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Logo Caffe 0.9999

by sergeyk - August 9, 2014, 01:57:58 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 11709 views, 1896 downloads, 2 subscriptions

About: Caffe aims to provide computer vision scientists with a clean, modifiable implementation of state-of-the-art deep learning algorithms. We believe that Caffe is the fastest available GPU CNN implementation. Caffe also provides seamless switching between CPU and GPU, which allows one to train models with fast GPUs and then deploy them on non-GPU clusters. Even in CPU mode, computing predictions on an image takes only 20 ms (in batch mode).


LOTS of stuff:

Logo GPDT Gradient Projection Decomposition Technique 1.01

by sezaza - December 21, 2007, 20:10:43 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 10179 views, 1889 downloads, 1 subscription

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About: This is a C++ software designed to train large-scale SVMs for binary classification. The algorithm is also implemented in parallel (**PGPDT**) for distributed memory, strictly coupled multiprocessor [...]


Initial Announcement on

Logo SCD 2.1

by ambujtewari - December 3, 2009, 22:21:45 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 9569 views, 1882 downloads, 1 subscription

About: A (randomized) coordinate descent procedure to minimize L1 regularized loss for classification and regression purposes.


Fixed some I/O bugs. Lines that ended with whitespace were not read correctly in the previous version.

Logo Oger 1.1.3

by dvrstrae - August 13, 2012, 14:55:41 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 4839 views, 1876 downloads, 1 subscription

About: The OrGanic Environment for Reservoir computing (Oger) toolbox is a Python toolbox for rapidly building, training and evaluating modular learning architectures on large datasets.


Initial Announcement on

Logo r-cran-tree 1.0-29

by r-cran-robot - July 24, 2011, 00:00:00 CET [ Project Homepage BibTeX Download ] 9752 views, 1871 downloads, 1 subscription

About: Classification and regression trees


Fetched by r-cran-robot on 2012-02-01 00:00:11.999664

Logo A Pattern Recognizer In Lua with ANNs v0.4.1

by pakozm - December 3, 2015, 15:01:36 CET [ Project Homepage BibTeX Download ] 8279 views, 1868 downloads, 2 subscriptions

About: APRIL-ANN toolkit (A Pattern Recognizer In Lua with Artificial Neural Networks). This toolkit incorporates ANN algorithms (as dropout, stacked denoising auto-encoders, convolutional neural networks), with other pattern recognition methods as hidden makov models (HMMs) among others.

