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- MLOSS workshop at ICML 2015: Open Ecosystems
by
Antti Honkela
on March 30, 2015
- A third of the top 100 papers are about software
by
Cheng Soon Ong
on October 30, 2014
- Open Machine Learning Workshop
by
Cheng Soon Ong
on July 28, 2014
- Machine Learning Distro
by
Cheng Soon Ong
on July 22, 2014
- Google Summer of Code 2014
by
Cheng Soon Ong
on June 3, 2014
- Reproducibility is not simple
by
Cheng Soon Ong
on March 30, 2014
- Keynotes at ACML 2013
by
Cheng Soon Ong
on November 14, 2013
- What does the “OSS” in MLOSS mean?
by
Mark Reid
on September 1, 2013
- Code review for science
by
Cheng Soon Ong
on August 14, 2013
- GSoC 2013
by
Cheng Soon Ong
on April 9, 2013
No forum yet.
About:
A recommender systems research framework aimed at modeling non-stationary environments.
Changes:
Initial Announcement on mloss.org.
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About:
A probabilistic programming language embedded in Haskell.
Changes:
Initial Announcement on mloss.org.
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About:
R package facilitating the simulation and evaluation of context-free and contextual Multi-Armed Bandit policies.
Changes:
Minor update.
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About:
Wrapper Algorithm for All Relevant Feature Selection
Changes:
Fetched by r-cran-robot on 2018-09-01 00:00:04.516878
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About:
Bayesian Additive Regression Trees
Changes:
Fetched by r-cran-robot on 2018-09-01 00:00:03.597464
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About:
Gradient Boosting
Changes:
Fetched by r-cran-robot on 2018-09-01 00:00:05.199020
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About:
A fast, flexible C++ machine learning library, with bindings to other languages.
Changes:
Released June 8th, 2018.
-
Documentation generation fixes for Python bindings (#1421).
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Fix build error for man pages if command-line bindings are not being built (#1424).
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Add shuffle parameter and Shuffle() method to KFoldCV (#1412). This will shuffle the data when the object is constructed, or when Shuffle() is called.
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Added neural network layers: AtrousConvolution (#1390), Embedding (#1401), and LayerNorm (layer normalization) (#1389).
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Add Pendulum environment for reinforcement learning (#1388) and update Mountain Car environment (#1394).
- Authors:
Ryan Curtin,
James Cline,
Neil Slagle,
Matthew Amidon,
Ajinkya Kale,
Bill March,
Nishant Mehta,
Parikshit Ram,
Dongryeol Lee,
Rajendran Mohan,
Trironk Kiatkungwanglai,
Patrick Mason,
Marcus Edel,
Etc
- License:
Bsd,
Bsd 3 Clause License
- Programming Language:
C++,
Python,
Shell
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- Operating System:
Platform Independent
- Data Formats:
Plain Ascii,
Ascii,
Txt,
Hdf,
Bin,
Csv,
Xml
- JMLR-MLOSS Publication:
JMLR Page
- Tags:
Gmm,
Hmm,
Machine Learning,
Sparse,
Dual Tree,
Fast,
Scalable,
Tree
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About:
A header-only C++ library for solving large scale eigenvalue problems
Changes:
-
Fixed regressions in v0.6.1 on some edge cases
-
Improved the accuracy of restarting processes in
SymEigsSolver and GenEigsSolver
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Code and documentation cleanup
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About:
A Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. Dynamically generates CPU and GPU modules for good performance. Deep Learning Tutorials illustrate deep learning with Theano.
Changes:
Theano 1.0.2 (23rd of May, 2018)
This is a maintenance release of Theano, version 1.0.2, with no
new features, but some important bug fixes.
We recommend that everybody update to this version.
Highlights (since 1.0.1):
-
Theano should work under PyPy now (this is experimental).
-
Update for cuDNN 7.1 RNN API changes.
-
Fix for a crash related to mixed dtypes with cuDNN convolutions.
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MAGMA should work in more cases without manual config.
-
Handle reductions with non-default accumulator dtype better on the GPU.
-
Improvements to the test suite so that it fails less often due to
random chance.
A total of 6 people contributed to this release since 1.0.1:
-
Frederic Bastien
-
Steven Bocco
-
Jon Haygood
-
Arnaud Bergeron
-
Jordan Melendez
-
Desiree Vogt-Lee
-
Garming Sam
-
Pascal Lamblin
-
Vincent Dumoulin
-
Glexin
-
Simon Lefrancois
|
About:
This project is a C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real world problems.
Changes:
This release adds a bunch of new image processing routines as well as many minor usability improvements and bug fixes.
