A recurring scholarly workshop bringing together machine-learning and data-mining researchers advancing recommender systems — calls for papers, topics of interest, programs, and proceedings from each edition.
A dedicated resource for ML/DM researchers, PhD students, and industry data scientists who submit papers, serve on program committees, and attend the MLRec workshop co-located with the SIAM International Conference on Data Mining (SDM).
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(Please provide the ORIGINAL and TRANSLATED text to receive the edited version.) Key Takeaways - Matrix factorization with confidence weighting (WRMF/ALS)
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material typically covers four model families — neighborhood methods, matrix factorization, item-item si
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Researchers in recommender systems may find practical examples of information architecture in this directory of digital tools for displaced people.
Academic researchers can ensure their project portals remain usable for everyone by applying principles of inclusive front-end development.
Researchers studying recommendation algorithms may find a useful real-world dataset within this local services directory.