Learning to rank using gradient descent
Citations
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13,246 citations
8,059 citations
Cites background from "Learning to rank using gradient des..."
...This is a special kind of neural network known as RankNet (Burges et al. 2005) (see Section 16....
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3,429 citations
2,515 citations
Cites background or methods from "Learning to rank using gradient des..."
...In recent years, learning to rank has become a very hot research direction in IR, and a large number of learning-to-rank algorithms have been proposed, such as [9, 13, 14, 16, 17, 26, 29, 33, 34, 47, 49, 59, 63, 73, 78, 90, 97, 99, 102, 114, 119, 122, 129, 134, 136]....
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...Example algorithms belonging to the pairwise approach include [9, 14, 16, 29, 47, 63, 97, 122]....
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2,037 citations
References
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13,246 citations
"Learning to rank using gradient des..." refers background in this paper
...two layer neural nets can approximate any bounded continuous function (Mitchell, 1997)), and since they are often faster in test phase than competing kernel methods (and test speed is critical for this application); however our cost function could equally well be applied to a variety of machine learning algorithms....
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...…to explore these ideas using neural networks, since they are flexible (e.g. two layer neural nets can approximate any bounded continuous function (Mitchell, 1997)), and since they are often faster in test phase than competing kernel methods (and test speed is critical for this application);…...
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2,980 citations
"Learning to rank using gradient des..." refers background or methods in this paper
...4One can also view this as a weight sharing update for a Siamese-like net(Bromley et al., 1993)....
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...Table 2 compares results, for the polynomial ranking function, of training on ties, assigning P = 1 for nonties and P = 0.5 for ties, using a two layer net with 10 hidden units....
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1,992 citations
"Learning to rank using gradient des..." refers background in this paper
...In (Hastie & Tibshirani, 1998) and (Bradley & Terry, 1952), the authors consider models of the following form: for some fixed set of events A1, . . . , Ak, pairwise probabilities P (Ai|Ai or Aj) are given, and it is assumed that there is a set of probabilities P̂i such that P (Ai|Ai or Aj) =…...
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...In (Hastie & Tibshirani, 1998) and ( Bradley & Terry, 1952 ), the authors consider models of the following form: for some xed set of events A1; : : : ; Ak, pairwise probabilities P (AijAi or Aj) are given, and it is assumed that there is a set of probabilities ^...
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1,889 citations
"Learning to rank using gradient des..." refers background or methods in this paper
...PRank learns using one example at a time, which is held as an advantage over pair-based methods (e.g. (Freund et al., 2003)), since the latter must learn using O(m2) pairs rather than m examples....
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...In (Freund et al., 2003), results are given using decision stumps as the weak learners....
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...RankBoost (Freund et al., 2003) is another ranking algorithm that is trained on pairs, and which is closer in spirit to our work since it attempts to solve the preference learning problem directly, rather than solving an ordinal regression problem....
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...(Freund et al., 2003)), since the latter must learn using O(m(2)) pairs rather than m examples....
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