Pages that link to "Item:Q4376150"
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The following pages link to A New Class of Incremental Gradient Methods for Least Squares Problems (Q4376150):
Displaying 38 items.
- A stochastic successive minimization method for nonsmooth nonconvex optimization with applications to transceiver design in wireless communication networks (Q301668) (← links)
- Minimizing finite sums with the stochastic average gradient (Q517295) (← links)
- Random algorithms for convex minimization problems (Q644912) (← links)
- Incremental proximal methods for large scale convex optimization (Q644913) (← links)
- Generalized row-action methods for tomographic imaging (Q742852) (← links)
- Communication-reducing algorithm of distributed least mean square algorithm with neighbor-partial diffusion (Q831586) (← links)
- Approximation schemes for functional optimization problems (Q1024253) (← links)
- Error stability properties of generalized gradient-type algorithms (Q1273917) (← links)
- Distributed multi-task classification: a decentralized online learning approach (Q1640564) (← links)
- On the application of iterative methods of nondifferentiable optimization to some problems of approximation theory (Q1717808) (← links)
- An incremental subgradient method on Riemannian manifolds (Q1752648) (← links)
- Steered sequential projections for the inconsistent convex feasibility problem (Q1888607) (← links)
- An incremental primal-dual method for nonlinear programming with special structure (Q1936792) (← links)
- Incremental without replacement sampling in nonconvex optimization (Q2046568) (← links)
- An adaptive Polyak heavy-ball method (Q2102380) (← links)
- Why random reshuffling beats stochastic gradient descent (Q2227529) (← links)
- Cyclic and simultaneous iterative methods to matrix equations of the form \(A_iXB_i=F_i\) (Q2249834) (← links)
- Incrementally updated gradient methods for constrained and regularized optimization (Q2251572) (← links)
- An incremental least squares algorithm for large scale linear classification (Q2253466) (← links)
- A globally convergent incremental Newton method (Q2349125) (← links)
- Parallel stochastic gradient algorithms for large-scale matrix completion (Q2392935) (← links)
- On perturbed steepest descent methods with inexact line search for bilevel convex optimization (Q3112499) (← links)
- Adaptive clustering based on element-wised distance for distributed estimation over multi-task networks (Q3303861) (← links)
- Block‐iterative algorithms (Q3563613) (← links)
- Value and Policy Function Approximations in Infinite-Horizon Optimization Problems (Q3626047) (← links)
- Projected Nonlinear Least Squares for Exponential Fitting (Q4600007) (← links)
- A cyclic iterative approach and its modified version to solve coupled Sylvester-transpose matrix equations (Q4603777) (← links)
- String-averaging incremental stochastic subgradient algorithms (Q4631774) (← links)
- Surpassing Gradient Descent Provably: A Cyclic Incremental Method with Linear Convergence Rate (Q4641666) (← links)
- The Kaczmarz algorithm, row action methods, and statistical learning algorithms (Q4686248) (← links)
- Distributed event-triggered adaptive partial diffusion strategy under dynamic network topology (Q5119443) (← links)
- A Smooth Inexact Penalty Reformulation of Convex Problems with Linear Constraints (Q5152474) (← links)
- Convergence Rate of Incremental Gradient and Incremental Newton Methods (Q5237308) (← links)
- Applications of convex separable unconstrained nonsmooth optimization to numerical approximation with respect to l<sub>1</sub>- and l<sub>∞</sub>-norms (Q5455173) (← links)
- Distributed adaptive clustering learning over time-varying multitask networks (Q6081303) (← links)
- Incremental subgradient algorithms with dynamic step sizes for separable convex optimizations (Q6140717) (← links)
- A multivariate adaptive gradient algorithm with reduced tuning efforts (Q6488713) (← links)
- Maximal residual extended Kaczmarz and Gauss-Seidel methods-convergence properties and applications (Q6569156) (← links)
