SOTAVerified

Stochastic Optimization

Stochastic Optimization is the task of optimizing certain objective functional by generating and using stochastic random variables. Usually the Stochastic Optimization is an iterative process of generating random variables that progressively finds out the minima or the maxima of the objective functional. Stochastic Optimization is usually applied in the non-convex functional spaces where the usual deterministic optimization such as linear or quadratic programming or their variants cannot be used.

Source: ASOC: An Adaptive Parameter-free Stochastic Optimization Techinique for Continuous Variables

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1051–1100 of 1387 papers

TitleStatusHype
Zeroth-order Nonconvex Stochastic Optimization: Handling Constraints, High-Dimensionality and Saddle-Points—0
Zeroth-order Riemannian Averaging Stochastic Approximation Algorithms—0
Zeroth-order Stochastic Compositional Algorithms for Risk-Aware Learning—0
Stochastic Optimization with Non-stationary Noise: The Power of Moment Estimation—0
Using Statistics to Automate Stochastic Optimization—0
Convergence rates for the Adam optimizer—0
Efficient End-to-End Learning for Decision-Making: A Meta-Optimization Approach—0
A Latent Variational Framework for Stochastic Optimization—0
A Bias-Correction Decentralized Stochastic Gradient Algorithm with Momentum Acceleration—0
Accelerated Gradient Methods for Stochastic Optimization and Online Learning—0
Accelerated Mini-batch Randomized Block Coordinate Descent Method—0
Accelerated, Optimal, and Parallel: Some Results on Model-Based Stochastic Optimization—0
Accelerated Parameter-Free Stochastic Optimization—0
Accelerated Randomized Coordinate Descent Algorithms for Stochastic Optimization and Online Learning—0
Accelerated Reinforcement Learning—0
Accelerate Stochastic Subgradient Method by Leveraging Local Growth Condition—0
Accelerated zero-order SGD under high-order smoothness and overparameterized regime—0
Accelerate RNN-based Training with Importance Sampling—0
Practical Operator Sketching Framework for Accelerating Iterative Data-Driven Solutions in Inverse Problems—0
Accelerating Distributed Stochastic Optimization via Self-Repellent Random Walks—0
Accelerating first order optimization algorithms—0
Accelerating First-Order Optimization Algorithms—0
Accelerating Minibatch Stochastic Gradient Descent using Typicality Sampling—0
Accelerating SGD for Distributed Deep-Learning Using Approximated Hessian Matrix—0
Accelerating Stochastic Gradient Descent For Least Squares Regression—0
Accelerating Stochastic Probabilistic Inference—0
Accurate Neural Network Pruning Requires Rethinking Sparse Optimization—0
A Class of Short-term Recurrence Anderson Mixing Methods and Their Applications—0
A Communication-Efficient Adaptive Algorithm for Federated Learning under Cumulative Regret—0
A Communication Efficient Stochastic Multi-Block Alternating Direction Method of Multipliers—0
A Comparison of Monte Carlo Tree Search and Mathematical Optimization for Large Scale Dynamic Resource Allocation—0
A Computational Efficient Pumped Storage Hydro Optimization in the Look-ahead Unit Commitment and Real-time Market Dispatch Under Uncertainty—0
A Continuous-time Stochastic Gradient Descent Method for Continuous Data—0
A Convergence Analysis for A Class of Practical Variance-Reduction Stochastic Gradient MCMC—0
A Coreset-based, Tempered Variational Posterior for Accurate and Scalable Stochastic Gaussian Process Inference—0
Adam^+: A Stochastic Method with Adaptive Variance Reduction—0
On the Trend-corrected Variant of Adaptive Stochastic Optimization Methods—0
Adaptive First- and Second-Order Algorithms for Large-Scale Machine Learning—0
Adaptive First-and Zeroth-order Methods for Weakly Convex Stochastic Optimization Problems—0
Adaptive Importance Sampling for Finite-Sum Optimization and Sampling with Decreasing Step-Sizes—0
Adaptive Learning Rates for Faster Stochastic Gradient Methods—0
Adaptive Learning Rate via Covariance Matrix Based Preconditioning for Deep Neural Networks—0
Adaptive Online Estimation of Piecewise Polynomial Trends—0
Adaptive Sampling Quasi-Newton Methods for Derivative-Free Stochastic Optimization—0
Adaptive Sampling Quasi-Newton Methods for Zeroth-Order Stochastic Optimization—0
Adaptive Sampling Strategies for Stochastic Optimization—0
Adaptive Sequential Machine Learning—0
Adaptive Shells for Efficient Neural Radiance Field Rendering—0
Adaptive Single-Pass Stochastic Gradient Descent in Input Sparsity Time—0
Adaptive Step Sizes for Preconditioned Stochastic Gradient Descent—0
Show:102550
← PrevPage 22 of 28Next →
All datasetsCIFAR-100 WRN-28-10 - 200 EpochsCIFAR-10 WRN-28-10 - 200 EpochsCIFAR-10 ResNet-18 - 200 EpochsImageNet ResNet-50 - 90 EpochsPenn Treebank (Character Level) 3x1000 LSTM - 500 EpochsCIFAR-10CIFAR-100ImageNet ResNet-50 - 50 EpochsImageNet ResNet-50 - 60 EpochsAG NewsCoLAMNIST

