Efficiency of training for ranking systems
First Claim
1. Method for facilitating training of a learning machine utilizing a pairwise algorithm, comprising:
- generating a score for each of a plurality of data items;
maintaining the scores for the plurality of data items;
generating at least one gradient for each of the plurality of data items based at least in part upon the maintained scores of pairs of data items; and
updating the learning machine based at least in part upon the at least one gradient of each of the plurality of data items.
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Accused Products
Abstract
The subject disclosure pertains to systems and methods for facilitating training of machine learning systems utilizing pairwise training. The number of computations required during pairwise training is reduced by grouping the computations. First, a score is generated for each retrieved data item. During processing of the data item pairs, the scores of the data items in the pair are retrieved and used to generate a gradient for each data item. Once all of the pairs have been processed, the gradients for each data item are aggregated and the aggregated gradients are used to update the machine learning system.
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Citations
20 Claims
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1. Method for facilitating training of a learning machine utilizing a pairwise algorithm, comprising:
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generating a score for each of a plurality of data items;
maintaining the scores for the plurality of data items;
generating at least one gradient for each of the plurality of data items based at least in part upon the maintained scores of pairs of data items; and
updating the learning machine based at least in part upon the at least one gradient of each of the plurality of data items. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. A system for facilitating training of a learning machine utilizing a pairwise algorithm, comprising:
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a scorer component that generates a score for each of a plurality of data items;
a memory component that maintains the score for each of the plurality of data items;
a pair processor component that generates a gradient for each data item in a pair of data items based at least in part upon the scores for the data items in the pair; and
an update component that updates the learning machine based at least in part upon all of the gradients for each data item of the plurality of data items. - View Dependent Claims (12, 13, 14, 15, 16, 17)
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18. A system for training a learning machine using pairwise training, comprising:
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means for generating a score for each of a plurality of data items;
means for maintaining the scores for the plurality of data items;
means for generating gradients for the plurality of data items based at least in part upon the scores of pairs of data items; and
means for updating the learning machine based at least in part upon the gradients of each of the plurality of data items. - View Dependent Claims (19, 20)
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Specification