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SDM
2004
SIAM
214views Data Mining» more  SDM 2004»
15 years 5 months ago
Making Time-Series Classification More Accurate Using Learned Constraints
It has long been known that Dynamic Time Warping (DTW) is superior to Euclidean distance for classification and clustering of time series. However, until lately, most research has...
Chotirat (Ann) Ratanamahatana, Eamonn J. Keogh
PAMI
2007
217views more  PAMI 2007»
15 years 3 months ago
Discriminative Learning and Recognition of Image Set Classes Using Canonical Correlations
—We address the problem of comparing sets of images for object recognition, where the sets may represent variations in an object’s appearance due to changing camera pose and li...
Tae-Kyun Kim, Josef Kittler, Roberto Cipolla
IEEEVAST
2010
14 years 11 months ago
A visual analytics approach to model learning
The process of learning models from raw data typically requires a substantial amount of user input during the model initialization phase. We present an assistive visualization sys...
Supriya Garg, I. V. Ramakrishnan, Klaus Mueller
ICCV
2003
IEEE
16 years 6 months ago
A Sparse Probabilistic Learning Algorithm for Real-Time Tracking
This paper addresses the problem of applying powerful pattern recognition algorithms based on kernels to efficient visual tracking. Recently Avidan [1] has shown that object recog...
Oliver M. C. Williams, Andrew Blake, Roberto Cipol...
FSKD
2007
Springer
98views Fuzzy Logic» more  FSKD 2007»
15 years 10 months ago
Learning Selective Averaged One-Dependence Estimators for Probability Estimation
Naïve Bayes is a well-known effective and efficient classification algorithm, but its probability estimation performance is poor. Averaged One-Dependence Estimators, simply AODE,...
Qing Wang, Chuan-hua Zhou, Jiankui Guo