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GFKL
2007
Springer
202views Data Mining» more  GFKL 2007»
13 years 11 months ago
Collective Classification for Labeling of Places and Objects in 2D and 3D Range Data
In this paper, we present an algorithm to identify types of places and objects from 2D and 3D laser range data obtained in indoor environments. Our approach is a combination of a c...
Rudolph Triebel, Óscar Martínez Mozo...
AI
2008
Springer
13 years 8 months ago
Label ranking by learning pairwise preferences
Preference learning is a challenging problem that involves the prediction of complex structures, such as weak or partial order relations, rather than single values. In the recent ...
Eyke Hüllermeier, Johannes Fürnkranz, We...
CVPR
2012
IEEE
11 years 10 months ago
Structured Local Predictors for image labelling
In this paper we introduce Structured Local Predictors (SLP) – A new formulation that considers the image labelling problem from a structured learning point of view. SLP are loc...
Samuel Rota Bulò, Peter Kontschieder, Marce...
SIGIR
2012
ACM
11 years 10 months ago
Top-k learning to rank: labeling, ranking and evaluation
In this paper, we propose a novel top-k learning to rank framework, which involves labeling strategy, ranking model and evaluation measure. The motivation comes from the difficul...
Shuzi Niu, Jiafeng Guo, Yanyan Lan, Xueqi Cheng
ACL
2009
13 years 5 months ago
Distant supervision for relation extraction without labeled data
Modern models of relation extraction for tasks like ACE are based on supervised learning of relations from small hand-labeled corpora. We investigate an alternative paradigm that ...
Mike Mintz, Steven Bills, Rion Snow, Daniel Jurafs...