All entries.
Showing Items 61-70 of 537 on page 7 of 54: First Previous 2 3 4 5 6 7 8 9 10 11 12 Next Last

Logo JMLR JKernelMachines 2.4

by dpicard - July 24, 2014, 13:51:44 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 10943 views, 2831 downloads, 2 subscriptions

Rating Whole StarWhole Star1/2 StarEmpty StarEmpty Star
(based on 1 vote)

About: machine learning library in java for easy development of new kernels

Changes:

Version 2.4

  • Added a simple GUI to rapidly test some algorithms
  • New Active Learning package
  • New algorithms (LLSVM, KMeans)
  • New Kernels (Polynomials, component wise)
  • Many bugfixes and improvements to existing algorithms
  • Many optimization

The number of changes in this version is massive, test it! Don't forget to report any regression.


Logo python weka wrapper 0.1.10

by fracpete - August 29, 2014, 05:00:14 CET [ Project Homepage BibTeX Download ] 3113 views, 626 downloads, 2 subscriptions

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

Changes:
  • fixed adding custom classpath using jvm.start(class_path=[...])

Logo JMLR dlib ml 18.10

by davis685 - August 29, 2014, 02:56:23 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 78443 views, 13618 downloads, 2 subscriptions

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:

In addition to a number of usability improvements, this release adds an implementation of the recent paper "One Millisecond Face Alignment with an Ensemble of Regression Trees" by Vahid Kazemi and Josephine Sullivan. This includes tools for performing high quality face landmarking as well as tools for training new landmarking models. See the face_landmark_detection_ex.cpp and train_shape_predictor_ex.cpp example programs for an introduction.


Logo RLPy 1.3a

by bobklein2 - August 28, 2014, 14:34:35 CET [ Project Homepage BibTeX Download ] 1422 views, 318 downloads, 1 subscription

About: RLPy is a framework for performing reinforcement learning (RL) experiments in Python. RLPy provides a large library of agent and domain components, and a suite of tools to aid in experiments (parallelization, hyperparameter optimization, code profiling, and plotting).

Changes:
  • Fixed bug where results using same random seed were different with visualization turned on/off
  • Created RLPy package on pypi (Available at https://pypi.python.org/pypi/rlpy)
  • Switched from custom logger class to python default
  • Added unit tests
  • Code readability improvements (formatting, variable names/ordering)
  • Restructured TD Learning heirarchy
  • Updated tutorials

Logo Salad 0.5.0

by chwress - August 22, 2014, 17:54:56 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 3263 views, 596 downloads, 1 subscription

About: A Content Anomaly Detector based on n-Grams

Changes:

Lots and lots of cool new features and bugfixes ;)

  • Refinements to the user interface: This includes a progress indicator, colors, etc.
  • Determine the expected error (salad-inspect)
  • Enable the user to echo the used parametrization: salad [train|predict|inspect] --echo-params
  • Allow to set the input batch size as program argument: salad [train|predict|inspect] --batch-size
  • libsalad: The library allows to access salad's basic functions
  • Installers and precompiled binaries: Windows installer, Debian (ppa:chwress/salad) & RPM packages as well a generic linux installers.
  • Various minor bug fixes
  • Support for "length at end" zip files
  • Improve salad's usage in a 2-class setting: salad [train|predict|inspect] --input-filter

Logo CURFIL 1.1

by hanschul - August 18, 2014, 13:54:31 CET [ Project Homepage BibTeX Download ] 311 views, 51 downloads, 1 subscription

About: CURFIL uses NVIDIA CUDA to accelerate random forest training and prediction for RGB and RGB-D images. It focuses on image labelling tasks, such as image segmentation or classification applications. CURFIL allows to search for optimal hyper-parameter configurations (e.g. using the hyperopt) package) by massively decreasing training time.

Changes:

Initial Announcement on mloss.org.


Logo BayesPy 0.2

by jluttine - August 14, 2014, 17:24:22 CET [ Project Homepage BibTeX Download ] 1160 views, 339 downloads, 2 subscriptions

About: Variational Bayesian inference tools for Python

Changes:
  • added all common distributions: Poisson, beta, multinomial, Bernoulli, categorical, etc

  • added Gaussian arrays (not just scalars or vectors)

  • added Gaussian Markov chains with time-varying or swithing dynamics

  • added discrete Markov chains (enabling hidden Markov models)

  • added deterministic gating node

  • added deterministic general sum-product node

  • added parameter expansion

  • added new plotting functions: pdf, Hinton diagram

  • added monitoring of posterior distributions during iteration

  • improved documentation


Logo Toeblitz Toolkit for Fast Toeplitz Matrix Operations 1.03

by cunningham - August 13, 2014, 02:21:36 CET [ BibTeX Download ] 1951 views, 501 downloads, 2 subscriptions

About: Toeblitz is a MATLAB/Octave package for operations on positive definite Toeplitz matrices. It can solve Toeplitz systems Tx = b in O(n*log(n)) time and O(n) memory, compute matrix inverses T^(-1) (with free log determinant) in O(n^2) time and memory, compute log determinants (without inverses) in O(n^2) time and O(n) memory, and compute traces of products A*T for any matrix A, in minimal O(n^2) time and memory.

Changes:

Adding a write-up in written/toeblitz.pdf describing the package.


Logo libcmaes 0.8.1

by beniz - August 12, 2014, 16:18:31 CET [ Project Homepage BibTeX Download ] 696 views, 132 downloads, 2 subscriptions

About: Libcmaes is a multithreaded C++11 library for high performance blackbox stochastic optimization using the CMA-ES algorithm for Covariance Matrix Adaptation Evolution Strategy. Libcmaes is useful to minimize / maximize any function, without information regarding gradient or derivability.

Changes:
  • Added customization of data to file streaming function, ref #51
  • Added configure control for compiling the library alone without examples or tools, ref #11
  • Fixed code in order to avoid various compiler warnings
  • Fixed sample code in README, ref #54
  • Fixed get_max_iter and set_mt_feval in Parameters object
  • New CMAParameters constructor, from x0 as a vector of double
  • Updated building instructions for Mac OSX
  • New set_str_algo in Parameters object

Logo Caffe 0.9999

by sergeyk - August 9, 2014, 01:57:58 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 3144 views, 525 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).

Changes:

LOTS of stuff: https://github.com/BVLC/caffe/releases/tag/v0.9999


Showing Items 61-70 of 537 on page 7 of 54: First Previous 2 3 4 5 6 7 8 9 10 11 12 Next Last