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» Magnitude-preserving ranking algorithms
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CVPR
2007
IEEE
16 years 8 months ago
Autocalibration via Rank-Constrained Estimation of the Absolute Quadric
We present an autocalibration algorithm for upgrading a projective reconstruction to a metric reconstruction by estimating the absolute dual quadric. The algorithm enforces the ra...
Manmohan Krishna Chandraker, Sameer Agarwal, Fredr...
ICML
2010
IEEE
15 years 4 months ago
Learning optimally diverse rankings over large document collections
Most learning to rank research has assumed that the utility of different documents is independent, which results in learned ranking functions that return redundant results. The fe...
Aleksandrs Slivkins, Filip Radlinski, Sreenivas Go...
CORR
2011
Springer
157views Education» more  CORR 2011»
14 years 9 months ago
Large-Scale Convex Minimization with a Low-Rank Constraint
We address the problem of minimizing a convex function over the space of large matrices with low rank. While this optimization problem is hard in general, we propose an efficient...
Shai Shalev-Shwartz, Alon Gonen, Ohad Shamir
WWW
2007
ACM
16 years 6 months ago
Comparing apples and oranges: normalized pagerank for evolving graphs
PageRank is the best known technique for link-based importance ranking. The computed importance scores, however, are not directly comparable across different snapshots of an evolv...
Klaus Berberich, Srikanta J. Bedathur, Gerhard Wei...
ICML
2007
IEEE
16 years 6 months ago
Solving multiclass support vector machines with LaRank
Optimization algorithms for large margin multiclass recognizers are often too costly to handle ambitious problems with structured outputs and exponential numbers of classes. Optim...
Antoine Bordes, Jason Weston, Léon Bottou, ...