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ULTRA: Unbiased Learning to Rank Algorithms toolbox

posted May 3, 2020, 10:45 AM by Qingyao Ai   [ updated May 3, 2020, 10:45 AM ]

ULTRA is a toolkit for unbiased/online learning to rank algorithms. It was developed with a focus on facilitating the designing, comparing and sharing of unbiased/online learning to rank algorithms. ULTRA creates a single pipeline for input/simulating noisy labels (e.g., clicks), implementing different ranking models, and testing different learning algorithms. There are a number of unbiased/online learning to rank algorithms, such as IPWrank, DLA, RegressionEM, DBGD, PDGD, and PairwiseDebias, designed with a unified interface. It also have a number of ranking models that support gradient descent optimizations, such as DNN, linear regression, DLCM, GSF, and SetRank. We are always happy to receive any code contributions, suggestions, and comments.

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