52 search results - page 3 / 11 » Partially labeled classification with Markov random walks |
NIPS
2007
13 years 8 months ago
2007
A semi-supervised multitask learning (MTL) framework is presented, in which M parameterized semi-supervised classifiers, each associated with one of M partially labeled data mani...
MIR
2005
ACM
14 years 1 months ago
2005
ACM
In this paper, we propose a transductive learning method for content-based image retrieval: Multiple Random Walk (MRW). Its basic idea is to construct two generative models by mea...
ICPR
2006
IEEE
14 years 8 months ago
2006
IEEE
This paper integrates Markov random fields (MRFs) with type-2 fuzzy sets (T2 FSs) referred to as T2 FMRFs, which can handle the fuzziness of the labeling space as well as the rand...
ASUNAM
2010
IEEE
13 years 9 months ago
2010
IEEE
The goal of semi-supervised learning (SSL) methods is to reduce the amount of labeled training data required by learning from both labeled and unlabeled instances. Macskassy and Pr...
NIPS
2004
13 years 8 months ago
2004
We consider the problem of structured classification, where the task is to predict a label y from an input x, and y has meaningful internal structure. Our framework includes super...