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» Learning Gaussian Process Models from Uncertain Data
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WSC
2007
15 years 4 months ago
Simulating air traffic blockage due to convective weather conditions
A Monte Carlo methodology is proposed for simulating air traffic blockage patterns under the impact of convective weather. The simulation utilizes probabilistic convective weather...
Liling Ren, Dawei Chang, Senay Solak, John-Paul Cl...
AAAI
2012
13 years 4 months ago
A Search Algorithm for Latent Variable Models with Unbounded Domains
This paper concerns learning and prediction with probabilistic models where the domain sizes of latent variables have no a priori upper-bound. Current approaches represent prior d...
Michael Chiang, David Poole
120
Voted
MMSEC
2004
ACM
137views Multimedia» more  MMSEC 2004»
15 years 8 months ago
Perturbed quantization steganography with wet paper codes
In this paper, we introduce a new approach to passive-warden steganography in which the sender embeds the secret message into a certain subset of the cover object without having t...
Jessica J. Fridrich, Miroslav Goljan, David Soukal
ICASSP
2010
IEEE
15 years 2 months ago
A union of incoherent spaces model for classification
We present a new and computationally efficient scheme for classifying signals into a fixed number of known classes. We model classes as subspaces in which the corresponding data...
Karin Schnass, Pierre Vandergheynst
ICML
2007
IEEE
16 years 3 months ago
Conditional random fields for multi-agent reinforcement learning
Conditional random fields (CRFs) are graphical models for modeling the probability of labels given the observations. They have traditionally been trained with using a set of obser...
Xinhua Zhang, Douglas Aberdeen, S. V. N. Vishwanat...