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07/25/2023
Mitigating Mainstream Bias in Recommendation via Cost-sensitive Learning
Mainstream bias, where some users receive poor recommendations because t...
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06/04/2021
New Insights into Metric Optimization for Ranking-based Recommendation
Direct optimization of IR metrics has often been adopted as an approach ...
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02/02/2021
Leave No User Behind: Towards Improving the Utility of Recommender Systems for Non-mainstream Users
In a collaborative-filtering recommendation scenario, biases in the data...
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05/27/2019
Statistical Significance Testing in Information Retrieval: An Empirical Analysis of Type I, Type II and Type III Errors
Statistical significance testing is widely accepted as a means to assess...
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04/15/2019
Are Nearby Neighbors Relatives?: Diagnosing Deep Music Embedding Spaces
Deep neural networks have frequently been used to directly learn represe...
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02/12/2018
