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JMLR
2010
121views more  JMLR 2010»
13 years 2 months ago
Efficient Collapsed Gibbs Sampling for Latent Dirichlet Allocation
Collapsed Gibbs sampling is a frequently applied method to approximate intractable integrals in probabilistic generative models such as latent Dirichlet allocation. This sampling ...
Han Xiao, Thomas Stibor
ICASSP
2011
IEEE
12 years 11 months ago
Causal signal recovery from U-invariant samples
Causal processing of a signal’s samples is crucial in on-line applications such as audio rate conversion, compression, tracking and more. This paper addresses the problem of cau...
Tomer Michaeli, Yonina C. Eldar, Volker Pohl
SDM
2012
SIAM
235views Data Mining» more  SDM 2012»
11 years 10 months ago
Sampling Strategies to Evaluate the Performance of Unknown Predictors
The focus of this paper is on how to select a small sample of examples for labeling that can help us to evaluate many different classification models unknown at the time of sampl...
Hamed Valizadegan, Saeed Amizadeh, Milos Hauskrech...
ICML
2004
IEEE
14 years 8 months ago
Learning and evaluating classifiers under sample selection bias
Classifier learning methods commonly assume that the training data consist of randomly drawn examples from the same distribution as the test examples about which the learned model...
Bianca Zadrozny
FOCS
2007
IEEE
13 years 11 months ago
Inferring Local Homology from Sampled Stratified Spaces
We study the reconstruction of a stratified space from a possibly noisy point sample. Specifically, we use the vineyard of the distance function restricted to a 1-parameter family...
Paul Bendich, David Cohen-Steiner, Herbert Edelsbr...