Publication

Anonymous Linear Bandits for Multi-User Systems

2026

Abstract

We provide the first anonymity-preserving algorithm for a centralized decision maker in linear bandit-based multiuser systems. Our algorithm employs successive elimination techniques for linear bandits to build an assignment multi-graph (from users to arms) along with a greedy matching algorithm that efficiently allocates the arms to users. We provide lower and upper bounds for this problem, showing that our algorithm is regret optimal up to a √ 𝐶𝐾 factor. CCS Concepts • Theory of computation → Sequential decision making; Online learning algorithms; • Security and privacy → Data anonymization and sanitization; Privacy protections.

Official source

https://infoscience.epfl.ch/entities/publication/e12df101-7490-4848-a821-4df8e4a7de2c

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2026

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/e12df101-7490-4848-a821-4df8e4a7de2c

About this result

Related concepts (32)

Prim's algorithm

In computer science, Prim's algorithm (also known as Jarník's algorithm) is a greedy algorithm that finds a minimum spanning tree for a weighted undirected graph. This means it finds a subset of the edges that forms a tree that includes every vertex, where the total weight of all the edges in the tree is minimized. The algorithm operates by building this tree one vertex at a time, from an arbitrary starting vertex, at each step adding the cheapest possible connection from the tree to another vertex.

Greedy algorithm

A greedy algorithm is any algorithm that follows the problem-solving heuristic of making the locally optimal choice at each stage. In many problems, a greedy strategy does not produce an optimal solution, but a greedy heuristic can yield locally optimal solutions that approximate a globally optimal solution in a reasonable amount of time. For example, a greedy strategy for the travelling salesman problem (which is of high computational complexity) is the following heuristic: "At each step of the journey, visit the nearest unvisited city.

Privacy-enhancing technologies

Privacy-enhancing technologies (PET) are technologies that embody fundamental data protection principles by minimizing personal data use, maximizing data security, and empowering individuals. PETs allow online users to protect the privacy of their personally identifiable information (PII), which is often provided to and handled by services or applications. PETs use techniques to minimize an information system's possession of personal data without losing functionality.

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