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 876–900 of 1387 papers

TitleStatusHype
Memory and Communication Efficient Distributed Stochastic Optimization with Minibatch-Prox—0
Memory-Driven Metaheuristics: Improving Optimization Performance—0
Memory-Efficient 4-bit Preconditioned Stochastic Optimization—0
MESS+: Energy-Optimal Inferencing in Language Model Zoos with Service Level Guarantees—0
META-STORM: Generalized Fully-Adaptive Variance Reduced SGD for Unbounded Functions—0
Microscopic Advances with Large-Scale Learning: Stochastic Optimization for Cryo-EM—0
MindFlayer SGD: Efficient Parallel SGD in the Presence of Heterogeneous and Random Worker Compute Times—0
Minimizing AoI in Resource-Constrained Multi-Source Relaying Systems with Stochastic Arrivals—0
Minimum Cost Adaptive Submodular Cover—0
Min-Max Optimization under Delays—0
MixedGrad: An O(1/T) Convergence Rate Algorithm for Stochastic Smooth Optimization—0
Mixed Optimization for Smooth Functions—0
Mixing of Stochastic Accelerated Gradient Descent—0
mL-BFGS: A Momentum-based L-BFGS for Distributed Large-Scale Neural Network Optimization—0
Modeling Realistic Degradations in Non-blind Deconvolution—0
Modeling Stochastic Microscopic Traffic Behaviors: a Physics Regularized Gaussian Process Approach—0
Model Predictive Control-Based Battery Scheduling and Incentives to Manipulate Demand Response Baselines—0
Momentum Accelerates the Convergence of Stochastic AUPRC Maximization—0
Momentum and Stochastic Momentum for Stochastic Gradient, Newton, Proximal Point and Subspace Descent Methods—0
Momentum-based variance-reduced proximal stochastic gradient method for composite nonconvex stochastic optimization—0
Momentum Provably Improves Error Feedback!—0
Movable Antenna-Aided Federated Learning with Over-the-Air Aggregation: Joint Optimization of Positioning, Beamforming, and User Selection—0
Multi-Level Composite Stochastic Optimization via Nested Variance Reduction—0
Multi-level Monte-Carlo Gradient Methods for Stochastic Optimization with Biased Oracles—0
Multilevel Monte Carlo Variational Inference—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