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» Alignment using Spectral Clusters
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152
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DAGM
2011
Springer
14 years 28 days ago
Relaxed Exponential Kernels for Unsupervised Learning
Many unsupervised learning algorithms make use of kernels that rely on the Euclidean distance between two samples. However, the Euclidean distance is optimal for Gaussian distribut...
Karim T. Abou-Moustafa, Mohak Shah, Fernando De la...
113
Voted
CVPR
2008
IEEE
16 years 3 months ago
Generalised blurring mean-shift algorithms for nonparametric clustering
Gaussian blurring mean-shift (GBMS) is a nonparametric clustering algorithm, having a single bandwidth parameter that controls the number of clusters. The algorithm iteratively sh...
Miguel Á. Carreira-Perpiñán
109
Voted
DCC
2005
IEEE
16 years 21 days ago
Efficient Inter-Band Prediction and Wavelet Based Compression for Hyperspectral Imagery: A Distributed Source Coding Approach
Hyperspectral images have correlation at the level of pixels; moreover, images from neighboring frequency bands are also closely correlated. In this paper, we propose to use distr...
Caimu Tang, Ngai-Man Cheung, Antonio Ortega, Cauli...
87
Voted
UAI
2008
15 years 2 months ago
Learning and Solving Many-Player Games through a Cluster-Based Representation
In addressing the challenge of exponential scaling with the number of agents we adopt a cluster-based representation to approximately solve asymmetric games of very many players. ...
Sevan G. Ficici, David C. Parkes, Avi Pfeffer
122
Voted
MM
2005
ACM
146views Multimedia» more  MM 2005»
15 years 6 months ago
Unsupervised content discovery in composite audio
Automatically extracting semantic content from audio streams can be helpful in many multimedia applications. Motivated by the known limitations of traditional supervised approache...
Rui Cai, Lie Lu, Alan Hanjalic