• AdaGrad

  • Referenced in 166 articles [sw22202]
  • earlier iterations to perform more informative gradient-based learning. Metaphorically, the adaptation allows ... online learning which employ proximal functions to control the gradient steps of the algorithm ... analyze an apparatus for adaptively modifying the proximal function, which significantly simplifies setting a learning...
  • PESTO

  • Referenced in 36 articles [sw20864]
  • those performing explicit, projected, proximal, conditional and inexact (sub)gradient steps. We simultaneously obtain tight ... obtain a tighter analysis of the proximal point algorithm ... several variants of fast proximal gradient, conditional gradient, subgradient and alternating projection methods. In particular ... fast as the standard accelerated proximal gradient method...
  • ParNes

  • Referenced in 12 articles [sw08366]
  • rely on Nesterov’s accelerated proximal gradient method, which takes $O(sqrt {1/varepsilon })$ iterations...
  • ProxSARAH

  • Referenced in 9 articles [sw35438]
  • consist of two steps: a proximal gradient and an averaging step making them different from...
  • Saga

  • Referenced in 104 articles [sw39677]
  • SVRG, a set of recently proposed incremental gradient algorithms with fast linear convergence rates. SAGA ... support for composite objectives where a proximal operator is used on the regulariser. Unlike SDCA...
  • 2EBD-HPE

  • Referenced in 15 articles [sw31879]
  • method based on the BD-hybrid proximal extra-gradient. The main contribution of the paper...
  • APG

  • Referenced in 2 articles [sw39281]
  • lightweight accelerated proximal-gradient package for matlab. Implements an Accelerated Proximal Gradient method (Nesterov...
  • SLEP

  • Referenced in 42 articles [sw13487]
  • evaluate the function value and the gradient; and thus the algorithms can handle large-scale ... methods. 3) Efficient Projection. The projection problem (proximal operator) can be solved efficiently. 4) Pathwise...
  • iPiano

  • Referenced in 68 articles [sw09623]
  • iPiano: inertial proximal algorithm for nonconvex optimization. In this paper we study an algorithm ... used to prove convergence for several other gradient methods. First, an abstract convergence theorem...
  • FarRSA

  • Referenced in 1 article [sw25237]
  • subproblem must be solved, which allow conjugate gradient or coordinate descent techniques to be employed ... updated; and (v) a reduced proximal gradient step that ensures a sufficient decrease...
  • SALES

  • Referenced in 1 article [sw31659]
  • Squares (COSALES) using Coordinate Descent and Proximal Gradient Algorithms. A coordinate descent algorithm for computing...
  • PredictPDPS.jl

  • Referenced in 1 article [sw39172]
  • dual variable based on (proximal) gradient flow. This affects the model that the method asymptotically...
  • SVR-AMA

  • Referenced in 1 article [sw29521]
  • previously used in the context of proximal stochastic gradient methods (Prox-SVRG...
  • IQC-Game

  • Referenced in 1 article [sw39462]
  • sharper bounds for the proximal point method (PPM) and optimistic gradient method (OG), and provide...
  • MDC-ELLIPSOIDs

  • Referenced in 11 articles [sw22577]
  • vector calculus, is derived as the gradient of the implicit function. The Householder transformation ... them is collinear to the surface normal. Proximity queries were also implemented to test...
  • NPPC

  • Referenced in 4 articles [sw08728]
  • cost. NPPC classifies binary patterns by the proximity ... system of linear equations by conjugate gradient method. The performance of the reformulated NPPC...
  • RMTL

  • Referenced in 1 article [sw41670]
  • network incorporation. Based on the accelerated gradient descent method, the algorithms feature a state ... structure is induced by the solving the proximal operator. The detail of the package...
  • ProMP

  • Referenced in 2 articles [sw34914]
  • ProMP: Proximal Meta-Policy Search. Credit assignment in Meta-reinforcement learning (Meta-RL) is still ... theoretical analysis of credit assignment in gradient-based Meta-RL. Building on the gained insights...
  • Inertial-SsGM

  • Referenced in 1 article [sw42307]
  • with Delayed Derivatives for Nonconvex Problems. Stochastic gradient methods (SGMs) are predominant approaches for solving ... this paper, we propose an inertial proximal SsGM for solving nonsmooth nonconvex stochastic optimization problems ... expected value of the gradient norm square, for $K$ iterations. In a distributed environment...
  • SINE

  • Referenced in 1 article [sw32344]
  • often exhibit high correlation, incorporating node attribute proximity into network embedding is beneficial for learning ... missing information on representation learning. A stochastic gradient descent based online algorithm is derived...