• darch

  • Referenced in 321 articles [sw11086]
  • Package for deep architectures and Restricted-Bolzmann-Machines. The darch package is build ... method introduced by the publications ”A fast learning algorithm for deep belief nets...
  • XGBoost

  • Referenced in 125 articles [sw21035]
  • efficient, flexible and portable. It implements machine learning algorithms under the Gradient Boosting framework. XGBoost ... solve many data science problems in a fast and accurate way. The same code runs...
  • Apache Spark

  • Referenced in 63 articles [sw28418]
  • Apache Spark: Spark is a fast and general cluster computing system for Big Data ... DataFrames, MLlib for machine learning, GraphX for graph processing, and Spark Streaming for stream processing...
  • VFML

  • Referenced in 6 articles [sw11967]
  • streams. Welcome to the VFML (Very Fast Machine Learning) toolkit for mining high-speed data...
  • MXNet

  • Referenced in 36 articles [sw20940]
  • MXNet is a deep learning framework designed for both efficiency and flexibility. It allows ... that makes symbolic execution fast and memory efficient. MXNet is portable and lightweight, scaling effectively ... GPUs and multiple machines. MXNet is also more than a deep learning project...
  • LAMG

  • Referenced in 34 articles [sw06551]
  • Lean algebraic multigrid (LAMG): fast graph Laplacian linear solver. Laplacian matrices of graphs arise ... scale computational applications such as semisupervised machine learning; spectral clustering of images, genetic data ... coarse-level systems. This results in fast convergence and substantial setup and memory savings...
  • SSVM

  • Referenced in 64 articles [sw12678]
  • reformulation a Smooth Support Vector Machine (SSVM). A fast Newton-Armijo algorithm for solving ... Advances in kernel methods – support vector learning, MIT Press: Cambridge...
  • LightGBM

  • Referenced in 21 articles [sw27912]
  • highly efficient gradient boosting decision tree. A fast, distributed, high performance gradient boosting (GBDT, GBRT ... ranking, classification and many other machine learning tasks. It is under the umbrella...
  • AutoGraph

  • Referenced in 3 articles [sw30957]
  • that is scalable or fast to execute. In machine learning, imperative style libraries like Autograd...
  • AIDE

  • Referenced in 5 articles [sw28438]
  • AIDE: Fast and Communication Efficient Distributed Optimization. In this paper, we present two new communication ... settings that naturally arise in machine learning applications...
  • Edward

  • Referenced in 16 articles [sw21517]
  • criticism. It is a testbed for fast experimentation and research with probabilistic models, ranging from ... fuses three fields: Bayesian statistics and machine learning, deep learning, and probabilistic programming...
  • MASON

  • Referenced in 22 articles [sw28011]
  • Multiagent Simulation Environment. MASON is a fast, easily extensible, discrete-event multi-agent simulation toolkit ... tasks ranging from swarm robotics to machine learning to social complexity environments. MASON carefully delineates...
  • NEURObjects

  • Referenced in 3 articles [sw00617]
  • neural networks and fast prototyping of inductive machine learning applications. We present NEURObjects design issues...
  • TPMSVM

  • Referenced in 15 articles [sw12692]
  • parametric-margin ν-support vector machine (par-ν-SVM), this TPMSVM is suitable for many ... there is an advantage in the learning speed compared with ... indicate that the TPMSVM not only obtains fast learning speed, but also shows good generalization...
  • OP-ELM

  • Referenced in 22 articles [sw12171]
  • based on the original extreme learning machine (ELM) algorithm with additional steps to make ... used methodologies: multilayer perceptron (MLP), support vector machine (SVM), and Gaussian process ... original ELM. Despite the simplicity and fast performance, the OP-ELM is still able...
  • mnlogit

  • Referenced in 7 articles [sw21116]
  • optimized, parallel C++ library to achieve fast computation of Hessian matrices. Motivated by large scale ... multiclass classification problems in econometrics and machine learning...
  • Bolasso

  • Referenced in 29 articles [sw31649]
  • model with probability tending to one exponentially fast, while it selects all other variables with ... data and datasets from the UCI machine learning repository...
  • quanteda

  • Referenced in 9 articles [sw30853]
  • quanteda: Quantitative Analysis of Textual Data. A fast, flexible, and comprehensive framework for quantitative text ... content dictionaries, applying supervised and unsupervised machine learning, visually representing text and text analyses...
  • Hypermax

  • Referenced in 1 article [sw35101]
  • algorithm Adaptive-TPE, and it is fast and accurate optimizer that trades off between explore ... your results. It depends upon pretrained machine learning models that have been ... taught how to optimize your machine learning model as fast as possible. Read the research...
  • camel

  • Referenced in 10 articles [sw14318]
  • family of high-dimensional calibrated machine learning tools, including (1) LAD, SQRT Lasso and Calibrated ... combination of the dual smoothing and monotone fast iterative soft-thresholding algorithm (MFISTA). The computation...