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- Operating System:
Linux,
Macosx,
Windows,
Unix,
Solaris
- Data Formats:
Svmlight,
Binary,
Csv
- JMLR-MLOSS Publication:
JMLR Page
- Tags:
Svm,
Classification,
Clustering,
Regression,
Kernel Methods,
Matrix Library,
Kkmeans,
Optimization,
Algorithms,
Exact Bayesian Methods,
Approximate Inference,
Bayesian Networks,
Junction Tree
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About:
In DMNS source, five databases are used in slover.cpp and data_veh_layer.cpp,
these images and databases are included in this file, except munich database.
Changes:
Initial Announcement on mloss.org.
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About:
Deep measuring net sequence(DMNS) is a sequence of three deep measuring nets, the later are deep fcn-based networks, directely output object category score, object orientation, location and scale simultaneously without any anchor boxes. DMNS acheived high accuracy in maneuvering target detection and geometrical measurements. Its average orientation error is less than 3.5 degree, loaction error less than 1.3 pixel, scale measuring error less than 10%, achieve a detection F1-score 96.5% in OAD, 91.8% in SVDS ,90.8% in Munich , 87.3% in OIRDS, outperforms SSD, Fater R-CNN, etc.
Changes:
Initial Announcement on mloss.org.
|
About:
Aika is an open source text mining engine. It can automatically extract and annotate semantic information in text. In case this information is ambiguous, Aika will generate several hypothetical interpretations about the meaning of this text and retrieve the most likely one.
Changes:
Aika Version 0.17 2018-05-14
-
Introduction of synapse relations. Previously the relation between synapses was implicitly modeled through word positions (RIDs). Now it is possible to explicitly model relations like: The end position of input activation 1 equals to the begin position of input activation 2. Two types of relations are currently supported, range relations and instance relations. Range relations compare the input activation range of a given synapse with that of the linked synapse. Instance relations also compare the input activations of two synapses, but instead of the ranges the dependency relations of these activations are compared.
-
Removed the norm term from the interpretation objective function.
-
Introduction of an optional distance function to synapses. It allows to model a weakening signal depending on the distance of the activation ranges.
-
Example implementation of a context free grammar.
-
Example implementation for co-reference resolution.
-
Work on an syllable identification experiment based on the meta network implementation.
Aika Version 0.15 2018-03-16
-
Simplified interpretation handling by removing the InterpretationNode class and moving the remaining logic to the Activation class.
-
Moved the activation linking and activation selection code to separate classes.
-
Ongoing work on the training algorithms.
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About:
A WEKA package for analyzing emotion and sentiment of tweets.
Changes:
Initial Announcement on mloss.org.
|
About:
Bayesian Additive Regression Trees
Changes:
Fetched by r-cran-robot on 2018-09-01 00:00:04.021726
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About:
A fast and scalable graph-based clustering algorithm based on the eigenvectors of the nonlinear 1-Laplacian.
Changes:
-
improved optimization of ncut and rcut criterion
-
optimized eigenvector initialization
-
changed default values for number of runs
-
several internal optimizations
-
made console output more informative
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About:
Armadillo is a high quality C++ library for linear algebra & scientific computing, aiming towards a good balance between speed and ease of use. The function syntax is deliberately similar to MATLAB. Useful for algorithm development directly in C++, or quick conversion of research code into production environments (eg. software & hardware products).
Changes:
-
faster handling of sparse matrices by kron() and repmat()
-
faster transpose of sparse matrices
-
faster element access in sparse matrices
-
faster row iterators for sparse matrices
-
faster handling of compound expressions by trace()
-
more efficient handling of aliasing in submatrix views
-
expanded normalise() to handle sparse matrices
-
expanded .transform() and .for_each() to handle sparse matrices
-
added reverse() for reversing order of elements
-
added repelem() for replicating elements
-
added roots() for finding the roots of a polynomial
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- Operating System:
Linux,
Windows,
Unix,
Mac Os X
- Data Formats:
Ascii,
Binary,
Hdf,
Csv
- Tags:
Matlab,
Matrix Library,
Atlas,
Lapack,
Linear Algebra,
Templates
|
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About:
A Graphical Tool for Designing and Training Deep Neural Networks
Changes:
-
new Caffe version manager
-
added separate executable for remote server
-
new Session cloning behavior
-
improved Host Manager design
-
change database location in Input Manager
-
many smaller improvements and bugfixes
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About:
Mining Association Rules and Frequent Itemsets
Changes:
Fetched by r-cran-robot on 2018-09-01 00:00:03.513366
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About:
SMPyBandits: an Open-Source Research Framework for Single and Multi-Players Multi-Arms Bandits (MAB) Algorithms in Python
Changes:
Initial Announcement on mloss.org.
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