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IJCAI
2001
15 years 3 months ago
Approximate inference for first-order probabilistic languages
A new, general approach is described for approximate inference in first-order probabilistic languages, using Markov chain Monte Carlo (MCMC) techniques in the space of concrete po...
Hanna Pasula, Stuart J. Russell
NIPS
2001
15 years 3 months ago
On the Generalization Ability of On-Line Learning Algorithms
In this paper, it is shown how to extract a hypothesis with small risk from the ensemble of hypotheses generated by an arbitrary on-line learning algorithm run on an independent an...
Nicolò Cesa-Bianchi, Alex Conconi, Claudio ...
IJCAI
2003
15 years 3 months ago
Statistics Gathering for Learning from Distributed, Heterogeneous and Autonomous Data Sources
With the growing use of distributed information networks, there is an increasing need for algorithmic and system solutions for data-driven knowledge acquisition using distributed,...
Doina Caragea, Jaime Reinoso, Adrian Silvescu, Vas...
AUTOMATICA
2007
179views more  AUTOMATICA 2007»
15 years 2 months ago
Approximate bisimulation relations for constrained linear systems
In this paper, we define the notion of approximate bisimulation relation between two continuous systems. While exact bisimulation requires that the observations of two systems ar...
Antoine Girard, George J. Pappas
CORR
2010
Springer
99views Education» more  CORR 2010»
15 years 2 months ago
Pure Type Systems without Explicit Contexts
We present an approach to type theory in which the typing judgments do not have explicit contexts. Instead of judgments of the shape A : B, our systems just have judgments of the ...
Herman Geuvers, Robbert Krebbers, James McKinna, F...