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» A Bayesian Approach to Semi-Supervised Learning
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NAACL
2007
13 years 9 months ago
Data-Driven Graph Construction for Semi-Supervised Graph-Based Learning in NLP
Graph-based semi-supervised learning has recently emerged as a promising approach to data-sparse learning problems in natural language processing. All graph-based algorithms rely ...
Andrei Alexandrescu, Katrin Kirchhoff
JMLR
2010
119views more  JMLR 2010»
13 years 2 months ago
Semi-Supervised Learning via Generalized Maximum Entropy
Various supervised inference methods can be analyzed as convex duals of the generalized maximum entropy (MaxEnt) framework. Generalized MaxEnt aims to find a distribution that max...
Ayse Erkan, Yasemin Altun
ICML
2010
IEEE
13 years 8 months ago
High-Performance Semi-Supervised Learning using Discriminatively Constrained Generative Models
We develop a semi-supervised learning method that constrains the posterior distribution of latent variables under a generative model to satisfy a rich set of feature expectation c...
Gregory Druck, Andrew McCallum
EMNLP
2009
13 years 5 months ago
Semi-Supervised Learning for Semantic Relation Classification using Stratified Sampling Strategy
This paper presents a new approach to selecting the initial seed set using stratified sampling strategy in bootstrapping-based semi-supervised learning for semantic relation class...
Longhua Qian, Guodong Zhou, Fang Kong, Qiaoming Zh...
ACL
2009
13 years 5 months ago
A Graph-based Semi-Supervised Learning for Question-Answering
We present a graph-based semi-supervised learning for the question-answering (QA) task for ranking candidate sentences. Using textual entailment analysis, we obtain entailment sco...
Asli Çelikyilmaz, Marcus Thint, Zhiheng Hua...