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ACL
2008
15 years 1 months ago
Semi-Supervised Convex Training for Dependency Parsing
We present a novel semi-supervised training algorithm for learning dependency parsers. By combining a supervised large margin loss with an unsupervised least squares loss, a discr...
Qin Iris Wang, Dale Schuurmans, Dekang Lin
137
Voted
SIAMIS
2010
156views more  SIAMIS 2010»
14 years 7 months ago
Learning the Morphological Diversity
This article proposes a new method for image separation into a linear combination of morphological components. Sparsity in fixed dictionaries is used to extract the cartoon and osc...
Gabriel Peyré, Jalal Fadili, Jean-Luc Starc...
93
Voted
FUZZIEEE
2007
IEEE
15 years 6 months ago
Survey of Rough and Fuzzy Hybridization
— This paper provides a broad overview of logical and black box approaches to fuzzy and rough hybridization. The logical approaches include theoretical, supervised learning, feat...
Pawan Lingras, Richard Jensen
NIPS
2004
15 years 1 months ago
A Method for Inferring Label Sampling Mechanisms in Semi-Supervised Learning
We consider the situation in semi-supervised learning, where the "label sampling" mechanism stochastically depends on the true response (as well as potentially on the fe...
Saharon Rosset, Ji Zhu, Hui Zou, Trevor Hastie
113
Voted
AIM
1999
15 years 4 days ago
Machine Learning, Machine Vision, and the Brain
The problem of learning is arguably at the very core of the problem of intelligence, both biological and artificial. In this paper we review our work over the last ten years in th...
Tomaso Poggio, Christian R. Shelton