About: Regularization for semiparametric additive hazards regression

Fetched by r-cran-robot on 2018-09-01 00:00:03.378832

About: DAL is an efficient and flexibible MATLAB toolbox for sparse/low-rank learning/reconstruction based on the dual augmented Lagrangian method.

• Supports weighted lasso (dalsqal1.m, dallral1.m)
• Supports weighted squared loss (dalwl1.m)
• Bug fixes (group lasso and elastic-net-regularized logistic regression)

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 cast.to 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
  ann.loss.cross_entropy.
• 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
  ann.components.right_probabilistic_matrix.
• 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 matrix.sparse.builders.dok, 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.

C/C++

• 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
  Matrix<T>.
• 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
  SparseMatrix<T>::fromDenseMatrix().
• 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.

About: Logic Regression

Fetched by r-cran-robot on 2013-04-01 00:00:06.139495

About: The UniverSVM is a SVM implementation written in C/C++. Its functionality comprises large scale transduction via CCCP optimization, sparse solutions via CCCP optimization and data-dependent [...]

Minor changes: fix bug on set_alphas_b0 function (thanks to Ferdinand Kaiser - ferdinand.kaiser@tut.fi)

About: KeplerWeka represents the integration of all the functionality of the WEKA Machine Learning Workbench into the open-source scientific workflow Kepler. Among them are classification, [...]

• Now compatible with Kepler 2.0
• New version of WEKA included (patched 3.7.2 release), WEKA's new package manager works in conjunction with Kepler
• Renamed actor Count to ConditionalTee, introduced new Count actor
• Removed actors OutputLogger, MultiSync, TwinSync

About: A thin Python3 wrapper that uses the javabridge Python library to communicate with a Java Virtual Machine executing Weka API calls.

• upgraded to Weka 3.9.2
• properly initializing package support now, rather than adding package jars to classpath
• added weka.core.ClassHelper Java class for obtaining classes and static fields, as javabridge only uses the system class loader

About: OpenNN is a software library written in C++ for advanced analytics. It implements neural networks, the most successful machine learning method. The library has been designed to learn from both data sets and mathematical models.

New algorithms, correction of bugs.

About: Large scale, distributed graph processing made easy.

Graph partitioning methods APSP approximation method Performance improvements License change Bug fixes

About: Hivemall is a scalable machine learning library running on Hive/Hadoop.

• Supported Matrix Factorization
• Added a support for TF-IDF computation
• Supported AdaGrad/AdaDelta
• Supported AdaGradRDA classification
• Added normalization scheme

About: KReator is an integrated development environment (IDE) for relational probabilistic knowledge representation languages. At the moment, KReator supports Bayesian Logic Programs (BLPs), Markov Logic Networks (MLNs), Relational Maximum Entropy (RME), Relational Bayesian Networks (RBN), and Probabilistic Prolog (ProbLog).

• several bugfixes
• Beta version of ProbLog plugin
• enhanced command completion in console
• enhanced error messages for syntax errors
• refactored logic libraries
• added prettyprint function in console
• added syntax highlighting for RBNs

About: R package facilitating the simulation and evaluation of context-free and contextual Multi-Armed Bandit policies.

Minor update.

About: svmpath

Fetched by r-cran-robot on 2012-02-01 00:00:11.755984

About: Data Sets, Functions and Examples from the Book

Fetched by r-cran-robot on 2018-01-01 00:00:07.925283

About: An implementation of the infinite hidden Markov model.

Since 0.4: Removed dependency from lightspeed (now using statistics toolbox). Updated to newer matlab versions.

About: A MATLAB spectral clustering package to deal with large data sets. Our tool can handle large data sets (200,000 RCV1 data) on a 4GB memory general machine. Spectral clustering algorithm has been [...]

• Add bib
• Add code of nystrom without orthogonalization
• Add accuracy quality measure
• Add more running scripts

About: Heteroscedastic Discriminant Analysis

Fetched by r-cran-robot on 2013-04-01 00:00:05.551691

About: An open source Java software providing collaborative filtering algorithms.

Initial Announcement on mloss.org.

About: Bayesian Additive Regression Trees

Fetched by r-cran-robot on 2018-09-01 00:00:03.597464

About: MOSIS is a modularized framework for signal processing, stream analysis, machine learning and stream mining applications.

• Move "flow"-related classes into package "de.claas.mosis.flow" (e.g. Node and Link).
• Refined and improved "flow"-related tests (e.g. Iterator and Node tests).
• Refactored tests for data formats (e.g. PlainText and JSON tests).
• Added visitor design pattern for graph-based functions (e.g. initialization and processing).
• Documented parameters of Processor implementations.