Alex Slivkins: publications by topic

[home | all pubs] [Areas: bandits | crowdsourcing | social networks | Internet & P2P]
Hover on an item / touch the title to see its description. All pdf links are to "full versions".

Explore-exploit learning with resource constraints: e.g. dynamic pricing with limited supply, dynamic procurement on a budget, pay-per-click ad allocation with advertisers' budgets, etc.

Truthful mechanisms that learn over time. We study settings in which the algorithmic challenges of online learning, and particularly the exploration-exploitation tradeoff, are combined with the game-theoretic challenges of interacting with self-interested agents. Crowdsourcing systems: design of algorithms and incentives. Multi-armed bandits with a similarity structure on arms and/or contexts. Multi-armed bandits in a changing environment. Contextual bandits: computationally efficient algorithms for contextual bandits with policy sets.
Social networks Algorithms for Internet and P2P networks: network triangulation and network/metric embeddings, locality-aware distributed data structures, decentralized failure detection, etc. Peer-to-peer systems

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