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1AvaGradAccuracy81.24—Unverified
2AdaShiftAccuracy81.12—Unverified
3Adam (eps-adjusted)Accuracy81.04—Unverified
4SGDAccuracy80.95—Unverified
5AdamWAccuracy79.87—Unverified
6AdaBoundAccuracy77.24—Unverified
#ModelMetricClaimedVerifiedStatus
1Adam (eps-adjusted)Accuracy96.36—Unverified
2AvaGradAccuracy96.2—Unverified
3SGDAccuracy96.14—Unverified
4AdaShiftAccuracy95.92—Unverified
5AdamWAccuracy95.89—Unverified
6AdaBoundAccuracy94.6—Unverified
#ModelMetricClaimedVerifiedStatus
1SGD - cosine LR scheduleAccuracy95.55—Unverified
2LookaheadAccuracy95.27—Unverified
3SGDAccuracy95.23—Unverified
4ADAMAccuracy94.84—Unverified
#ModelMetricClaimedVerifiedStatus
1AvaGradTop 1 Accuracy76.51—Unverified
2SGDTop 1 Accuracy75.99—Unverified
3AdamWTop 1 Accuracy72.9—Unverified
4AdaBoundTop 1 Accuracy72.01—Unverified
#ModelMetricClaimedVerifiedStatus
1AdaBoundBit per Character (BPC)2.86—Unverified
2AdaShiftBit per Character (BPC)1.27—Unverified
3AdamWBit per Character (BPC)1.23—Unverified
4AvaGradBit per Character (BPC)1.18—Unverified
#ModelMetricClaimedVerifiedStatus
1Resnet18Accuracy (max)86.85—Unverified
2Resnet34Accuracy (max)86.14—Unverified
#ModelMetricClaimedVerifiedStatus
1Resnet18Accuracy (max)58.48—Unverified
2Resnet34Accuracy (max)54.5—Unverified
#ModelMetricClaimedVerifiedStatus
1SGDTop 5 Accuracy92.15—Unverified
2LookaheadTop 1 Accuracy75.13—Unverified
#ModelMetricClaimedVerifiedStatus
1LookaheadTop 1 Accuracy75.49—Unverified
2SGDTop 1 Accuracy75.15—Unverified
#ModelMetricClaimedVerifiedStatus
1BertAccuracy (max)93.99—Unverified
#ModelMetricClaimedVerifiedStatus
1BertAccuracy (max)86.34—Unverified
#ModelMetricClaimedVerifiedStatus
1MLPNLL0.05—Unverified