Thodoris Lykouris | DeepAI

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∙ 08/15/2023

Quantifying the Cost of Learning in Queueing Systems

Queueing systems are widely applicable stochastic models with use cases ...

0 Daniel Freund, et al. ∙

∙ 01/25/2023

Group fairness in dynamic refugee assignment

Ensuring that refugees and asylum seekers thrive (e.g., find employment)...

0 Daniel Freund, et al. ∙

∙ 08/19/2022

Learning in Stackelberg Games with Non-myopic Agents

We study Stackelberg games where a principal repeatedly interacts with a...

0 Nika Haghtalab, et al. ∙

∙ 06/05/2022

Efficient decentralized multi-agent learning in asymmetric queuing systems

We study decentralized multi-agent learning in bipartite queuing systems...

0 Daniel Freund, et al. ∙

∙ 07/03/2021

Bayesian decision-making under misspecified priors with applications to meta-learning

Thompson sampling and other Bayesian sequential decision-making algorith...

13 Max Simchowitz, et al. ∙

∙ 07/15/2020

Static pricing for multi-unit prophet inequalities

We study a pricing problem where a seller has k identical copies of a pr...

0 Shuchi Chawla, et al. ∙

∙ 06/09/2020

Constrained episodic reinforcement learning in concave-convex and knapsack settings

We propose an algorithm for tabular episodic reinforcement learning with...

8 Kianté Brantley, et al. ∙

∙ 03/04/2020

Bandits with adversarial scaling

We study "adversarial scaling", a multi-armed bandit model where rewards...

0 Thodoris Lykouris, et al. ∙

∙ 02/26/2020

Corrupted Multidimensional Binary Search: Learning in the Presence of Irrational Agents

Standard game-theoretic formulations for settings like contextual pricin...

13 Akshay Krishnamurthy, et al. ∙

∙ 11/20/2019

Corruption Robust Exploration in Episodic Reinforcement Learning

We initiate the study of multi-stage episodic reinforcement learning und...

12 Thodoris Lykouris, et al. ∙

∙ 09/18/2019

Advancing subgroup fairness via sleeping experts

We study methods for improving fairness to subgroups in settings with ov...

1 Avrim Blum, et al. ∙

∙ 05/23/2019

Graph regret bounds for Thompson Sampling and UCB

We study the stochastic multi-armed bandit problem with the graph-based ...

0 Thodoris Lykouris, et al. ∙

∙ 10/28/2018

On preserving non-discrimination when combining expert advice

We study the interplay between sequential decision making and avoiding d...

0 Avrim Blum, et al. ∙

∙ 03/25/2018

Stochastic bandits robust to adversarial corruptions

We introduce a new model of stochastic bandits with adversarial corrupti...

0 Thodoris Lykouris, et al. ∙

∙ 02/15/2018

Competitive caching with machine learned advice

Traditional online algorithms encapsulate decision making under uncertai...

0 Thodoris Lykouris, et al. ∙

∙ 11/09/2017

Small-loss bounds for online learning with partial information

We consider the problem of adversarial (non-stochastic) online learning ...

0 Thodoris Lykouris, et al. ∙

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