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@karlnapf karlnapf released this Jul 5, 2019 · 1072 commits to develop since this release

  • Bugfixes:
    - Fix cookbook examples for website
Assets 2

@vigsterkr vigsterkr released this Dec 7, 2017 · 1072 commits to develop since this release


  • Drop all <math.h> function calls [Viktor Gal]
  • Use c++11 std::isnan, std:isfinite, std::isinf [Viktor Gal]


  • Port ipython notebooks to be python3 compatible [Viktor Gal]
  • Use the shogun-static library on Windows when linking the interface library [Viktor Gal]
  • Fix python typemap when compiling with MSVC [Viktor Gal]
  • Fix ShogunConfig.cmake paths [Viktor Gal]
  • Fix meta example parser bug in parallel builds [Esben Sørig]
Assets 2

@vigsterkr vigsterkr released this Nov 29, 2017 · 1095 commits to develop since this release


  • Fix installation of examples on WIN32 [Viktor Gal]
Assets 2

@vigsterkr vigsterkr released this Nov 29, 2017 · 1097 commits to develop since this release


  • Install headers of GPL models when LICENSE_GPL_SHOGUN is enabled [Viktor Gal]
  • Always turn on LIBSHOGUN_BUILD_STATIC when compiling with MSVC [Viktor Gal]
  • Fix ipython notebook errors [Viktor Gal]
Assets 2

@vigsterkr vigsterkr released this Nov 28, 2017 · 1101 commits to develop since this release

  • This release is dedicated for Heiko's successful PhD defense!

  • Add conda-forge packages, to get prebuilt binaries via the cross-platform conda package manager [Dougal Sutherland]

  • Change interface cmake variables to INTERFACE_*

  • Move GPL code to gpl submodule [Heiko Strathmann]


  • Enable using BLAS/LAPACK from Eigen by default [Viktor Gal]
  • Add iterators to SGVector and SGMatrix [Viktor Gal]
  • Significantly lower the runtime of KernelPCA (GSoC '17) [Michele Mazzoni]
  • Refactor FisherLDA and LDA solvers (GSoC '17) [Michele Mazzoni]
  • Add automated test for trained model serialization (GSoC '17) [Michele Mazzoni]
  • Enable SWIG director classes by default [Viktor Gal]
  • Vectorize DotFeatures covariance/mean calculation [Michele Mazzoni]
  • Support for premature stopping of model training (GSoC '17) [Giovanni De Toni]
  • Add support for observable variables (GSoC '17) [Giovanni De Toni]
  • Use TFLogger to serialize observed variables for TensorBoard (GSoC '17) [Giovanni De Toni]
  • Drop CMath::dot and SGVector::dot and use linalg::dot [Viktor Gal]
  • Added class probabilities for BaggingMachine (GSoC '17) [Olivier Nguyen]


  • Fix transpose bug in Ruby typemap for matrices [Elias Saalmann]
  • Fix MKL detection and linking; use mkl_rt when available [Viktor Gal]
  • Fix Windows static linking [Viktor Gal]
  • Fix SWIG interface compilation on Windows [qcrist]
  • Fix CircularBuffer bug that broke parsing of big CSV and LibSVM files #1991 [Viktor Gal]
  • Fix R interface when using clang to compile the interface [Viktor Gal]
Assets 2

@vigsterkr vigsterkr released this Apr 23, 2017 · 1483 commits to develop since this release

  • Add native MS Windows support [Viktor Gal]
  • Shogun requires the compiler to support C++11 features
  • Shogun cloud online: Jupyter notebook with Shogun from the browser,


  • LDA now supports 32, 64 and 128 bit floating point numbers [Chris Goldsworthy]
  • Add SHOGUN_NUM_THREADS enviroment variable to control the number of threads
    used by the models in runtime [Viktor Gal]
  • Added Scala Interface to the build [Abhinav Rai]
  • Major re-writing and API changes in kernel statistical hypothesis
    testing framework, significant speed up in permutation test for
    quadratic time MMD, new kernel selection algorithms for quadratic time MMD [Soumyajit De]


  • Fix build error of R interface for R>=3.3.0, #3460 [Heiko Strathmann]
  • Make the code compatible with Eigen 3.3.0 [Viktor Gal]
  • Fix number of CPUs detected on Linux [Viktor Gal]
  • Fix multi-threading in KMeansBase [Viktor Gal]
  • Make ExponentialARDKernel thread-safe [Viktor Gal]
  • Make PRNG thread-safe [Viktor Gal]
  • Fix python interface when using libshogun compiled with OpenMP [Viktor Gal]
  • Fix CART to work with cross-validation [Fernando Iglesias]

