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We integrated the work of the following people:
Alex J. Smola
- the pr_loqo optimizer
Antoine Bordes
- LaRank
Thorsten Joachims
- SVMLight
Chih-Chung Chang and and Chih-Jen Lin
- LibSVM
Xiang-Rui Wang and Chih-Jen Lin
- LIBLINEAR
Thomas Serafini, Luca Zanni, Gaetano Zanghirati
- the Gradient Projection Decomposition Technique (GPDT) - SVM
Vikas Sindhwani
- SVM-lin: Fast SVM Solvers for Supervised and Semi-supervised Learning
Vojtech Franc
- Generalized Nearest Point Problem Solver based L2 (slacks) SVM
- Optimized Cutting Plane Support Vector Machines (Ocas)
Jean-Philippe Vert and Hiroto Saigo
- Local Alignment Kernel
Leon Bottou
- Stochastic Gradient Descent (SGD) SVM
Marius Kloft
- 2-norm and q-norm MKL
- SMO based true Multi-Class SVM
Alexander Zien
- Newton based q-norm MKL
- POIM code for WD kernels
Christian Gehl
- Distance Metrics
Christian Widmer
- Dual and Multitask Learning
- Serialization support
Jonas Behr
- Structured Learning
Elpmis Lee
- Translation of the documentation to Chinese
Baozeng Ding
- Support for modular java, c#, ruby, lua interfaces
Shashwat Lal Das
- Streaming / Online Feature Framework for SimpleFeatures, SparseFeatures,
StringFeatures, SGD-QN, Online SGD, Online Liblinear, Online Vowpal Vabit
Heiko Strathmann
- Model selection framework for arbitrary Machines
- Statistics module
- Subset support in features
- Various bugfixes and structural improvements
- Serialization improvements and fixes
Alesis Novik
- Gaussian Mixture Models
Evgeniy Andreev:
- FibonacciHeap
- Python 3 support
- CoverTree
- HashSet
Justin Patera
- Ruby examples
Daniel Korn
- C# examples
Fernando José Iglesias Garcia
- Generic multiclass OvO training
- Quadratic Discriminant Analysis