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20242026
most citedNash Incentive-compatible Online Mechanism Learning via Weakly Differentially Private Online Learning

1 citations · 1 across the 10 of their papers we have counts for

collaborators

12 papers

cs.GT2026

Pairwise Exchanges of Freely Replicable Goods with Negative Externalities

Shangyuan Yang, Kirthevasan Kandasamy

We study a setting where a set of agents engage in pairwise exchanges of freely replicable goods (e.g., digital goods such as data), where two agents grant each other a copy of a g…

stat.ML2026

Learning from Biased and Costly Data Sources: Minimax-optimal Data Collection under a Budget

Michael O. Harding, Vikas Singh, Kirthevasan Kandasamy

Data collection is a critical component of modern statistical and machine learning pipelines, particularly when data must be gathered from multiple heterogeneous sources to study a…

cs.GT2025

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 the onli…

cs.LG2025

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…

cs.DC2025

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…

cs.LG2025

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…