# Learning Rankings via Convex Hull Separation

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##### Citations

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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

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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

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40,147 citations

### "Learning Rankings via Convex Hull S..." refers background in this paper

...Note that enforcing the constraints defined above indeed implies the desired ordering, since we have: Aw + y ≥ −γ ≥ γ̂ + 1 ≥ γ̂ ≥ Aw − y It is also important to note the connection with Support Vector Machines (SVM) formulation [10, 14] for the binary case....

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23,215 citations

### "Learning Rankings via Convex Hull S..." refers methods in this paper

...Ordinal regression and methods for handling structured output classes: For a classic description of generalized linear models for ordinal regre ssion, see [11]....

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5,933 citations

### "Learning Rankings via Convex Hull S..." refers background in this paper

...B′u− w′[A− ′ − A+ ′ ] = 0, b′u ≤ −1, u ≥ 0, (7) Where the second equivalent form of the constraints was obtained by negation (as before), and the third equivalent form results from ourthird key insight: the application of Farka’s theorem of alternatives[9]....

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4,453 citations

2,146 citations

### "Learning Rankings via Convex Hull S..." refers background in this paper

...Bu− w[A ′ − A ′ ] = 0, bu ≤ −1, u ≥ 0, (7) Where the second equivalent form of the constraints was obtai ned by negation (as before), and the third equivalent form results from our third key insight: the application of Farka’s theorem of alternatives[9]....

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