• Neural Network Toolbox

  • Referenced in 175 articles [sw07378]
  • dynamic networks. It also supports unsupervised learning with self-organizing maps and competitive layers. With...
  • Scikit

  • Referenced in 479 articles [sw08058]
  • machine learning algorithms for medium-scale supervised and unsupervised problems. This package focuses on bringing...
  • KEEL

  • Referenced in 109 articles [sw06791]
  • various kinds including as regression, classification, unsupervised learning, etc. It includes evolutionary learning algorithms based...
  • GloVe

  • Referenced in 62 articles [sw26211]
  • Word Representation. GloVe is an unsupervised learning algorithm for obtaining vector representations for words. Training...
  • STL-10 dataset

  • Referenced in 22 articles [sw39164]
  • image recognition dataset for developing unsupervised feature learning, deep learning, self-taught learning algorithms ... unlabeled examples is provided to learn image models prior to supervised training. The primary challenge ... challenging benchmark for developing more scalable unsupervised learning methods. Reference: Adam Coates, Honglak Lee, Andrew ... Analysis of Single Layer Networks in Unsupervised Feature Learning...
  • DeepWalk

  • Referenced in 44 articles [sw39604]
  • present DeepWalk, a novel approach for learning latent representations of vertices in a network. These ... recent advancements in language modeling and unsupervised feature learning (or deep learning) from sequences...
  • LS-SVMlab

  • Referenced in 26 articles [sw07367]
  • been introduced within the context of statistical learning theory and structural risk minimization ... Fisher discriminant analysis and extensions to unsupervised learning, recurrent networks and control are available. Robustness...
  • Statistics Toolbox

  • Referenced in 18 articles [sw10157]
  • Statistics Toolbox™ provides statistical and machine learning algorithms and tools for organizing, analyzing, and modeling ... regression. The toolbox provides supervised and unsupervised machine learning algorithms, including support vector machines (SVMs...
  • mdp

  • Referenced in 10 articles [sw14129]
  • collection of supervised and unsupervised learning algorithms and other data processing units that...
  • RolX

  • Referenced in 7 articles [sw32343]
  • linear in the number of edges), unsupervised learning approach for automatically extracting structural roles from...
  • RFCM

  • Referenced in 7 articles [sw02668]
  • rough and fuzzy sets. A hybrid unsupervised learning algorithm, termed as rough-fuzzy c-means...
  • CHIME

  • Referenced in 6 articles [sw28514]
  • with EM algorithm and its optimality. Unsupervised learning is an important problem in statistics...
  • quanteda

  • Referenced in 9 articles [sw30853]
  • applying content dictionaries, applying supervised and unsupervised machine learning, visually representing text and text analyses...
  • subgraph2vec

  • Referenced in 4 articles [sw36496]
  • neighbourhoods of nodes to learn their latent representations in an unsupervised fashion. We demonstrate that ... could be used for building a deep learning variant of Weisfeiler-Lehman graph kernel ... graph kernels on both supervised and unsupervised learning tasks. Specifically, on two realworld program analysis...
  • SOFAR

  • Referenced in 7 articles [sw31665]
  • with broad applications to both unsupervised and supervised learning tasks, such as biclustering with sparse...
  • GLISSOM

  • Referenced in 6 articles [sw04192]
  • subsequently organized through an unsupervised Hebbian learning process using visual input. Weak connections are eliminated...
  • FoldingNet

  • Referenced in 3 articles [sw32562]
  • been state-of-the-art for supervised learning tasks on point clouds such as classification ... auto-encoder is proposed to address unsupervised learning challenges on point clouds. On the encoder...
  • UnFlow

  • Referenced in 3 articles [sw38831]
  • UnFlow: Unsupervised Learning of Optical Flow with a Bidirectional Census Loss ... deep learning, many advances in computer vision are driven by large amounts of labeled data ... based optical flow methods, we design an unsupervised loss based on occlusion-aware bidirectional flow...
  • Karate Club

  • Referenced in 2 articles [sw32339]
  • Oriented Open-source Python Framework for Unsupervised Learning on Graphs. We present Karate Club ... graph mining algorithms which can solve unsupervised machine learning tasks. The primary goal...
  • 3DMatch

  • Referenced in 4 articles [sw32561]
  • present 3DMatch, a data-driven model that learns a local volumetric patch descriptor for establishing ... model, we propose an unsupervised feature learning method that leverages the millions of correspondence labels...