Pages that link to "Item:Q4643371"

The following pages link to Non-convex Optimization for Machine Learning (Q4643371):

Displaying 50 items.

• Measuring the local non-convexity of real algebraic curves (Q820982) (← links)
• Inertial proximal gradient methods with Bregman regularization for a class of nonconvex optimization problems (Q2022322) (← links)
• On the geometric analysis of a quartic-quadratic optimization problem under a spherical constraint (Q2089778) (← links)
• Proximal ADMM for nonconvex and nonsmooth optimization (Q2097703) (← links)
• Provably training overparameterized neural network classifiers with non-convex constraints (Q2106783) (← links)
• A unified Douglas-Rachford algorithm for generalized DC programming (Q2114583) (← links)
• Finding the global optimum of a class of quartic minimization problem (Q2114839) (← links)
• Machine learning algorithms of relaxation subgradient method with space extension (Q2117655) (← links)
• A Bayesian perspective of statistical machine learning for big data (Q2203387) (← links)
• Parametric deep energy approach for elasticity accounting for strain gradient effects (Q2246296) (← links)
• A deep energy method for finite deformation hyperelasticity (Q2292258) (← links)
• Stable and robust LQR design via scenario approach (Q2665078) (← links)
• Nonsmooth rank-one matrix factorization landscape (Q2673521) (← links)
• The exact worst-case convergence rate of the gradient method with fixed step lengths for \(L\)-smooth functions (Q2673524) (← links)
• A backward SDE method for uncertainty quantification in deep learning (Q2676245) (← links)
• Zeroth-order nonconvex stochastic optimization: handling constraints, high dimensionality, and saddle points (Q2696568) (← links)
• A quasi-Newton approach to nonsmooth convex optimization problems in machine learning (Q2896073) (← links)
• Systems of Bounded Rational Agents with Information-Theoretic Constraints (Q3379603) (← links)
• A Newton-Based Method for Nonconvex Optimization with Fast Evasion of Saddle Points (Q4620423) (← links)
• A Finite Time Analysis of Temporal Difference Learning with Linear Function Approximation (Q5003727) (← links)
• An inertial proximal alternating direction method of multipliers for nonconvex optimization (Q5031320) (← links)
• A Nonlinear Matrix Decomposition for Mining the Zeros of Sparse Data (Q5070506) (← links)
• Low-rank, Orthogonally Decomposable Tensor Regression With Application to Visual Stimulus Decoding of fMRI Data (Q5083366) (← links)
• Exact Recovery of Multichannel Sparse Blind Deconvolution via Gradient Descent (Q5143310) (← links)
• Learning Enabled Constrained Black-Box Optimization (Q5153491) (← links)
• (Q5159422) (← links)
• Optimization with Non-Differentiable Constraints with Applications to Fairness, Recall, Churn, and Other Goals (Q5214272) (← links)
• Sublinear optimization for machine learning (Q5395692) (← links)
• A combined dictionary learning and TV model for image restoration with convergence analysis (Q5855717) (← links)
• Bilevel Methods for Image Reconstruction (Q5870782) (← links)
• Orientation estimation of cryo-EM images using projected gradient descent method (Q5885761) (← links)
• Nonlinear optimization and support vector machines (Q5915690) (← links)
• Nonlinear optimization and support vector machines (Q5918754) (← links)
• Sharp global convergence guarantees for iterative nonconvex optimization with random data (Q6046308) (← links)
• CoolPINNs: a physics-informed neural network modeling of active cooling in vascular systems (Q6072827) (← links)
• Optimal control under nonconvexity: A generalized Hamiltonian approach (Q6081039) (← links)
• A unified analysis of stochastic gradient‐free Frank–Wolfe methods (Q6092499) (← links)
• Nested alternating minimization with FISTA for non-convex and non-smooth optimization problems (Q6145059) (← links)
• High-dimensional low-rank tensor autoregressive time series modeling (Q6152591) (← links)
• An integrated design method for active fault diagnosis and control (Q6152767) (← links)
• Tail probability estimates of continuous-time simulated annealing processes (Q6164089) (← links)
• First-order methods for convex optimization (Q6169988) (← links)
• Assessing Monotonicity: An Approach Based on Transformed Order Statistics (Q6497056) (← links)
• Graphmax for text generation (Q6535428) (← links)
• Joint learning of linear time-invariant dynamical systems (Q6550232) (← links)
• On fluorophore imaging by nonlinear diffusion model with dynamical iterative scheme (Q6567018) (← links)
• Optimization in machine learning: a distribution-space approach (Q6575304) (← links)
• Extrapolated plug-and-play three-operator splitting methods for nonconvex optimization with applications to image restoration (Q6587639) (← links)
• Exterior-point optimization for sparse and low-rank optimization (Q6608755) (← links)
• Robust singular value decomposition with application to video surveillance background modelling (Q6643209) (← links)