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MP
2010
162views more  MP 2010»
13 years 7 months ago
Approximation accuracy, gradient methods, and error bound for structured convex optimization
Convex optimization problems arising in applications, possibly as approximations of intractable problems, are often structured and large scale. When the data are noisy, it is of i...
Paul Tseng
PR
2010
186views more  PR 2010»
13 years 7 months ago
Feature extraction by learning Lorentzian metric tensor and its extensions
We develop a supervised dimensionality reduction method, called Lorentzian Discriminant Projection (LDP), for feature extraction and classification. Our method represents the str...
Risheng Liu, Zhouchen Lin, Zhixun Su, Kewei Tang
WWW
2008
ACM
14 years 9 months ago
Automatic web image selection with a probabilistic latent topic model
We propose a new method to select relevant images to the given keywords from images gathered from the Web based on the Probabilistic Latent Semantic Analysis (PLSA) model which is...
Keiji Yanai
ESEM
2008
ACM
13 years 10 months ago
A hybrid faulty module prediction using association rule mining and logistic regression analysis
This paper proposes a fault-prone module prediction method that combines association rule mining with logistic regression analysis. In the proposed method, we focus on three key m...
Yasutaka Kamei, Akito Monden, Shuuji Morisaki, Ken...
ICMCS
2006
IEEE
112views Multimedia» more  ICMCS 2006»
14 years 2 months ago
Visual Feature Space Analysis for Unsupervised Effectiveness Estimation and Feature Engineering
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...
Tobias Schreck, Daniel A. Keim, Christian Panse