Convergent Tree-Reweighted Message Passing for Energy Minimization
IEEE Transactions on Pattern Analysis and Machine Intelligence
Linear Programming Relaxations and Belief Propagation -- An Empirical Study
The Journal of Machine Learning Research
PatchMatch: a randomized correspondence algorithm for structural image editing
ACM SIGGRAPH 2009 papers
Dlib-ml: A Machine Learning Toolkit
The Journal of Machine Learning Research
Probabilistic Graphical Models: Principles and Techniques - Adaptive Computation and Machine Learning
FastInf: An Efficient Approximate Inference Library
The Journal of Machine Learning Research
The SHOGUN Machine Learning Toolbox
The Journal of Machine Learning Research
libDAI: A Free and Open Source C++ Library for Discrete Approximate Inference in Graphical Models
The Journal of Machine Learning Research
Multiscale conditional random fields for image labeling
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Waffles: A Machine Learning Toolkit
The Journal of Machine Learning Research
An alternating direction method for dual MAP LP relaxation
ECML PKDD'11 Proceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - Volume Part II
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
PATCHMATCHGRAPH: building a graph of dense patch correspondences for label transfer
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part V
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We present an open-source platform-independent C++ framework for machine learning and computer vision research. The framework includes a wide range of standard machine learning and graphical models algorithms as well as reference implementations for many machine learning and computer vision applications. The framework contains Matlab wrappers for core components of the library and an experimental graphical user interface for developing and visualizing machine learning data flows.