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» Preference-based learning to rank
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85
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ECML
2007
Springer
15 years 6 months ago
A Simple Lexicographic Ranker and Probability Estimator
Given a binary classification task, a ranker sorts a set of instances from highest to lowest expectation that the instance is positive. We propose a lexicographic ranker, LexRank,...
Peter A. Flach, Edson Takashi Matsubara
108
Voted
SIGIR
2010
ACM
15 years 4 months ago
How good is a span of terms?: exploiting proximity to improve web retrieval
Ranking search results is a fundamental problem in information retrieval. In this paper we explore whether the use of proximity and phrase information can improve web retrieval ac...
Krysta Marie Svore, Pallika H. Kanani, Nazan Khan
PAMI
2012
13 years 2 months ago
CPMC: Automatic Object Segmentation Using Constrained Parametric Min-Cuts
—We present a novel framework to generate and rank plausible hypotheses for the spatial extent of objects in images using bottom-up computational processes and mid-level selectio...
João Carreira, Cristian Sminchisescu
96
Voted
ICML
2010
IEEE
15 years 1 months ago
On the Consistency of Ranking Algorithms
We present a theoretical analysis of supervised ranking, providing necessary and sufficient conditions for the asymptotic consistency of algorithms based on minimizing a surrogate...
John Duchi, Lester W. Mackey, Michael I. Jordan
CVPR
2012
IEEE
13 years 2 months ago
Steerable part models
We describe a method for learning steerable deformable part models. Our models exploit the fact that part templates can be written as linear filter banks. We demonstrate that one...
Hamed Pirsiavash, Deva Ramanan