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

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Showing 901–925 of 1387 papers

TitleStatusHype
Stochastic Optimization of Inventory at Large-scale Supply Chains—0
Stochastic Optimization of PCA with Capped MSG—0
Stochastic Optimization of Smooth Loss—0
Stochastic optimization on matrices and a graphon McKean-Vlasov limit—0
Stochastic optimization under time drift: iterate averaging, step-decay schedules, and high probability guarantees—0
Stochastic Optimization with Bandit Sampling—0
Stochastic Optimization with Constraints: A Non-asymptotic Instance-Dependent Analysis—0
Stochastic Optimization with Importance Sampling—0
Stochastic Optimization with Laggard Data Pipelines—0
Stochastic optimization with momentum: convergence, fluctuations, and traps avoidance—0
Beyond Worst-Case Analysis in Stochastic Approximation: Moment Estimation Improves Instance Complexity—0
Stochastic Optimization with Optimal Importance Sampling—0
Stochastic Optimization with Variance Reduction for Infinite Datasets with Finite Sum Structure—0
Stochastic Particle Gradient Descent for Infinite Ensembles—0
Stochastic PCA with _2 and _1 Regularization—0
Stochastic Primal Dual Coordinate Method with Non-Uniform Sampling Based on Optimality Violations—0
Stochastic Proximal Algorithms for AUC Maximization—0
Stochastic Proximal Gradient Algorithm with Minibatches. Application to Large Scale Learning Models—0
Stochastic Proximal Gradient Descent for Nuclear Norm Regularization—0
Stochastic Quasi-Newton Methods for Nonconvex Stochastic Optimization—0
Stochastic Real-Time Economic Dispatch for Integrated Electric and Gas Systems Considering Uncertainty Propagation and Pipeline Leakage—0
Stochastic Recursive Variance Reduction for Efficient Smooth Non-Convex Compositional Optimization—0
Stochastic Reformulations of Linear Systems: Algorithms and Convergence Theory—0
Stochastic Saddle-Point Optimization for Wasserstein Barycenters—0
Stochastic Steffensen method—0
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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