide variety of real-world applications. In many of those real-world applications, some of the information required to specify the relevant optimization problem is noisy, unc
Externí odkaz:
http://arxiv.org/abs/2403.10640
Autor:
Bhaskara, Aditya, Gollapudi, Sreenivas, Im, Sungjin, Kollias, Kostas, Munagala, Kamesh, Sankar, Govind S.
This paper explores the design of a balanced data-sharing marketplace for entities with heterogeneous datasets and machine learning models that they seek to refine using data from other agents. The goal of the marketplace is to encourage participatio
Externí odkaz:
http://arxiv.org/abs/2401.13053
Electric vehicle (EV) adoption in long-distance logistics faces challenges such as range anxiety and uneven distribution of charging stations. Two pivotal questions emerge: How can EVs be efficiently routed in a charging network considering range lim
Externí odkaz:
http://arxiv.org/abs/2311.05040
Historically, much of machine learning research has focused on the performance of the algorithm alone, but recently more attention has been focused on optimizing joint human-algorithm performance. Here, we analyze a specific type of human-algorithm c
Externí odkaz:
http://arxiv.org/abs/2308.11721
For traffic routing platforms, the choice of which route to recommend to a user depends on the congestion on these routes -- indeed, an individual's utility depends on the number of people using the recommended route at that instance. Motivated by th
Externí odkaz:
http://arxiv.org/abs/2301.09251
We consider the classic online learning and stochastic multi-armed bandit (MAB) problems, when at each step, the online policy can probe and find out which of a small number ($k$) of choices has better reward (or loss) before making its choice. In th
Externí odkaz:
http://arxiv.org/abs/2211.02703
A central goal in algorithmic game theory is to analyze the performance of decentralized multiagent systems, like communication and information networks. In the absence of a central planner who can enforce how these systems are utilized, the users ca
Externí odkaz:
http://arxiv.org/abs/2205.04252
We study a dynamic traffic assignment model, where agents base their instantaneous routing decisions on real-time delay predictions. We formulate a mathematically concise model and define dynamic prediction equilibrium (DPE) in which no agent can at
Externí odkaz:
http://arxiv.org/abs/2109.06713
Autor:
Gollapudi, Sreenivas, Guruganesh, Guru, Kollias, Kostas, Manurangsi, Pasin, Leme, Renato Paes, Schneider, Jon
We consider the following variant of contextual linear bandits motivated by routing applications in navigational engines and recommendation systems. We wish to learn a hidden $d$-dimensional value $w^*$. Every round, we are presented with a subset $\
Externí odkaz:
http://arxiv.org/abs/2106.04819
A two-sided market consists of two sets of agents, each of whom have preferences over the other (Airbnb, Upwork, Lyft, Uber, etc.). We propose and analyze a repeated matching problem, where some set of matches occur on each time step, and our goal is
Externí odkaz:
http://arxiv.org/abs/2009.09336