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 701–750 of 1387 papers

TitleStatusHype
Faster Convergence on Heterogeneous Federated Edge Learning: An Adaptive Clustered Data Sharing Approach—0
Faster Eigenvector Computation via Shift-and-Invert Preconditioning—0
Faster Gradient-Free Algorithms for Nonsmooth Nonconvex Stochastic Optimization—0
Faster Rates of Convergence to Stationary Points in Differentially Private Optimization—0
Faster SGD Using Sketched Conditioning—0
Faster Stochastic Optimization with Arbitrary Delays via Asynchronous Mini-Batching—0
Faster variational inducing input Gaussian process classification—0
Fast Multi-Agent Temporal-Difference Learning via Homotopy Stochastic Primal-Dual Optimization—0
Fast Power Control Adaptation via Meta-Learning for Random Edge Graph Neural Networks—0
Fast Rates for Bandit Optimization with Upper-Confidence Frank-Wolfe—0
Fast Rates for Bandit PAC Multiclass Classification—0
Fast Rates for Exp-concave Empirical Risk Minimization—0
Fast Reinforcement Learning for Energy-Efficient Wireless Communications—0
Fast Stochastic Algorithms for Low-rank and Nonsmooth Matrix Problems—0
Fast Stochastic Policy Gradient: Negative Momentum for Reinforcement Learning—0
f-Divergence Variational Inference—0
Federated Conditional Stochastic Optimization—0
Federated Learning Using Variance Reduced Stochastic Gradient for Probabilistically Activated Agents—0
Federated Learning with Flexible Control—0
Fill-and-Spill: Deep Reinforcement Learning Policy Gradient Methods for Reservoir Operation Decision and Control—0
Finding Acceptable Parameter Regions of Stochastic Hill functions for Multisite Phosphorylation Mechanism—0
Finding Linear Structure in Large Datasets with Scalable Canonical Correlation Analysis—0
Finding Local Minima via Stochastic Nested Variance Reduction—0
RATQ: A Universal Fixed-Length Quantizer for Stochastic Optimization—0
Finite Sample Convergence Rates of Zero-Order Stochastic Optimization Methods—0
Finite-Sum Coupled Compositional Stochastic Optimization: Theory and Applications—0
Finite-Time Convergence Rates of Decentralized Stochastic Approximation with Applications in Multi-Agent and Multi-Task Learning—0
First-order methods for stochastic and finite-sum convex optimization with deterministic constraints—0
First Order Methods with Markovian Noise: from Acceleration to Variational Inequalities—0
FIS-GAN: GAN with Flow-based Importance Sampling—0
FLECS-CGD: A Federated Learning Second-Order Framework via Compression and Sketching with Compressed Gradient Differences—0
Fluid Antenna Enabled Over-the-Air Federated Learning: Joint Optimization of Positioning, Beamforming, and User Selection—0
Follow the Moving Leader in Deep Learning—0
Forecast-Driven Scenario Generation for Building Energy Management Using Stochastic Optimization—0
Forecasting Outside the Box: Application-Driven Optimal Pointwise Forecasts for Stochastic Optimization—0
Formal guarantees for heuristic optimization algorithms used in machine learning—0
Formal Uncertainty Propagation for Stochastic Dynamical Systems with Additive Noise—0
Fractal Structure and Generalization Properties of Stochastic Optimization Algorithms—0
From Gradient Clipping to Normalization for Heavy Tailed SGD—0
From Reinforcement Learning to Optimal Control: A unified framework for sequential decisions—0
Function Norms and Regularization in Deep Networks—0
Fundamental Bias in Inverting Random Sampling Matrices with Application to Sub-sampled Newton—0
Fundamental Limits of Online and Distributed Algorithms for Statistical Learning and Estimation—0
Fusion of Image Segmentation Algorithms using Consensus Clustering—0
Generalization Bounds of Surrogate Policies for Combinatorial Optimization Problems—0
Generalization Bounds using Lower Tail Exponents in Stochastic Optimizers—0
Generative AI for Lyapunov Optimization Theory in UAV-based Low-Altitude Economy Networking—0
Genetic multi-armed bandits: a reinforcement learning approach for discrete optimization via simulation—0
GeoAdaLer: Geometric Insights into Adaptive Stochastic Gradient Descent Algorithms—0
Global Convergence and Stability of Stochastic Gradient Descent—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