Cleanup, efficiency updates, and API Changes:

  • Port multi-threading to use OpenMP backend in Kernel [Viktor Gal]
  • Fix false sharing in EuclideanDistance [Viktor Gal]
  • Fix out of source build of the whole project [Viktor Gal]
  • Add LIBSHOGUN cmake flag to turn off libshogun compilation [Viktor Gal]
  • Export Shogun target with cmake to enable to build modular interfaces to a
    pre-compiled libshogun on the system without requiring to compile
    libshogun itself [Viktor Gal]


  • Contains major rewrite and clean-up of developer documentation in doc/readme [Heiko Strathmann, Lea Götz]
  • Known issue: Octave multithreaded crashes, currently bindings are initialized single-threaded, #3772 [Heiko Strathmann]
Assets 2

@vigsterkr vigsterkr released this Nov 4, 2016 · 2115 commits to develop since this release


  • GSoC 2016 project of Saurabh Mahindre: Major efficiency improvements for KMeans, LARS, Random Forests, Bagging, KNN.
  • Add new Shogun cookbook for documentation and testing across all target languages [Heiko Strathmann, Sergey Lisitsyn, Esben Sorig, Viktor Gal].
  • Added option to learn CombinedKernel weights with GP approximate inference [Wu Lin].
  • LARS now supports 32, 64, and 128 bit floating point numbers [Chris Goldsworthy].


  • Fix gTest segfaults with GCC >= 6.0.0 [Björn Esser].
  • Make Java and CSharp install-dir configurable [Björn Esser].
  • Autogenerate modshogun.rb with correct module-suffix [Björn Esser].
  • Fix KMeans++ initialization [Saurabh Mahindre].

Cleanup, efficiency updates, and API Changes:

  • Make Eigen3 a hard requirement. Bundle if not found on system. [Heiko Strathmann]
  • Drop ALGLIB (GPL) dependency in CStatistics and ship CDFLIB (public domain) instead [Heiko Strathmann]
  • Drop p-value estimation in model-selection [Heiko Strathmann]
  • Static interfaces have been removed [Viktor Gal]
  • New base class ShiftInvariantKernel of which GaussianKernel inherits [Rahul De].


This version contains a new CMake option USE_GPL_SHOGUN, which when set to OFF will exclude all GPL codes from Shogun [Heiko Strathmann].

Assets 2

@karlnapf karlnapf released this May 17, 2016 · 2953 commits to develop since this release

This is a new feature and cleanup release.


  • Added GEMPLP for approximate inference to the structured output framework [Jiaolong Xu].
  • Effeciency improvements of the FITC framework for GP inference (FITC_Laplce, FITC, VarDTC) [Wu Lin].
  • Added optimisation of inducing variables in sparse GP inference [Wu Lin].
  • Added optimisation methods for GP inference (Newton, Cholesky, LBFGS, ...) [Wu Lin].
  • Added Automatic Relevance Determination (ARD) kernel functionality for variational GP inference [Wu Lin].
  • Updated Notebook for variational GP inference [Wu Lin].
  • New framework for stochastic optimisation (L1/2 loss, mirror descent, proximal gradients, adagrad, SVRG, RMSProp, adadelta, ...) [Wu Lin].
  • New Shogun meta-language for automatically generating code listings in all target languages [Esben Sörig].
  • Added periodic kernel [Esben Sörig].
  • Add gradient output functionality in Neural Nets [Sanuj Sharma].


  • Fixes for java_modular build using OpenJDK [Björn Esser].
  • Catch uncaught exceptions in Neural Net code [Khaled Nasr].
  • Fix build of modular interfaces with SWIG 3.0.5 on MacOSX [Björn Esser].
  • Fix segfaults when calling delete[] twice on SGMatrix-instances [Björn Esser].
  • Fix for building with full-hardening-(CXX|LD)FLAGS [Björn Esser].
  • Patch SWIG to fix a problem with SWIG and Python >= 3.5 [Björn Esser].
  • Add modshogun.rb: make sure narray is loaded before [Björn Esser].
  • set working-dir properly when running R (#2654) [Björn Esser].

