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ITSL
2008
13 years 8 months ago
An Empirical Comparison of NML Clustering Algorithms
Clustering can be defined as a data assignment problem where the goal is to partition the data into nonhierarchical groups of items. In our previous work, we suggested an informati...
Petri Kontkanen, Petri Myllymäki
SETN
2004
Springer
14 years 23 days ago
Incremental Mixture Learning for Clustering Discrete Data
Abstract. This paper elaborates on an efficient approach for clustering discrete data by incrementally building multinomial mixture models through likelihood maximization using the...
Konstantinos Blekas, Aristidis Likas
WWW
2009
ACM
14 years 8 months ago
An axiomatic approach for result diversification
Understanding user intent is key to designing an effective ranking system in a search engine. In the absence of any explicit knowledge of user intent, search engines want to diver...
Sreenivas Gollapudi, Aneesh Sharma
DAGM
2007
Springer
14 years 1 months ago
Clustered Stochastic Optimization for Object Recognition and Pose Estimation
We present an approach for estimating the 3D position and in case of articulated objects also the joint configuration from segmented 2D images. The pose estimation without initial...
Juergen Gall, Bodo Rosenhahn, Hans-Peter Seidel
PAMI
2008
270views more  PAMI 2008»
13 years 7 months ago
Randomized Clustering Forests for Image Classification
This paper introduces three new contributions to the problems of image classification and image search. First, we propose a new image patch quantization algorithm. Other competitiv...
Frank Moosmann, Eric Nowak, Frédéric...