no code implementations • 22 Apr 2024 • Jung-hun Kim, Milan Vojnovic, Se-Young Yun
In this study, we consider the infinitely many-armed bandit problems in a rested rotting setting, where the mean reward of an arm may decrease with each pull, while otherwise, it remains unchanged.
no code implementations • 21 Dec 2023 • Daniel Haimovich, Dima Karamshuk, Fridolin Linder, Niek Tax, Milan Vojnovic
This includes demonstrating convergence rate guarantees for loss-based sampling with various loss functions.
1 code implementation • 31 Jan 2022 • Jung-hun Kim, Milan Vojnovic, Se-Young Yun
We consider the infinitely many-armed bandit problem with rotting rewards, where the mean reward of an arm decreases at each pull of the arm according to an arbitrary trend with maximum rotting rate $\varrho=o(1)$.
1 code implementation • 13 Dec 2021 • Jung-hun Kim, Milan Vojnovic
In this paper, we study scheduling in multi-class, multi-server queueing systems with stochastic rewards of job-server assignments following a bilinear model in feature vectors characterizing jobs and servers.
no code implementations • 31 Jul 2021 • Flore Sentenac, Jialin Yi, Clément Calauzènes, Vianney Perchet, Milan Vojnovic
Finding an optimal matching in a weighted graph is a standard combinatorial problem.
1 code implementation • NeurIPS 2021 • Dabeen Lee, Milan Vojnovic
Our numerical results demonstrate the efficacy of our algorithms and show that our regret analysis is nearly tight.
1 code implementation • 30 Dec 2020 • Dabeen Lee, Milan Vojnovic, Se-Young Yun
Motivated by recent developments in designing algorithms based on individual item scores for solving utility maximization problems, we study the framework of using test scores, defined as a statistic of observed individual item performance data, for solving the budgeted stochastic utility maximization problem.
1 code implementation • 1 Jan 2019 • Milan Vojnovic, Se-Young Yun, Kaifang Zhou
In this paper, we study a popular method for inference of the Bradley-Terry model parameters, namely the MM algorithm, for maximum likelihood estimation and maximum a posteriori probability estimation.
1 code implementation • NeurIPS 2018 • Moez Draief, Konstantin Kutzkov, Kevin Scaman, Milan Vojnovic
We present novel graph kernels for graphs with node and edge labels that have ordered neighborhoods, i. e. when neighbor nodes follow an order.
no code implementations • 2 Mar 2017 • Virag Shah, Lennart Gulikers, Laurent Massoulie, Milan Vojnovic
To address this challenge, we develop a model of a task-expert matching system where a task is matched to an expert using not only the prior information about the task but also the feedback obtained from the past matches.
2 code implementations • NeurIPS 2017 • Dan Alistarh, Demjan Grubic, Jerry Li, Ryota Tomioka, Milan Vojnovic
In this paper, we propose Quantized SGD (QSGD), a family of compression schemes which allow the compression of gradient updates at each node, while guaranteeing convergence under standard assumptions.
no code implementations • NeurIPS 2015 • Dan Alistarh, Jennifer Iglesias, Milan Vojnovic
In many applications, the data is of rich structure that can be represented by a hypergraph, where the data items are represented by vertices and the associations among items are represented by hyperedges.
no code implementations • NeurIPS 2014 • Fajwel Fogel, Alexandre d'Aspremont, Milan Vojnovic
Intuitively, the algorithm assigns similar rankings to items that compare similarly with all others.
no code implementations • 20 Jun 2014 • Fajwel Fogel, Alexandre d'Aspremont, Milan Vojnovic
We first show that this spectral seriation algorithm recovers the true ranking when all pairwise comparisons are observed and consistent with a total order.