6 papers
Human-AI Collaboration with Misaligned Preferences
Jiaxin Song, Parnian Shahkar, Kate Donahue +1
In many real-life settings, algorithms play the role of assistants, while humans ultimately make the final decision. Often, algorithms specifically act as curators, narrowing down…
The Complexity of Finding Local Optima in Contrastive Learning
Jingming Yan, Yiyuan Luo, Vaggos Chatziafratis +3
Contrastive learning is a powerful technique for discovering meaningful data representations by optimizing objectives based on , often given as a…
On the Existence and Complexity of Core-Stable Data Exchanges
Jiaxin Song, Pooja Kulkarni, Parnian Shahkar +1
The rapid growth of data-driven technologies and the emergence of various data-sharing paradigms have underscored the need for efficient and stable data exchange protocols. In any…
Welfare Approximation in Additively Separable Hedonic Games
Martin Bullinger, Vaggos Chatziafratis, Parnian Shahkar
Partitioning a set of items or agents while maximizing the value of the partition is a fundamental algorithmic task. We study this problem in the specific setting of maximizing…
Improved MMS Approximations for Few Agent Types
Jugal Garg, Parnian Shahkar
We study fair division of indivisible goods under the maximin share (MMS) fairness criterion in settings where agents are grouped into a small number of types, with agents within e…
Online Fair Division: Towards Ex-Post Constant MMS Guarantees
Pooja Kulkarni, Ruta Mehta, Parnian Shahkar
We investigate the problem of fairly allocating indivisible items among sequentially arriving agents with additive valuations, under the sought-after fairness notion of max…