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Strategy-robust Online Learning in Contextual Pricing
Joon Suk Huh, Kirthevasan Kandasamy
Learning effective pricing strategies is crucial in digital marketplaces, especially when buyers' valuations are unknown and must be inferred through interaction. We study online c…
Constrained Best Arm Identification with Tests for Feasibility
Ting Cai, Kirthevasan Kandasamy
Best arm identification (BAI) aims to identify the highest-performance arm among a set of arms by collecting stochastic samples from each arm. In real-world problems, the best…
Agora: A System for Consumption-Based GPU Pricing
Ian McDougall, Noah Scott, Joon Huh +2
We present Agora, a lightweight system designed for cloud-based GPUs which meters a three-dimensional resource vector from commodity performance counters and prices it with a funct…
A Cramér-von Mises Approach to Incentivizing Truthful Data Sharing
Alex Clinton, Thomas Zeng, Yiding Chen +2
Modern data marketplaces and data sharing consortia increasingly rely on incentive mechanisms to encourage agents to contribute data. However, schemes that reward agents based on t…
Balancing Performance and Costs in Best Arm Identification
Michael O. Harding, Kirthevasan Kandasamy
We consider the problem of identifying the best arm in a multi-armed bandit model. Despite a wealth of literature in the traditional fixed budget and fixed confidence regimes of th…
Incentivizing Truthful Data Contributions in a Marketplace for Mean Estimation
Keran Chen, Alex Clinton, Kirthevasan Kandasamy
We study a data marketplace where a broker intermediates between buyers, who seek to estimate the mean \(μ\) of an unknown normal distribution \(\Ncal(μ, σ^2)\), and contributors,…