  • Updated home repository link to follow april-org github organization.
  • Improved serialize/deserialize functions, reimplemented all the serialization procedure.
  • Added exceptions support to LuaPkg and APRIL-ANN, allowing to capture C++ errors into Lua code.
  • Added set class.
  • Added series class.
  • Added data_frame class, similar to Python Pandas DataFrame.
  • Serialization and deserilization have been updated with more robust and reusable API, implemented in util.serialize() and util.deserialize() functions.
  • Added matrix.ext.broadcast utility (similar to broadcast in numpy).
  • Added ProbablisitcMatrixANNComponent, which allow to implement probabilistic mixtures of posteriors and/or likelihoods.
  • Added batch normalization ANN component.
  • Allowing matrix.join to add new axis.
  • Added methods prod(), cumsum() and cumprod() at matrix classes.
  • Added methods count_eq() and count_neq() at matrix classes.
  • Serializable objects API have been augmented with methods ctor_name() and
    ctor_params() in Lua, refered to luaCtorName() and luaCtorParams() in C++.
  • Added to dynamic cast C++ objects pushed into Lua, allowing to convert base class objects into any of its derived classes.
  • Added matrix.sparse as valid values for targets in ann.loss.mse and
  • Changed matrix metamethods __index and __newindex, allowing to use
    matrix objects with standard Lua operator[].
  • Added matrix.masked_fill and matrix.masked_copy matrix.
  • Added matrix.indexed_fill and matrix.indexed_copy matrix.
  • Added ann.components.probabilistic_matrix, and its corresponding specializations ann.components.left_probabilistic_matrix and
  • Added operator[] in the right side of matrix operations.
  • Added ann.components.transpose.
  • Added max_gradients_norm in traianble.supervised_trainer, to avoid gradients exploding.
  • Added ann.components.actf.sparse_logistic a logistic activation function with sparsity penalty.
  • Simplified math.add, math.sub, ... and other math extensions for reductions, their original behavior can be emulated by using bind function.
  • Added bind function to freeze any positional argument of any Lua function.
  • Function stats.boot uses multiple_unpack to allow a table of sizes and the generation of multiple index matrices.
  • Added multiple_unpack Lua function.
  • Added __tostring metamethod to numeric memory blocks in Lua.
  • Added dataset.token.sparse_matrix, a dataset which allow to traverse by rows a sparse matrix instance.
  • Added, a builder which uses the Dictionary-of-Keys format to construct a sparse matrix from scratch.
  • Added method data to numeric matrix classes.
  • Added methods values, indices, first_index to sparse matrix class.
  • Fixed bugs when reading bad formed CSV files.
  • Fixed bugs at statistical distributions.
  • FloatRGB bug solved on equal (+=, -=, ...) operators. This bug affected ImageRGB operations such as resize.
  • Solved problems when chaining methods in Lua, some objects end to be garbage collected.
  • Improved support of strings in auto-completion (rlcompleter package).
  • Solved bug at SparseMatrix<T> when reading it from a file.
  • Solved bug in Image<T>::rotate90_cw methods.
  • Solved bug in SparseMatrix::toDense() method.


  • Better LuaTable accessors, using [] operator.
  • Implementation of matrix __index, __newindex and __call metamethods in C++.
  • Implementation of matProd(), matCumSum() and matCumProd() functions.
  • Implementation of matCountEq() and matCountNeq() functions for
  • Updated matrix_ext_operations.h to change API of matrix operations. All functions have been overloaded to accept an in-place operation and another version which receives a destination matrix.
  • Adding iterators to language models.
  • Added MatrixScalarMap2 which receives as input2 a SparaseMatrix instance. This functions needs to be generalized to work with CPU and CUDA.
  • The method SparseMatrix<T>::fromDenseMatrix() uses a DOKBuilder object to build the sparse matrix.
  • The conversion of a Matrix<T> into a SparseMatrix<T> has been changed from a constructor overload to the static method
  • Added support for IPyLua.
  • Optimized matrix access for confusion matrix.
  • Minor changes in class.lua.
  • Improved binding to avoid multiple object copies when pushing C++ objects.
  • Added Git commit hash and compilation time.

Logo r-cran-gbm 2.0-8

by r-cran-robot - January 17, 2013, 00:00:00 CET [ Project Homepage BibTeX Download ] 9039 views, 1868 downloads, 1 subscription

About: Generalized Boosted Regression Models


Fetched by r-cran-robot on 2013-04-01 00:00:05.019963

Logo K tree 0.4.2

by cdevries - July 4, 2011, 06:01:59 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 8860 views, 1863 downloads, 1 subscription

About: The K-tree is a scalable approach to clustering inspired by the B+-tree and k-means algorithms.


Release of K-tree implementation in Python. This is targeted at a research and rapid prototyping audience.

Logo Nested Effects Models 2.4.0

by florian - July 8, 2008, 00:05:59 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 7219 views, 1849 downloads, 1 subscription

About: Nested Effects Models (NEMs) are a class of directed graphical models originally introduced to analyze the effects of gene perturbation screens with high-dimensional phenotypes. In contrast to other [...]


Initial Announcement on

Logo mcmkl 0.1

by ong - May 15, 2008, 15:30:44 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 9107 views, 1848 downloads, 1 subscription

About: We provide some preliminary code for multiclass multiple kernel learning in Matlab using CPLEX as a base solver.


Initial Announcement on

Showing Items 201-210 of 624 on page 21 of 63: First Previous 16 17 18 19 20 21 22 23 24 25 26 Next Last