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» Hierarchical Morphable Models
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110
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NIPS
2003
15 years 4 months ago
Learning the k in k-means
When clustering a dataset, the right number k of clusters to use is often not obvious, and choosing k automatically is a hard algorithmic problem. In this paper we present an impr...
Greg Hamerly, Charles Elkan
171
Voted
NETWORKING
2000
15 years 4 months ago
An Exact Algorithm for Calculating Blocking Probabilities in Multicast Networks
Abstract. The paper deals with tree-structured point-to-multipoint networks, where users from infinite user populations at the leaf nodes subscribe to a variety of channels, offere...
Eeva Nyberg, Jorma T. Virtamo, Samuli Aalto
ICASSP
2010
IEEE
15 years 3 months ago
Swift: Scalable weighted iterative sampling for flow cytometry clustering
Flow cytometry (FC) is a powerful technology for rapid multivariate analysis and functional discrimination of cells. Current FC platforms generate large, high-dimensional datasets...
Iftekhar Naim, Suprakash Datta, Gaurav Sharma, Jam...
ML
2006
ACM
121views Machine Learning» more  ML 2006»
15 years 3 months ago
Model-based transductive learning of the kernel matrix
This paper addresses the problem of transductive learning of the kernel matrix from a probabilistic perspective. We define the kernel matrix as a Wishart process prior and construc...
Zhihua Zhang, James T. Kwok, Dit-Yan Yeung
MVA
2006
205views Computer Vision» more  MVA 2006»
15 years 3 months ago
Ontological inference for image and video analysis
Abstract This paper presents an approach to designing and implementing extensible computational models for perceiving systems based on a knowledge-driven joint inference approach. ...
Christopher Town