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» Modeling Classification and Inference Learning
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117
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ICML
2008
IEEE
16 years 3 months ago
Multi-task compressive sensing with Dirichlet process priors
Compressive sensing (CS) is an emerging field that, under appropriate conditions, can significantly reduce the number of measurements required for a given signal. In many applicat...
Yuting Qi, Dehong Liu, David B. Dunson, Lawrence C...
ICRA
2009
IEEE
147views Robotics» more  ICRA 2009»
15 years 9 months ago
Equipping robot control programs with first-order probabilistic reasoning capabilities
— An autonomous robot system that is to act in a real-world environment is faced with the problem of having to deal with a high degree of both complexity as well as uncertainty. ...
Dominik Jain, Lorenz Mösenlechner, Michael Be...
131
Voted
ICML
2005
IEEE
16 years 3 months ago
Bayesian hierarchical clustering
We present a novel algorithm for agglomerative hierarchical clustering based on evaluating marginal likelihoods of a probabilistic model. This algorithm has several advantages ove...
Katherine A. Heller, Zoubin Ghahramani
ICML
2010
IEEE
15 years 3 months ago
Asymptotic Analysis of Generative Semi-Supervised Learning
Semi-supervised learning has emerged as a popular framework for improving modeling accuracy while controlling labeling cost. Based on an extension of stochastic composite likeliho...
Joshua Dillon, Krishnakumar Balasubramanian, Guy L...
SAGA
2001
Springer
15 years 6 months ago
Stochastic Finite Learning
Inductive inference can be considered as one of the fundamental paradigms of algorithmic learning theory. We survey results recently obtained and show their impact to potential ap...
Thomas Zeugmann