• Referenced in 166 articles [sw22202]
• # PESTO

• Referenced in 36 articles [sw20864]
• those performing explicit, projected, proximal, conditional and inexact (sub)gradient steps. We simultaneously obtain tight ... proximal point algorithm and of several variants of fast proximal gradient, conditional gradient, subgradient ... analytical worst-case guarantee for the proximal point algorithm that is twice better than previously ... projection or a proximal operator, which leads to an algorithm that converges in the worst...
• # Saga

• Referenced in 104 articles [sw39677]
• recently proposed incremental gradient algorithms with fast linear convergence rates. SAGA improves on the theory ... support for composite objectives where a proximal operator is used on the regulariser. Unlike SDCA...
• # SLEP

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

• Referenced in 68 articles [sw09623]
• inertial proximal algorithm for nonconvex optimization. In this paper we study an algorithm for solving ... convex (possibly nondifferentiable) function. The algorithm iPiano combines forward-backward splitting with an inertial force ... from Polyak. A rigorous analysis of the algorithm for the proposed class of problems yields ... values and the arguments. This makes the algorithm robust for usage on nonconvex problems...
• # ParNes

• Referenced in 12 articles [sw08366]
• convergent. As in the case of the algorithm nesta, proposed by Becker, Bobin, and Cand ... rely on Nesterov’s accelerated proximal gradient method, which takes $O(sqrt {1/varepsilon })$ iterations ... Friedlander in their spgl1 solver. The resulting algorithm is called parnes. We provide numerical evidence...
• # SVR-AMA

• Referenced in 1 article [sw29521]
• asynchronous alternating minimization algorithm with variance reduction for model predictive control applications. This paper focuses ... proximal stochastic gradient methods (Prox-SVRG) and on the alternating minimization algorithm (AMA). The resultant...
• # RMTL

• Referenced in 1 article [sw41670]
• 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 ... develop a novel meta-learning algorithm that overcomes both the issue of poor credit assignment...
• # PredictPDPS.jl

• Referenced in 1 article [sw39172]
• video frames now exactly correspond to the algorithm iterations. A user-prescribed predictor describes ... dual variable based on (proximal) gradient flow. This affects the model that the method asymptotically...
• # IQC-Game

• Referenced in 1 article [sw39462]
• sharper bounds for the proximal point method (PPM) and optimistic gradient method (OG), and provide ... time-varying systems, we prove that the gradient method with optimal step size achieves ... impact of multiplicative noise on different algorithms. We show that it is impossible...
• # SINE

• Referenced in 1 article [sw32344]
• often exhibit high correlation, incorporating node attribute proximity into network embedding is beneficial for learning ... linkages, yet existing attributed network embedding algorithms all operate under the assumption that networks ... propose a Scalable Incomplete Network Embedding (SINE) algorithm for learning node representations from incomplete graphs ... relationships. Different from existing attributed network embedding algorithms, SINE provides greater flexibility to make...