In competitive ML markets, standard gradient training can drive learners into overspecialized equilibria with arbitrarily poor global performance; a proposed 'peer probing' algorithm provably escapes this under informative probing sources.
Social media polarization and echo chambers in the context of covid-19: Case study.JMIRx med, 2(3):e29570, 2021
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Dynamics of Learning under User Choice: Overspecialization and Peer-Model Probing
In competitive ML markets, standard gradient training can drive learners into overspecialized equilibria with arbitrarily poor global performance; a proposed 'peer probing' algorithm provably escapes this under informative probing sources.