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DAGSTUHL
2007
13 years 9 months ago
An Axiomatic Approach to Personalized Ranking Systems
Personalized ranking systems and trust systems are an essential tool for collaboration in a multi-agent environment. In these systems, trust relations between many agents are aggr...
Alon Altman, Moshe Tennenholtz
ECCC
2006
109views more  ECCC 2006»
13 years 7 months ago
How to rank with few errors: A PTAS for Weighted Feedback Arc Set on Tournaments
Suppose you ran a chess tournament, everybody played everybody, and you wanted to use the results to rank everybody. Unless you were really lucky, the results would not be acyclic...
Claire Kenyon-Mathieu, Warren Schudy
IR
2010
13 years 6 months ago
Learning to rank with (a lot of) word features
In this article we present Supervised Semantic Indexing (SSI) which defines a class of nonlinear (quadratic) models that are discriminatively trained to directly map from the word...
Bing Bai, Jason Weston, David Grangier, Ronan Coll...
ICCV
2003
IEEE
14 years 9 months ago
Feature Selection for Unsupervised and Supervised Inference: the Emergence of Sparsity in a Weighted-based Approach
The problem of selecting a subset of relevant features in a potentially overwhelming quantity of data is classic and found in many branches of science. Examples in computer vision...
Lior Wolf, Amnon Shashua
STOC
2007
ACM
181views Algorithms» more  STOC 2007»
14 years 8 months ago
How to rank with few errors
We present a polynomial time approximation scheme (PTAS) for the minimum feedback arc set problem on tournaments. A simple weighted generalization gives a PTAS for KemenyYoung ran...
Claire Kenyon-Mathieu, Warren Schudy