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» Bayesian Parameter Estimation: A Monte Carlo Approach
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NIPS
2000
13 years 7 months ago
Learning Continuous Distributions: Simulations With Field Theoretic Priors
Learning of a smooth but nonparametric probability density can be regularized using methods of Quantum Field Theory. We implement a field theoretic prior numerically, test its eff...
Ilya Nemenman, William Bialek
CORR
2010
Springer
210views Education» more  CORR 2010»
13 years 6 months ago
Exploiting Statistical Dependencies in Sparse Representations for Signal Recovery
Signal modeling lies at the core of numerous signal and image processing applications. A recent approach that has drawn considerable attention is sparse representation modeling, in...
Tomer Faktor, Yonina C. Eldar, Michael Elad
TSP
2010
13 years 1 months ago
Variance-component based sparse signal reconstruction and model selection
We propose a variance-component probabilistic model for sparse signal reconstruction and model selection. The measurements follow an underdetermined linear model, where the unknown...
Kun Qiu, Aleksandar Dogandzic
ICRA
2008
IEEE
144views Robotics» more  ICRA 2008»
14 years 25 days ago
Interacting multiple model monocular SLAM
— Recent work has demonstrated the benefits of adopting a fully probabilistic SLAM approach in sequential motion and structure estimation from an image sequence. Unlike standard...
Javier Civera, Andrew J. Davison, J. M. M. Montiel
WWW
2010
ACM
14 years 1 months ago
Factorizing personalized Markov chains for next-basket recommendation
Recommender systems are an important component of many websites. Two of the most popular approaches are based on matrix factorization (MF) and Markov chains (MC). MF methods learn...
Steffen Rendle, Christoph Freudenthaler, Lars Schm...