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 951–1000 of 1387 papers

TitleStatusHype
Teaching Models To Survive: Proper Scoring Rule and Stochastic Optimization with Competing Risks—0
Temporal Action Co-Segmentation in 3D Motion Capture Data and Videos—0
Temporal Difference Learning with Compressed Updates: Error-Feedback meets Reinforcement Learning—0
Test-Time Classifier Adjustment Module for Model-Agnostic Domain Generalization—0
The Asset Liability Management problem of a nuclear operator : a numerical stochastic optimization approach—0
The Challenge of Crafting Intelligible Intelligence—0
The Complexity of Making the Gradient Small in Stochastic Convex Optimization—0
The Devil is in the Detail: A Framework for Macroscopic Prediction via Microscopic Models—0
The Information-Collecting Vehicle Routing Problem: Stochastic Optimization for Emergency Storm Response—0
The Limitations of Model Retraining in the Face of Performativity—0
The Marginal Value of Momentum for Small Learning Rate SGD—0
The Minimax Complexity of Distributed Optimization—0
The Perils of Learning Before Optimizing—0
The Practicality of Stochastic Optimization in Imaging Inverse Problems—0
The Role of Local Steps in Local SGD—0
The Role of Memory in Stochastic Optimization—0
The Sample Complexity of Parameter-Free Stochastic Convex Optimization—0
The Wang-Landau Algorithm as Stochastic Optimization and Its Acceleration—0
Think out of the "Box": Generically-Constrained Asynchronous Composite Optimization and Hedging—0
Thinning for Accelerating the Learning of Point Processes—0
Third-order Smoothness Helps: Even Faster Stochastic Optimization Algorithms for Finding Local Minima—0
Third-order Smoothness Helps: Faster Stochastic Optimization Algorithms for Finding Local Minima—0
Thompson Sampling Guided Stochastic Searching on the Line for Deceptive Environments with Applications to Root-Finding Problems—0
Three-Dimensional Swarming Using Cyclic Stochastic Optimization—0
Tiering as a Stochastic Submodular Optimization Problem—0
Tightening Bounds for Variational Inference by Revisiting Perturbation Theory—0
Time-consistent conditional expectation under probability distortion—0
Topological Generalization Bounds for Discrete-Time Stochastic Optimization Algorithms—0
A Diffusion Approximation Theory of Momentum SGD in Nonconvex Optimization—0
Toward Neural Network Simulation of Variational Quantum Algorithms—0
Accelerating Cutting-Plane Algorithms via Reinforcement Learning Surrogates—0
Towards a Sustainable Power Grid: Stochastic Hierarchical Planning for High Renewable Integration—0
Towards Gradient Free and Projection Free Stochastic Optimization—0
Towards Machine Wald—0
Towards Optimal Problem Dependent Generalization Error Bounds in Statistical Learning Theory—0
Towards Practical Adam: Non-Convexity, Convergence Theory, and Mini-Batch Acceleration—0
Towards Practical Second Order Optimization for Deep Learning—0
Towards QD-suite: developing a set of benchmarks for Quality-Diversity algorithms—0
Towards Reliable Alignment: Uncertainty-aware RLHF—0
Towards Training Probabilistic Topic Models on Neuromorphic Multi-chip Systems—0
Towards Understanding Acceleration Tradeoff between Momentum and Asynchrony in Nonconvex Stochastic Optimization—0
Towards Understanding the Generalization of Graph Neural Networks—0
Continuous-time Riemannian SGD and SVRG Flows on Wasserstein Probabilistic Space—0
Towards Weaker Variance Assumptions for Stochastic Optimization—0
Transformer-based Stagewise Decomposition for Large-Scale Multistage Stochastic Optimization—0
Trial-Based Dominance Enables Non-Parametric Tests to Compare both the Speed and Accuracy of Stochastic Optimizers—0
Trust-Region Sequential Quadratic Programming for Stochastic Optimization with Random Models—0
Trustworthy DNN Partition for Blockchain-enabled Digital Twin in Wireless IIoT Networks—0
Tuning-Free Stochastic Optimization—0
Efficiently Training Deep-Learning Parametric Policies using Lagrangian Duality—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