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KDD
2006
ACM
165views Data Mining» more  KDD 2006»
16 years 3 months ago
Training linear SVMs in linear time
Linear Support Vector Machines (SVMs) have become one of the most prominent machine learning techniques for highdimensional sparse data commonly encountered in applications like t...
Thorsten Joachims
115
Voted
CHI
2008
ACM
16 years 3 months ago
K-sketch: a 'kinetic' sketch pad for novice animators
Because most animation tools are complex and timeconsuming to learn and use, most animations today are created by experts. To help novices create a wide range of animations quickl...
Richard C. Davis, Brien Colwell, James A. Landay
CVPR
2010
IEEE
15 years 10 months ago
Face Recognition with Learning-based Descriptor
We present a novel approach to address the representation issue and the matching issue in face recognition (verification). Firstly, our approach encodes the micro-structures of t...
Zhimin Cao, Qi Yin, Jian Sun, Xiaoou Tang
132
Voted
ACML
2009
Springer
15 years 9 months ago
Robust Discriminant Analysis Based on Nonparametric Maximum Entropy
In this paper, we propose a Robust Discriminant Analysis based on maximum entropy (MaxEnt) criterion (MaxEnt-RDA), which is derived from a nonparametric estimate of Renyi’s quadr...
Ran He, Bao-Gang Hu, Xiaotong Yuan
127
Voted
ICPR
2008
IEEE
15 years 9 months ago
Semi-supervised marginal discriminant analysis based on QR decomposition
In this paper, a novel subspace learning method, semi-supervised marginal discriminant analysis (SMDA), is proposed for classification. SMDA aims at maintaining the intrinsic neig...
Rui Xiao, Pengfei Shi