Cleanup, efficiency updates, and API Changes:

  • Added GPU based dot-products to linalg [Rahul De].
  • Added scale methods to linalg [Rahul De].
  • Added element wise products to linalg [Rahul De].
  • Added element-wise unary operators in linalg [Rahul De].
  • Dropped parameter migration framework [Heiko Strathmann].
  • Disabled Python integration tests by default [Sergey Lisitsyn, Heiko Strathmann].
Assets 2

@vigsterkr vigsterkr released this Jan 18, 2015 · 3525 commits to develop since this release

  • This release features the work of our 8 GSoC 2014 students [student; mentors]:
    • OpenCV Integration and Computer Vision Applications [Abhijeet Kislay; Kevin Hughes]
    • Large-Scale Multi-Label Classification [Abinash Panda; Thoralf Klein]
    • Large-scale structured prediction with approximate inference [Jiaolong Xu; Shell Hu]
    • Essential Deep Learning Modules [Khaled Nasr; Sergey Lisitsyn, Theofanis Karaletsos]
    • Fundamental Machine Learning: decision trees, kernel density estimation [Parijat Mazumdar ; Fernando Iglesias]
    • Shogun Missionary & Shogun in Education [Saurabh Mahindre; Heiko Strathmann]
    • Testing and Measuring Variable Interactions With Kernels [Soumyajit De; Dino Sejdinovic, Heiko Strathmann]
    • Variational Learning for Gaussian Processes [Wu Lin; Heiko Strathmann, Emtiyaz Khan]
  • This release also contains several cleanups and bugfixes:
    • Features:
      • New Shogun project description [Heiko Strathmann]
      • ID3 algorithm for decision tree learning [Parijat Mazumdar]
      • New modes for PCA matrix factorizations: SVD & EVD, in-place or reallocating [Parijat Mazumdar]
      • Add Neural Networks with linear, logistic and softmax neurons [Khaled Nasr]
      • Add kernel multiclass strategy examples in multiclass notebook [Saurabh Mahindre]
      • Add decision trees notebook containing examples for ID3 algorithm [Parijat Mazumdar]
      • Add sudoku recognizer ipython notebook [Alejandro Hernandez]
      • Add in-place subsets on features, labels, and custom kernels [Heiko Strathmann]
      • Add Principal Component Analysis notebook [Abhijeet Kislay]
      • Add Multiple Kernel Learning notebook [Saurabh Mahindre]
      • Add Multi-Label classes to enable Multi-Label classification [Thoralf Klein]
      • Add rectified linear neurons, dropout and max-norm regularization to neural networks [Khaled Nasr]
      • Add C4.5 algorithm for multiclass classification using decision trees [Parijat Mazumdar]
      • Add support for arbitrary acyclic graph-structured neural networks [Khaled Nasr]
      • Add CART algorithm for classification and regression using decision trees [Parijat Mazumdar]
      • Add CHAID algorithm for multiclass classification and regression using decision trees [Parijat Mazumdar]
      • Add Convolutional Neural Networks [Khaled Nasr]
      • Add Random Forests algorithm for ensemble learning using CART [Parijat Mazumdar]
      • Add Restricted Botlzmann Machines [Khaled Nasr]
      • Add Stochastic Gradient Boosting algorithm for ensemble learning [Parijat Mazumdar]
      • Add Deep contractive and denoising autoencoders [Khaled Nasr]
      • Add Deep belief networks [Khaled Nasr]
    • Bugfixes:
      • Fix reference counting bugs in CList when reference counting is on [Heiko Strathmann, Thoralf Klein, lambday]
      • Fix memory problem in PCA::apply_to_feature_matrix [Parijat Mazumdar]
      • Fix crash in LeastAngleRegression for the case D greater than N [Parijat Mazumdar]
      • Fix memory violations in bundle method solvers [Thoralf Klein]
      • Fix fail in library_mldatahdf5.cpp example when is not working properly [Parijat Mazumdar]
      • Fix memory leaks in Vowpal Wabbit, LibSVMFile and KernelPCA [Thoralf Klein]
      • Fix memory and control flow issues discovered by Coverity [Thoralf Klein]
      • Fix R modular interface SWIG typemap (Requires SWIG >= 2.0.5) [Matt Huska]
    • Cleanup and API Changes:
      • PCA now depends on Eigen3 instead of LAPACK [Parijat Mazumdar]
      • Removing redundant and fixing implicit imports [Thoralf Klein]
      • Hide many methods from SWIG, reducing compile memory by 500MiB [Heiko Strathmann, Fernando Iglesias, Thoralf Klein]
Assets 2
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