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ML
2008
ACM
15 years 2 months ago
Structured machine learning: the next ten years
Thomas G. Dietterich, Pedro Domingos, Lise Getoor,...
110
Voted
ICML
2009
IEEE
16 years 3 months ago
The adaptive k-meteorologists problem and its application to structure learning and feature selection in reinforcement learning
The purpose of this paper is three-fold. First, we formalize and study a problem of learning probabilistic concepts in the recently proposed KWIK framework. We give details of an ...
Carlos Diuk, Lihong Li, Bethany R. Leffler
113
Voted
ECML
2007
Springer
15 years 8 months ago
On Phase Transitions in Learning Sparse Networks
In this paper we study the identification of sparse interaction networks as a machine learning problem. Sparsity means that we are provided with a small data set and a high number...
Goele Hollanders, Geert Jan Bex, Marc Gyssens, Ron...
CVPR
2010
IEEE
15 years 10 months ago
Hierarchical Convolutional Sparse Image Decomposition
Building robust low and mid-level image representations, beyond edge primitives, is a long-standing goal in vision. Many existing feature detectors spatially pool edge information...
Matthew Zeiler, Dilip Krishnan, Graham Taylor, Rob...
120
Voted
CVPR
2010
IEEE
15 years 2 months ago
Deconvolutional networks
Building robust low and mid-level image representations, beyond edge primitives, is a long-standing goal in vision. Many existing feature detectors spatially pool edge information...
Matthew D. Zeiler, Dilip Krishnan, Graham W. Taylo...