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» Bayesian Inference for Sparse Generalized Linear Models
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UAI
2000
15 years 1 months ago
Variational Relevance Vector Machines
The Support Vector Machine (SVM) of Vapnik [9] has become widely established as one of the leading approaches to pattern recognition and machine learning. It expresses predictions...
Christopher M. Bishop, Michael E. Tipping
EMMCVPR
2011
Springer
13 years 11 months ago
Data-Driven Importance Distributions for Articulated Tracking
Abstract. We present two data-driven importance distributions for particle filterbased articulated tracking; one based on background subtraction, another on depth information. In ...
Søren Hauberg, Kim Steenstrup Pedersen
PAMI
2011
14 years 6 months ago
Greedy Learning of Binary Latent Trees
—Inferring latent structures from observations helps to model and possibly also understand underlying data generating processes. A rich class of latent structures are the latent ...
Stefan Harmeling, Christopher K. I. Williams
STOC
2001
ACM
151views Algorithms» more  STOC 2001»
15 years 12 months ago
On the cell probe complexity of membership and perfect hashing
We study two fundamental static data structure problems, membership and perfect hashing, in Yao's cell probe model. The first space and bit probe optimal worst case upper bou...
Rasmus Pagh
130
Voted
CSDA
2007
169views more  CSDA 2007»
14 years 11 months ago
A null space method for over-complete blind source separation
In blind source separation, there are M sources that produce sounds independently and continuously over time. These sounds are then recorded by m receivers. The sound recorded by ...
Ray-Bing Chen, Ying Nian Wu