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ICML
2010
IEEE
13 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
DCC
2006
IEEE
14 years 7 months ago
The B-coder: An Improved Binary Arithmetic Coder and Probability Estimator
In this paper we present the B-coder, an efficient binary arithmetic coder that performs extremely well on a wide range of data. The B-coder should be classed as an `approximate&#...
Benjamin Kelly, David F. Brailsford
ML
2012
ACM
413views Machine Learning» more  ML 2012»
12 years 3 months ago
Gradient-based boosting for statistical relational learning: The relational dependency network case
Dependency networks approximate a joint probability distribution over multiple random variables as a product of conditional distributions. Relational Dependency Networks (RDNs) are...
Sriraam Natarajan, Tushar Khot, Kristian Kersting,...
JMLR
2008
135views more  JMLR 2008»
13 years 7 months ago
Complete Identification Methods for the Causal Hierarchy
We consider a hierarchy of queries about causal relationships in graphical models, where each level in the hierarchy requires more detailed information than the one below. The hie...
Ilya Shpitser, Judea Pearl
SIGGRAPH
1999
ACM
13 years 12 months ago
Real-Time Acoustic Modeling for Distributed Virtual Environments
Realistic acoustic modeling is essential for spatializing sound in distributed virtual environments where multiple networked users move around and interact visually and aurally in...
Thomas A. Funkhouser, Patrick Min, Ingrid Carlbom