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JMLR
2010
192views more  JMLR 2010»
14 years 8 months ago
Efficient Learning of Deep Boltzmann Machines
We present a new approximate inference algorithm for Deep Boltzmann Machines (DBM's), a generative model with many layers of hidden variables. The algorithm learns a separate...
Ruslan Salakhutdinov, Hugo Larochelle
ECCV
2006
Springer
16 years 3 months ago
PoseCut: Simultaneous Segmentation and 3D Pose Estimation of Humans Using Dynamic Graph-Cuts
Abstract. We present a novel algorithm for performing integrated segmentation and 3D pose estimation of a human body from multiple views. Unlike other related state of the art tech...
Matthieu Bray, Pushmeet Kohli, Philip H. S. Torr
BIODATAMINING
2008
96views more  BIODATAMINING 2008»
15 years 2 months ago
Fast approximate hierarchical clustering using similarity heuristics
Background: Agglomerative hierarchical clustering (AHC) is a common unsupervised data analysis technique used in several biological applications. Standard AHC methods require that...
Meelis Kull, Jaak Vilo
ICCV
2003
IEEE
16 years 3 months ago
Object Recognition with Informative Features and Linear Classification
In this paper we show that efficient object recognition can be obtained by combining informative features with linear classification. The results demonstrate the superiority of in...
Michel Vidal-Naquet, Shimon Ullman
NIPS
2000
15 years 3 months ago
Learning Winner-take-all Competition Between Groups of Neurons in Lateral Inhibitory Networks
It has long been known that lateral inhibition in neural networks can lead to a winner-take-all competition, so that only a single neuron is active at a steady state. Here we show...
Xiaohui Xie, Richard H. R. Hahnloser, H. Sebastian...