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ICML
2004
IEEE
16 years 4 months ago
Support vector machine learning for interdependent and structured output spaces
Learning general functional dependencies is one of the main goals in machine learning. Recent progress in kernel-based methods has focused on designing flexible and powerful input...
Ioannis Tsochantaridis, Thomas Hofmann, Thorsten J...
142
Voted
ICML
2010
IEEE
15 years 4 months ago
Label Ranking under Ambiguous Supervision for Learning Semantic Correspondences
This paper studies the problem of learning from ambiguous supervision, focusing on the task of learning semantic correspondences. A learning problem is said to be ambiguously supe...
Antoine Bordes, Nicolas Usunier, Jason Weston
ML
2011
ACM
179views Machine Learning» more  ML 2011»
14 years 10 months ago
Neural networks for relational learning: an experimental comparison
In the last decade, connectionist models have been proposed that can process structured information directly. These methods, which are based on the use of graphs for the representa...
Werner Uwents, Gabriele Monfardini, Hendrik Blocke...
JMLR
2010
82views more  JMLR 2010»
14 years 10 months ago
On Spectral Learning
In this paper, we study the problem of learning a matrix W from a set of linear measurements. Our formulation consists in solving an optimization problem which involves regulariza...
Andreas Argyriou, Charles A. Micchelli, Massimilia...
122
Voted
ETS
2006
IEEE
119views Hardware» more  ETS 2006»
15 years 3 months ago
An Ontology-Based Framework for Bridging Learning Design and Learning Content
The paper describes an ontology-based framework for bridging learning design and learning object content. In present solutions, researchers have proposed conceptual models and dev...
Colin Knight, Dragan Gasevic, Griff Richards