• mboost

  • Referenced in 67 articles [sw07331]
  • package mboost: Model-Based Boosting. Functional gradient descent algorithm (boosting) for optimizing general risk functions...
  • topopt_multi

  • Referenced in 23 articles [sw25723]
  • Allen-Cahn system and regularized projected steepest descent method. A new computational algorithm is introduced ... objective functional by the multiphase volume constrained Ginzburg-Landau energy functional. The update procedure ... gradient flow of the objective functional by a fractional step projected steepest descent method...
  • Vowpal Wabbit

  • Referenced in 12 articles [sw28398]
  • baseline being sparse gradient descent (GD) on a loss function (several are available), The code...
  • Pegasos

  • Referenced in 103 articles [sw08752]
  • contrast, previous analyses of stochastic gradient descent methods for SVMs require Ω(1/ϵ2) iterations ... while working solely on the primal objective function, though in this case the runtime does...
  • SGDR

  • Referenced in 15 articles [sw30752]
  • Stochastic Gradient Descent with Warm Restarts. Restart techniques are common in gradient-free optimization ... deal with multimodal functions. Partial warm restarts are also gaining popularity in gradient-based optimization ... functions. In this paper, we propose a simple warm restart technique for stochastic gradient descent...
  • MBT-optimizer

  • Referenced in 2 articles [sw41981]
  • Backtracking gradient descent method for general C1 functions, with applications to Deep Learning. While Standard ... gradient descent is one very popular optimisation method, its convergence cannot be proven beyond ... class of functions whose gradient is globally Lipschitz continuous. As such, it is not actually ... function, and {zn} a sequence constructed from the Backtracking gradient descent algorithm. (1) Either limn...
  • bst

  • Referenced in 1 article [sw25766]
  • package bst: Gradient Boosting. Functional gradient descent algorithm for a variety of convex...
  • EEBoost

  • Referenced in 1 article [sw26353]
  • modification of the standard boosting (or functional gradient descent) technique. We show that EEBoost...
  • neural-tangents

  • Referenced in 5 articles [sw39529]
  • study gradient descent training dynamics of wide but finite networks in either function space...
  • Entropy-SGD

  • Referenced in 20 articles [sw41231]
  • Entropy-SGD: Biasing Gradient Descent Into Wide Valleys. This paper proposes a new optimization algorithm ... construct a local-entropy-based objective function that favors well-generalizable solutions lying in large ... inner loop to compute the gradient of the local entropy before each update...
  • OPTool

  • Referenced in 2 articles [sw33218]
  • iterative optimization algorithms for differentiable cost functions is scattered throughout the literature, which hinders their ... software for the various gradient-descent-based algorithms and implements functions to return the optimal...
  • ziphsmm

  • Referenced in 1 article [sw41964]
  • minimizing the negative log likelihood function using the gradient descent algorithm. Multiple starting values should...
  • ACGSSV

  • Referenced in 11 articles [sw20836]
  • very well known acceleration scheme of conjugate gradient algorithms. The global convergence of the algorithm ... both for uniformly convex and general nonlinear functions under the exact or the Wolfe line ... substantially outperform the CG-DESCENT, SCALCG, and CONMIN conjugate gradient algorithms, being more efficient...
  • automl

  • Referenced in 3 articles [sw32865]
  • with gradient descent or metaheuristic, using automatic hyper parameters tuning and custom cost function...
  • deepNN

  • Referenced in 1 article [sw38663]
  • multilayer perceptron, different activation functions, regularisation strategies, stochastic gradient descent and dropout. Thanks...
  • Jensen

  • Referenced in 1 article [sw26651]
  • convex (or loss) functions, convex optimization algorithms (including Gradient Descent, L-BFGS, Stochastic Gradient Descent ... build upon this by integrating new loss functions and optimization algorithms...
  • LSGA

  • Referenced in 1 article [sw02836]
  • sequence of parameters of a level-set function. Each chromosome represents a unique segmenting contour ... segmentation methods typically perform gradient descent minimization on an energy function to deform a segmenting...
  • DeepTrack

  • Referenced in 2 articles [sw27576]
  • introduce a novel truncated structural loss function that maintains as many training samples as possible ... Second, we enhance the ordinary Stochastic Gradient Descent approach in CNN training with a robust...
  • Levenberg-Marquardt

  • Referenced in 0 articles [sw05284]
  • Marquardt Method is recommended, if such a function ... steepest descent method (that is, minimization along the direction of the gradient) with the Newton ... function). This algorithm obtained its operating stability from the steepest descent method, and adopted...
  • GMBL

  • Referenced in 1 article [sw40704]
  • constraints to accumulate into a (differentiable) loss function. A GMBL program induces a (usually) tractable ... that we can solve reliably using gradient descent. Of the 39 geometry problems since...