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NIPS
2008
15 years 8 months ago
Efficient Sampling for Gaussian Process Inference using Control Variables
Sampling functions in Gaussian process (GP) models is challenging because of the highly correlated posterior distribution. We describe an efficient Markov chain Monte Carlo algori...
Michalis Titsias, Neil D. Lawrence, Magnus Rattray
NIPS
2008
15 years 8 months ago
Differentiable Sparse Coding
Prior work has shown that features which appear to be biologically plausible as well as empirically useful can be found by sparse coding with a prior such as a laplacian (L1) that...
J. Andrew Bagnell, David M. Bradley
NIPS
2008
15 years 8 months ago
Particle Filter-based Policy Gradient in POMDPs
Our setting is a Partially Observable Markov Decision Process with continuous state, observation and action spaces. Decisions are based on a Particle Filter for estimating the bel...
Pierre-Arnaud Coquelin, Romain Deguest, Rém...
NETWORKING
2007
15 years 8 months ago
Optimization Models for the Radio Planning of Wireless Mesh Networks
In this paper we propose novel optimization models for the planning of Wireless Mesh Networks whose objective is to minimize the network installation cost, while providing full cov...
Edoardo Amaldi, Antonio Capone, Matteo Cesana, Fed...
NIPS
2007
15 years 8 months ago
Active Preference Learning with Discrete Choice Data
We propose an active learning algorithm that learns a continuous valuation model from discrete preferences. The algorithm automatically decides what items are best presented to an...
Eric Brochu, Nando de Freitas, Abhijeet Ghosh