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AAAI
2010
13 years 10 months ago
Efficient Lifting for Online Probabilistic Inference
Lifting can greatly reduce the cost of inference on firstorder probabilistic graphical models, but constructing the lifted network can itself be quite costly. In online applicatio...
Aniruddh Nath, Pedro Domingos
SDM
2010
SIAM
226views Data Mining» more  SDM 2010»
13 years 10 months ago
Two-View Transductive Support Vector Machines
Obtaining high-quality and up-to-date labeled data can be difficult in many real-world machine learning applications, especially for Internet classification tasks like review spam...
Guangxia Li, Steven C. H. Hoi, Kuiyu Chang
NIPS
2004
13 years 10 months ago
Bayesian inference in spiking neurons
We propose a new interpretation of spiking neurons as Bayesian integrators accumulating evidence over time about events in the external world or the body, and communicating to oth...
Sophie Deneve
VMV
2001
131views Visualization» more  VMV 2001»
13 years 10 months ago
Shape Model and Threshold Extraction via Shape Gradients
Shape information is utilized by numerous applications in computer vision, scientific visualization and computer graphics. This paper presents a novel algorithm for exploring and ...
Roger C. Tam, Alain Fournier
USITS
2003
13 years 10 months ago
Using Random Subsets to Build Scalable Network Services
In this paper, we argue that a broad range of large-scale network services would benefit from a scalable mechanism for delivering state about a random subset of global participan...
Dejan Kostic, Adolfo Rodriguez, Jeannie R. Albrech...