• AdaGrad

  • Referenced in 166 articles [sw22202]
  • Adaptive subgradient methods for online learning and stochastic optimization. We present a new family ... iterations to perform more informative gradient-based learning. Metaphorically, the adaptation allows us to find ... from recent advances in stochastic optimization and online learning which employ proximal functions to control...
  • LIBSVM

  • Referenced in 1204 articles [sw04879]
  • LIBSVM has gained wide popularity in machine learning and many other areas. In this article ... LIBSVM. Issues such as solving SVM optimization problems theoretical convergence multiclass classification probability estimates...
  • SVMlight

  • Referenced in 268 articles [sw04076]
  • problem of learning a ranking function. The optimization algorithms used in SVMlight are described ... this version is an algorithm for learning ranking functions [Joachims, 2002c]. The goal ... learn a function from preference examples, so that it orders a new set of objects ... algorithm proceeds by solving a sequence of optimization problems lower-bounding the solution using...
  • SMAC

  • Referenced in 80 articles [sw27215]
  • very effective for the hyperparameter optimization of machine learning algorithms, scaling better to high dimensions...
  • YALMIP

  • Referenced in 1063 articles [sw04595]
  • free MATLAB toolbox for rapid prototyping of optimization problems. The package initially aimed ... entirely based on MATLAB code. Easy to learn : 3 new commands is all the user...
  • LVQ_PAK

  • Referenced in 30 articles [sw12122]
  • developed for convenient and effective application of learning vector quantization algorithms, is presented ... into the class zones and the optimized-learning-rate algorithm OLVQ1...
  • Wasserstein GAN

  • Referenced in 159 articles [sw42583]
  • learning curves useful for debugging and hyperparameter searches. Furthermore, we show that the corresponding optimization...
  • OP-ELM

  • Referenced in 22 articles [sw12171]
  • optimally pruned extreme learning machine. In this brief, the optimally pruned extreme learning machine...
  • CMA-ES

  • Referenced in 124 articles [sw05063]
  • linear or non-convex continuous optimization problems. They belong to the class of evolutionary algorithms ... Adaptation of the covariance matrix amounts to learning a second order model of the underlying ... Quasi-Newton method in classical optimization. In contrast to most classical methods, fewer assumptions ... ranking between candidate solutions is exploited for learning the sample distribution and neither derivatives...
  • XGBoost

  • Referenced in 139 articles [sw21035]
  • XGBoost is an optimized distributed gradient boosting library designed to be highly efficient, flexible ... portable. It implements machine learning algorithms under the Gradient Boosting framework. XGBoost provides a parallel...
  • auto-sklearn

  • Referenced in 27 articles [sw33039]
  • algorithm for a new machine learning dataset and optimizes its hyperparameters. Thus, it frees...
  • Manopt

  • Referenced in 124 articles [sw08493]
  • design efficient numerical algorithms. In particular, optimization on manifolds is well-suited to deal with ... Such structured constraints appear pervasively in machine learning applications, including low-rank matrix completion, sensor ... camera network registration, independent component analysis, metric learning, dimensionality reduction and so on. The Manopt ... experimenting with state of the art Riemannian optimization algorithms. We aim particularly at reaching practitioners...
  • glasso

  • Referenced in 510 articles [sw07432]
  • graphical lasso [5] is an algorithm for learning the structure in an undirected Gaussian graphical ... block-coordinate descent, where Θ is the optimization target. We study all of these algorithms...
  • ARock

  • Referenced in 32 articles [sw16800]
  • ARock for linear systems, convex optimization, and machine learning, as well as distributed and decentralized...
  • top88.m

  • Referenced in 80 articles [sw22631]
  • efficient 88 line MATLAB code for topology optimization. It has been developed using ... ease the learning curve for those entering the field of topology optimization. The paper also...
  • SimpleMKL

  • Referenced in 69 articles [sw12290]
  • combinations. Apart from learning the combination, we solve a standard SVM optimization problem, where...
  • OpenCV

  • Referenced in 117 articles [sw11376]
  • open source computer vision and machine learning software library. OpenCV was built to provide ... code. The library has more than 2500 optimized algorithms, which includes a comprehensive ... computer vision and machine learning algorithms. These algorithms can be used to detect and recognize...
  • Auto-WEKA

  • Referenced in 37 articles [sw21536]
  • hyperparameter optimization in WEKA. WEKA is a widely used, open-source machine learning platform ... through the joint space of WEKA’s learning algorithms and their respective hyperparameter settings ... using a state-of-the-art Bayesian optimization method. Our new package is tightly integrated ... accessible to end users as any other learning algorithm...
  • POT

  • Referenced in 28 articles [sw30675]
  • problems related to Optimal Transport for signal, image processing and machine learning...
  • evtree

  • Referenced in 12 articles [sw14304]
  • evtree: Evolutionary Learning of Globally Optimal Trees. Commonly used classification and regression tree methods like ... package implements an evolutionary algorithm for learning globally optimal classification and regression trees...