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- CPSC 540: Machine Learning Rates of Convergence
- Method of Conjugate Gradients
- The Linear Convergence of a Successive Linear Programming
- 1. Gradient Method
- Iterative Methods for Optimization C.T. Kelley
- ECS289: Scalable Machine Learning
- Incremental Aggregated Proximal and Augmented Lagrangian Algorithms
- Lagrangian Decomposition for Neural Network Verification
- Mathematical Optimization Techniques
- 1 Gradient-Based Optimization
- Accelerating Greedy Coordinate Descent Methods
- An Introduction to the Conjugate Gradient Method Without the Agonizing Pain 1 Edition 1 4 Jonathan Richard Shewchuk August 4, 1994
- Gradient Estimation Based Directions and Its Use As a Local Search Operator in Evolutionary Algorithms
- A Scaled Gradient Descent Method for Unconstrained Optimiziation Problems with a Priori Estimation of the Minimum Value a SCALED GRADIENT DESCENT METHOD FOR
- Applying the Truncated Newton Method to Anacoustic
- An Ellipsoidal Branch and Bound Algorithm for Global Optimization∗
- Augmented Lagrangian Methods for Convex Optimization
- A Comparison of Backpropagation And
- Luenberger/ LINEAR and NONLINEAR PROGRAMMING, 2Nd Ed
- Accelerated Backpropagation Learning: Two Optimization Methods
- An Algorithm for Nonlinear Optimization Using Linear Programming and Equality Constrained Subproblems
- Accelerated Stochastic Block Coordinate Descent with Optimal Sampling
- Training Feed-Forward Neural Networks Using the Gradient Descent Method with the Optimal Stepsize
- Iterative Methods to Solve Linear Systems, Steepest Descent
- Large-Scale Numerical Optimization Notes 9: Augmented Lagrangian Methods 1 Origins
- Metaheuristic Design of Feedforward Neural Networks: a Review of Two Decades of Research Arxiv:1705.05584V1 [Cs.NE] 16 May
- A Brief Introduction to the Conjugate Gradient Method
- Gradient Descent
- First-Order Augmented Lagrangian Methods for State Constraint Problems
- Gradient Methods for Large Scale Nonlinear Optimization
- 3 Gradient Descent Method
- Metaheuristic Optimization Tool
- Counting Basis of Matroids Via Entropy Maximization
- Gradient Methods for Submodular Maximization
- Truncated-Newton Training Algorithm for Neurocomputational Viscoplastic Model
- The Conjugate Gradient Method for Solving Linear Systems of Equations
- A Survey of Gradient Methods for Solving Nonlinear Optimization
- Properties of the Sign Gradient Descent Algorithms Emmanuel Moulay, Vincent Léchappé, Franck Plestan
- The Proximal Gradient Method
- Full Waveform Inversion and the Truncated Newton Method Ludovic Métivier, Romain Brossier, Jean Virieux, Stéphane Operto
- A Branch and Bound Algorithm for Nonconvex Quadratic Optimization with Ball and Linear Constraints
- Application and Comparison of Metaheuristic and New Metamodel Based Global Optimization Methods to the Optimal Operation of Active Distribution Networks
- Deterministic Approximation for Submodular Maximization Over a Matroid in Nearly Linear Time
- Conditional Gradient Method for Stochastic Submodular Maximization: Closing the Gap
- From Machine Learning to Signal Processing Applications
- Conjugate Gradient Method from Wikipedia, the Free Encyclopedia
- The Gradient Evolution Algorithm: a New Metaheuristic ⇑ R.J
- Arxiv:1804.09554V2 [Math.OC] 12 Nov 2018
- Rebier Updates for Training Feed Forward Neural Network Abstract
- Adaptive Natural Gradient Method for Learning of Stochastic Neural Networks in Mini-Batch Mode
- A Conditional-Gradient-Based Augmented Lagrangian Framework
- An Accelerated Gradient Method for Trace Norm Minimization
- A Survey of Truncated-Newton Methods
- An Accelerated Proximal Coordinate Gradient Method
- 10. Augmented Lagrangian, Alternating Direction Multiplier Method
- Coordinate Descent and Ascent Methods
- Optimization for Approximate Submodularity