Learning Rankings via Convex Hull Separation
Citations
2,515 citations
Cites background from "Learning Rankings via Convex Hull S..."
...• Other learning-to-rank algorithms [15, 19, 32, 93, 109, 127, 142, 143, 144] that are based on association rules, decision systems, and other technologies; other theoretical analysis on ranking [50]; and applications of learning-to-rank methods [87, 128]....
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2,003 citations
873 citations
Cites background from "Learning Rankings via Convex Hull S..."
...For other approaches to learning to rank, refer to [2, 11, 31]....
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591 citations
References
1,889 citations
"Learning Rankings via Convex Hull S..." refers methods in this paper
...In other related work, boosting methods have been p roposed for learning preferences [3], and a combinatorial structure called the ranking poset was used for conditional modeling of partially ranked data[8], in the context of comb ining ranked sets of web pages produced by various web-page search engines....
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1,888 citations
1,446 citations
"Learning Rankings via Convex Hull S..." refers methods in this paper
...g.[13] presents SVM based algorithms for handling structured and i nterdependent output spaces, and [5] discusses automatic document categorization into p re-defined hierarchies or taxonomies of topics....
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1,049 citations
"Learning Rankings via Convex Hull S..." refers background or methods in this paper
...By contrast, bipartite ranking solutions are evaluated using theWilcoxon-Mann-Whitney (WMW) statistic which measures the (sample averaged) probability that anypair of samples is ordered correctly; intuitively, the WMW statistic may be interpreted as thearea under the ROC curve(AUC)....
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...Experiments on public benchmarks indicate that: (a) the proposed algorithm s at least as accurate as the current state-of-the-art; (b) computationally, it is several orders of magnitude faster and—unlike current methods—it is easily able to handle even large datasets with over 20,000 samples....
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...Ordinal regression and methods for handling structured output classes: For a classic description of generalized linear models for ordinal regression, see [11]....
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...W compare our method against SVM for ranking (e.g.[4, 6]) using the SVM-light package2 and an efficient Gaussian process method (the informative vector machine)3 [7]....
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864 citations
"Learning Rankings via Convex Hull S..." refers background or methods in this paper
...g.[4, 6]) using the SVM-light package 2 and an efficient Gaussian process method (the informative ve ctor machine)3 [7]....
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...g.[4]) as a special case when each set A is reduced to a singleton and the order graph is equal to...
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...Learning Rankings: The problem of learning rankings was first treated as a classi fication problem on pairs of objects by Herbrich [4] and subsequently used on a web page ranking task by Joachims [6]; a variety of authors have investigated this approach recently....
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...Learning Rankings: The problem of learning rankings was first treated as a classification problem on pairs of objects by Herbrich [4] and subsequentlyused on a web page ranking task by Joachims [6]; a variety of authors have investigatedthis approach recently....
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...Relationship to the proposed work:Our algorithm penalizes wrong ordering of pairs of training instances in order to learn ranking functions (sim ilar to [4]), but in addition, it can also utilize the notion of a structured class order graph....
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