RankGuard is a decentralized OLTR system that filters model updates using local click data for poisoning resistance and supplies the first formal convergence guarantee for decentralized OLTR.
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Eye-tracking study shows F-pattern and examination hypothesis from web search do not hold in carousel interfaces; users follow an L-pattern on clicks, ignore headings, and examination does not predict clicks as assumed.
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Efficient and Robust Online Learning to Rank in Decentralized Systems
RankGuard is a decentralized OLTR system that filters model updates using local click data for poisoning resistance and supplies the first formal convergence guarantee for decentralized OLTR.
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Following the Eye-Tracking Evidence: Established Web-Search Assumptions Fail in Carousel Interfaces
Eye-tracking study shows F-pattern and examination hypothesis from web search do not hold in carousel interfaces; users follow an L-pattern on clicks, ignore headings, and examination does not predict clicks as assumed.