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 1026–1050 of 1387 papers

TitleStatusHype
Variance-Reduced Splitting Schemes for Monotone Stochastic Generalized Equations—0
Variance reduced stochastic optimization over directed graphs with row and column stochastic weights—0
Variance Reduction and Low Sample Complexity in Stochastic Optimization via Proximal Point Method—0
Variance Reduction for Distributed Stochastic Gradient Descent—0
Variance Regularization for Accelerating Stochastic Optimization—0
Variational Bayesian Inference with Stochastic Search—0
Variational Inference MPC for Bayesian Model-based Reinforcement Learning—0
Variational Nearest Neighbor Gaussian Process—0
Variational Wasserstein Barycenters with c-Cyclical Monotonicity—0
Traversing the noise of dynamic mini-batch sub-sampled loss functions: A visual guide—0
Wasserstein Distributionally Robust Optimization and Variation Regularization—0
Weakly-supervised Multi-output Regression via Correlated Gaussian Processes—0
Weighted Aggregating Stochastic Gradient Descent for Parallel Deep Learning—0
Weighted parallel SGD for distributed unbalanced-workload training system—0
"What are my options?": Explaining RL Agents with Diverse Near-Optimal Alternatives (Extended)—0
When can we improve on sample average approximation for stochastic optimization?—0
When Does Stochastic Gradient Algorithm Work Well?—0
Low-Complexity Algorithm for Restless Bandits with Imperfect Observations—0
Without-Replacement Sampling for Stochastic Gradient Methods: Convergence Results and Application to Distributed Optimization—0
Without-Replacement Sampling for Stochastic Gradient Methods—0
You Only Accept Samples Once: Fast, Self-Correcting Stochastic Variational Inference—0
Zero-Order One-Point Estimate with Distributed Stochastic Gradient-Tracking Technique—0
Zeroth-Order Algorithms for Nonconvex Minimax Problems with Improved Complexities—0
Zeroth-Order Hard-Thresholding: Gradient Error vs. Expansivity—0
Zeroth-order (Non)-Convex Stochastic Optimization via Conditional Gradient and Gradient Updates—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