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» Spectral clustering based on matrix perturbation theory
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ICASSP
2010
IEEE
13 years 6 months ago
Adaptive beam tracking for interference alignment for multiuser time-varying MIMO interference channels
The problem of interference alignment in time-varying MIMO interference channels is considered. To reduce complexity, an adaptive algorithm for beam vector design is proposed base...
Heejung Yu, Youngchul Sung, Haksoo Kim, Yong Hoon ...
KDD
2005
ACM
165views Data Mining» more  KDD 2005»
14 years 7 months ago
Co-clustering by block value decomposition
Dyadic data matrices, such as co-occurrence matrix, rating matrix, and proximity matrix, arise frequently in various important applications. A fundamental problem in dyadic data a...
Bo Long, Zhongfei (Mark) Zhang, Philip S. Yu
ICRA
2009
IEEE
137views Robotics» more  ICRA 2009»
14 years 2 months ago
Unsupervised learning of 3D object models from partial views
— We present an algorithm for learning 3D object models from partial object observations. The input to our algorithm is a sequence of 3D laser range scans. Models learned from th...
Michael Ruhnke, Bastian Steder, Giorgio Grisetti, ...
ICML
2003
IEEE
14 years 8 months ago
Semi-Supervised Learning Using Gaussian Fields and Harmonic Functions
An approach to semi-supervised learning is proposed that is based on a Gaussian random field model. Labeled and unlabeled data are represented as vertices in a weighted graph, wit...
Xiaojin Zhu, Zoubin Ghahramani, John D. Lafferty
CVPR
2008
IEEE
14 years 9 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