Sciweavers

CIKM
2009
Springer
13 years 8 months ago
Improving binary classification on text problems using differential word features
We describe an efficient technique to weigh word-based features in binary classification tasks and show that it significantly improves classification accuracy on a range of proble...
Justin Martineau, Tim Finin, Anupam Joshi, Shamit ...
ACML
2009
Springer
13 years 8 months ago
Max-margin Multiple-Instance Learning via Semidefinite Programming
In this paper, we present a novel semidefinite programming approach for multiple-instance learning. We first formulate the multipleinstance learning as a combinatorial maximum marg...
Yuhong Guo
IJCNN
2000
IEEE
13 years 9 months ago
Support Vector Machine for Regression and Applications to Financial Forecasting
The main purpose of this paper is to compare the support vector machine (SVM) developed by Vapnik with other techniques such as Backpropagation and Radial Basis Function (RBF) Net...
Theodore B. Trafalis, Huseyin Ince
ICANN
2001
Springer
13 years 9 months ago
The Bayesian Committee Support Vector Machine
Empirical evidence indicates that the training time for the support vector machine (SVM) scales to the square of the number of training data points. In this paper, we introduce the...
Anton Schwaighofer, Volker Tresp
ICANN
2001
Springer
13 years 9 months ago
Fast Training of Support Vector Machines by Extracting Boundary Data
Support vector machines have gotten wide acceptance for their high generalization ability for real world applications. But the major drawback is slow training for classification p...
Shigeo Abe, Takuya Inoue
ICANN
2009
Springer
13 years 9 months ago
Learning SVMs from Sloppily Labeled Data
This paper proposes a modelling of Support Vector Machine (SVM) learning to address the problem of learning with sloppy labels. In binary classification, learning with sloppy labe...
Guillaume Stempfel, Liva Ralaivola
ICDM
2002
IEEE
133views Data Mining» more  ICDM 2002»
13 years 9 months ago
Learning with Progressive Transductive Support Vector Machine
Support vector machine (SVM) is a new learning method developed in recent years based on the foundations of statistical learning theory. By taking a transductive approach instead ...
Yisong Chen, Guoping Wang, Shihai Dong
ICMI
2003
Springer
184views Biometrics» more  ICMI 2003»
13 years 10 months ago
Real time facial expression recognition in video using support vector machines
Enabling computer systems to recognize facial expressions and infer emotions from them in real time presents a challenging research topic. In this paper, we present a real time ap...
Philipp Michel, Rana El Kaliouby
MM
2003
ACM
111views Multimedia» more  MM 2003»
13 years 10 months ago
A robust dissolve detector by support vector machine
In this paper, we propose a novel approach for the robust detection and classification of dissolve sequences in videos. Our approach is based on the multi-resolution representati...
Chong-Wah Ngo
AMFG
2003
IEEE
157views Biometrics» more  AMFG 2003»
13 years 10 months ago
Inference of Human Postures by Classification of 3D Human Body Shape
In this paper we describe an approach for inferring the body posture using a 3D visual-hull constructed from a set of silhouettes. We introduce an appearance-based, view-independe...
Isaac Cohen, Hongxia Li