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Ranking functions and rankings on languages

by Franz Huber , 2006
"... The Spohnian paradigm of ranking functions is in many respects like an order-of-magnitude reverse of subjective probability theory. Unlike probabilities, however, ranking functions are only indirectly—via a pointwise ranking function on the underlying set of possibilities W—defined on a field of pro ..."
Abstract - Cited by 15 (8 self) - Add to MetaCart
The Spohnian paradigm of ranking functions is in many respects like an order-of-magnitude reverse of subjective probability theory. Unlike probabilities, however, ranking functions are only indirectly—via a pointwise ranking function on the underlying set of possibilities W—defined on a field

Learning to rank using gradient descent

by Chris Burges, Tal Shaked, Erin Renshaw, Matt Deeds, Nicole Hamilton, Greg Hullender - In ICML , 2005
"... We investigate using gradient descent methods for learning ranking functions; we propose a simple probabilistic cost function, and we introduce RankNet, an implementation of these ideas using a neural network to model the underlying ranking function. We present test results on toy data and on data f ..."
Abstract - Cited by 534 (17 self) - Add to MetaCart
We investigate using gradient descent methods for learning ranking functions; we propose a simple probabilistic cost function, and we introduce RankNet, an implementation of these ideas using a neural network to model the underlying ranking function. We present test results on toy data and on data

Rank Aggregation Methods for the Web

by Cynthia Dwork, Ravi Kumar, Moni Naor, D. Sivakumar , 2010
"... We consider the problem of combining ranking results from various sources. In the context of the Web, the main applications include building meta-search engines, combining ranking functions, selecting documents based on multiple criteria, and improving search precision through word associations. Wed ..."
Abstract - Cited by 478 (6 self) - Add to MetaCart
We consider the problem of combining ranking results from various sources. In the context of the Web, the main applications include building meta-search engines, combining ranking functions, selecting documents based on multiple criteria, and improving search precision through word associations

Learnability of Bipartite Ranking Functions

by Shivani Agarwal, Dan Roth - PROCEEDINGS OF THE 18TH ANNUAL CONFERENCE ON LEARNING THEORY , 2005
"... The problem of ranking, in which the goal is to learn a real-valued ranking function that induces a ranking or ordering over an instance space, has recently gained attention in machine learning. We define a model of learnability for ranking functions in a particular setting of the ranking problem k ..."
Abstract - Cited by 12 (2 self) - Add to MetaCart
The problem of ranking, in which the goal is to learn a real-valued ranking function that induces a ranking or ordering over an instance space, has recently gained attention in machine learning. We define a model of learnability for ranking functions in a particular setting of the ranking problem

On the impossibility of certain ranking functions

by Jin-yi Cai - International Mathematical Journal
"... Suppose all the individuals in a field are linearly ordered. Groups of individuals form teams. Is there a perfect ranking function of each team based on the members of the team? We prove that under a very mild and reasonable set of axioms for the ranking function, no such ranking function exists. AM ..."
Abstract - Cited by 1 (0 self) - Add to MetaCart
Suppose all the individuals in a field are linearly ordered. Groups of individuals form teams. Is there a perfect ranking function of each team based on the members of the team? We prove that under a very mild and reasonable set of axioms for the ranking function, no such ranking function exists

Eventual Linear Ranking Functions

by Roberto Bagnara, Fred Mesnard
"... Program termination is a hot research topic in program analysis. The last few years have witnessed the development of termination analyzers for programming languages such as C and Java with remarkable precision and performance. These systems are largely based on techniques and tools coming from the ..."
Abstract - Cited by 1 (0 self) - Add to MetaCart
the field of declarative constraint programming. In this paper, we first recall an algorithm based on Farkas ’ Lemma for discovering linear ranking functions proving termination of a certain class of loops. Then we propose an extension of this method for showing the existence of eventual linear ranking

On Rank Functions of Graphs

by Aaron J Klein , 2013
"... We study rank functions (also known as graph homomorphisms onto Z), ways of imposing graded poset structures on graphs. We first look at a variation on rank functions called discrete Lipschitz functions. We relate the number of Lipschitz functions of a graph G to the number of rank functions of both ..."
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We study rank functions (also known as graph homomorphisms onto Z), ways of imposing graded poset structures on graphs. We first look at a variation on rank functions called discrete Lipschitz functions. We relate the number of Lipschitz functions of a graph G to the number of rank functions

Rank Functions of Fuzzy Greedoids

by Steven J. Tedford , 2015
"... Fuzzy greedoids were recently introduced as a fuzzy set generalization of (crisp) greedoids. We characterize fuzzy languages which define fuzzy greedoids, give necessary properties and suffi-cient properties of the fuzzy rank function of a fuzzy greedoid, give a characterization of the rank function ..."
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Fuzzy greedoids were recently introduced as a fuzzy set generalization of (crisp) greedoids. We characterize fuzzy languages which define fuzzy greedoids, give necessary properties and suffi-cient properties of the fuzzy rank function of a fuzzy greedoid, give a characterization of the rank

Ranking functions, AGM style

by Wolfgang Spohn , 1999
"... Ranking functions, having their first appearance under the name „ordinale Konditionalfunktionen“ in my Habilitationsschrift submitted in 1983, had several precursors of which I was only incompletely aware, among them Shackle’s functions of potential surprise (see Shackle 1969), Rescher’s plausibilit ..."
Abstract - Cited by 5 (0 self) - Add to MetaCart
Ranking functions, having their first appearance under the name „ordinale Konditionalfunktionen“ in my Habilitationsschrift submitted in 1983, had several precursors of which I was only incompletely aware, among them Shackle’s functions of potential surprise (see Shackle 1969), Rescher’s

Ranking Functions for Linear-Constraint Loops

by Amir M. Ben-amram , 2013
"... Ranking functions are a tool successfully used in termination analysis, complexity analysis, and program parallelization. Among the different types of ranking functions and approaches to finding them, this talk will concentrate on functions that are found by linear programming techniques. The settin ..."
Abstract - Cited by 5 (0 self) - Add to MetaCart
Ranking functions are a tool successfully used in termination analysis, complexity analysis, and program parallelization. Among the different types of ranking functions and approaches to finding them, this talk will concentrate on functions that are found by linear programming techniques
Results 1 - 10 of 8,932