Pages that link to "Item:Q5405113"

The following pages link to Optimal Distributed Online Prediction using Mini-Batches (Q5405113):

Displaying 41 items.

• Distributed prediction from vertically partitioned data (Q436642) (← links)
• A sparsity preserving stochastic gradient methods for sparse regression (Q457215) (← links)
• Distributed learning for random vector functional-link networks (Q528749) (← links)
• Sample size selection in optimization methods for machine learning (Q715253) (← links)
• Feature-aware regularization for sparse online learning (Q893629) (← links)
• Consensus-based modeling using distributed feature construction with ILP (Q1640573) (← links)
• Stochastic variance-reduced prox-linear algorithms for nonconvex composite optimization (Q2089785) (← links)
• Stochastic gradient descent for semilinear elliptic equations with uncertainties (Q2127008) (← links)
• Distributed optimization and statistical learning for large-scale penalized expectile regression (Q2131987) (← links)
• Multi-round smoothed composite quantile regression for distributed data (Q2164793) (← links)
• Vaidya's method for convex stochastic optimization problems in small dimension (Q2170511) (← links)
• A modular analysis of adaptive (non-)convex optimization: optimism, composite objectives, variance reduction, and variational bounds (Q2290691) (← links)
• Accelerating deep neural network training with inconsistent stochastic gradient descent (Q2292210) (← links)
• On the convergence analysis of asynchronous SGD for solving consistent linear systems (Q2685380) (← links)
• Communication-efficient sparse composite quantile regression for distributed data (Q2696327) (← links)
• On the parallelization upper bound for asynchronous stochastic gradients descent in non-convex optimization (Q2696976) (← links)
• Efficient online and batch learning using forward backward splitting (Q2880998) (← links)
• Revisiting EXTRA for Smooth Distributed Optimization (Q3300767) (← links)
• Likelihood Inference for Large Scale Stochastic Blockmodels With Covariates Based on a Divide-and-Conquer Parallelizable Algorithm With Communication (Q3391269) (← links)
• (Q4558562) (← links)
• (Q4558572) (← links)
• Batched Stochastic Gradient Descent with Weighted Sampling (Q4609808) (← links)
• (Q4633055) (← links)
• (Q4637006) (← links)
• Optimal Rates for Multi-pass Stochastic Gradient Methods (Q4637012) (← links)
• Harder, Better, Faster, Stronger Convergence Rates for Least-Squares Regression (Q4637017) (← links)
• Linear Coupling: An Ultimate Unification of Gradient and Mirror Descent (Q4638051) (← links)
• Random Gradient Extrapolation for Distributed and Stochastic Optimization (Q4687240) (← links)
• Graph-Dependent Implicit Regularisation for Distributed Stochastic Subgradient Descent (Q4969072) (← links)
• MultiLevel Composite Stochastic Optimization via Nested Variance Reduction (Q4987278) (← links)
• Online Learning of a Weighted Selective Naive Bayes Classifier with Non-convex Optimization (Q5016640) (← links)
• (Q5053207) (← links)
• Quantile-Based Iterative Methods for Corrupted Systems of Linear Equations (Q5071437) (← links)
• Complexity Analysis of stochastic gradient methods for PDE-constrained optimal Control Problems with uncertain parameters (Q5074382) (← links)
• (Q5149264) (← links)
• Stochastic distributed learning with gradient quantization and double-variance reduction (Q5882226) (← links)
• Unifying mirror descent and dual averaging (Q6038659) (← links)
• Semi-discrete optimal transport: hardness, regularization and numerical solution (Q6038666) (← links)
• Non-smooth setting of stochastic decentralized convex optimization problem over time-varying graphs (Q6060563) (← links)
• (Q6075951) (← links)
• Scaling up stochastic gradient descent for non-convex optimisation (Q6097095) (← links)