137 search results - page 4 / 28 » Sparse Semi-supervised Learning Using Conjugate Functions |
NIPS
1998
13 years 7 months ago
1998
We introduce a semi-supervised support vector machine (S3 VM) method. Given a training set of labeled data and a working set of unlabeled data, S3 VM constructs a support vector m...
COLING
2008
13 years 7 months ago
2008
This paper explores the use of the homotopy method for training a semi-supervised Hidden Markov Model (HMM) used for sequence labeling. We provide a novel polynomial-time algorith...
JMLR
2010
13 years 23 days ago
2010
In this paper, we propose a general framework for sparse semi-supervised learning, which concerns using a small portion of unlabeled data and a few labeled data to represent targe...
NIPS
2007
13 years 7 months ago
2007
We present a new and efficient semi-supervised training method for parameter estimation and feature selection in conditional random fields (CRFs). In real-world applications suc...
ICML
2006
IEEE
14 years 6 months ago
2006
IEEE
Semi-Supervised Support Vector Machines (S3 VMs) are an appealing method for using unlabeled data in classification: their objective function favors decision boundaries which do n...