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194
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UAI
1997
15 years 8 months ago
A Bayesian Approach to Learning Bayesian Networks with Local Structure
Recently several researchers have investigated techniques for using data to learn Bayesian networks containing compact representations for the conditional probability distribution...
David Maxwell Chickering, David Heckerman, Christo...
183
Voted
ICML
2010
IEEE
15 years 8 months ago
Restricted Boltzmann Machines are Hard to Approximately Evaluate or Simulate
Restricted Boltzmann Machines (RBMs) are a type of probability model over the Boolean cube {-1, 1}n that have recently received much attention. We establish the intractability of ...
Philip M. Long, Rocco A. Servedio
152
Voted
CORR
2010
Springer
95views Education» more  CORR 2010»
15 years 7 months ago
Statistical Compressive Sensing of Gaussian Mixture Models
A new framework of compressive sensing (CS), namely statistical compressive sensing (SCS), that aims at efficiently sampling a collection of signals that follow a statistical dist...
Guoshen Yu, Guillermo Sapiro
TSP
2008
74views more  TSP 2008»
15 years 6 months ago
Theoretical Performance Analysis of the W-ABORT Detector
In a recent paper we introduced a modification of the adaptive beamformer orthogonal rejection test (ABORT) for adaptive detection of signals in unknown noise, by supposing under t...
Francesco Bandiera, Olivier Besson, Danilo Orlando...
WSC
1997
15 years 8 months ago
Long-Lasting Transient Conditions in Simulations with Heavy-Tailed Workloads
Recent evidence suggests that some characteristics of computer and telecommunications systems may be well described using heavy tailed distributions — distributions whose tail d...
Mark Crovella, Lester Lipsky