CVPR
2012
IEEE
11 years 7 months ago
2012
IEEE
In this paper, we propose a bilevel sparse coding model for coupled feature spaces, where we aim to learn dictionaries for sparse modeling in both spaces while enforcing some desi...
AAAI
2011
12 years 4 months ago
2011
A common approach in machine learning is to use a large amount of labeled data to train a model. Usually this model can then only be used to classify data in the same feature spac...
ICML
2010
IEEE
13 years 5 months ago
2010
IEEE
In a variety of applications, kernel machines such as Support Vector Machines (SVMs) have been used with great success often delivering stateof-the-art results. Using the kernel t...
ACL
2006
13 years 6 months ago
2006
Recent developments in statistical modeling of various linguistic phenomena have shown that additional features give consistent performance improvements. Quite often, improvements...
ACL
2008
13 years 6 months ago
2008
In this work, we develop and evaluate a wide range of feature spaces for deriving Levinstyle verb classifications (Levin, 1993). We perform the classification experiments using Ba...
NLPRS
2001
Springer
13 years 9 months ago
2001
Springer
We propose a new ensembling method of Support Vector Machines (SVMs) based on Feature Space Restructuring. In the proposed method, the weighted majority voting method is applied f...
CVPR
2010
IEEE
13 years 9 months ago
2010
IEEE
The design of feature spaces for local image descriptors is an important research subject in computer vision due to its applicability in several problems, such as visual classifi...
ICMCS
2006
IEEE
13 years 10 months ago
2006
IEEE
The Feature Vector approach is one of the most popular schemes for managing multimedia data. For many data types such as audio, images, or 3D models, an abundance of different Fea...