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 601–650 of 1387 papers

TitleStatusHype
Improved Binary Forward Exploration: Learning Rate Scheduling Method for Stochastic Optimization—0
Improved Dropout for Shallow and Deep Learning—0
Improved Langevin Monte Carlo for stochastic optimization via landscape modification—0
Improved Learning Rates for Stochastic Optimization: Two Theoretical Viewpoints—0
Improved Optimization of Finite Sums with Minibatch Stochastic Variance Reduced Proximal Iterations—0
Improving Offline Contextual Bandits with Distributional Robustness—0
Improving the Sample and Communication Complexity for Decentralized Non-Convex Optimization: A Joint Gradient Estimation and Tracking Approach—0
Improving the Sample and Communication Complexity for Decentralized Non-Convex Optimization: Joint Gradient Estimation and Tracking—0
Continuous and Discrete-time Accelerated Stochastic Mirror Descent for Strongly Convex Functions—0
Incorporating statistical model error into the calculation of acceptability prices of contingent claims—0
Inefficiency of K-FAC for Large Batch Size Training—0
Inexact SARAH Algorithm for Stochastic Optimization—0
Information-Theoretic Generalization Bounds for Stochastic Gradient Descent—0
Integrated Optimization of Predictive and Prescriptive Tasks—0
From Gradient Clipping to Normalization for Heavy Tailed SGD—0
Integrating prediction in mean-variance portfolio optimization—0
Learning to Optimize Contextually Constrained Problems for Real-Time Decision-Generation—0
An Empirical Study of Large-Batch Stochastic Gradient Descent with Structured Covariance Noise—0
Identifying Cognitive Radars -- Inverse Reinforcement Learning using Revealed Preferences—0
IRS-aided Large-Scale MIMO Systems with Passive Constant Envelope Precoding—0
Is Stochastic Gradient Descent Effective? A PDE Perspective on Machine Learning processes—0
An adaptive stochastic optimization algorithm for resource allocation—0
Joint Client Scheduling and Resource Allocation under Channel Uncertainty in Federated Learning—0
Joint Ground and Aerial Package Delivery Services: A Stochastic Optimization Approach—0
Joint Optimization of Production and Maintenance in Offshore Wind Farms: Balancing the Short- and Long-Term Needs of Wind Energy Operation—0
Joint Training of Generic CNN-CRF Models with Stochastic Optimization—0
KOALA: A Kalman Optimization Algorithm with Loss Adaptivity—0
Convergence of adaptive algorithms for constrained weakly convex optimization—0
Katyusha Acceleration for Convex Finite-Sum Compositional Optimization—0
Katyusha: The First Direct Acceleration of Stochastic Gradient Methods—0
Stochastic Learning of Semiparametric Monotone Index Models with Large Sample Size—0
A New Random Reshuffling Method for Nonsmooth Nonconvex Finite-sum Optimization—0
Convergence of SGD with momentum in the nonconvex case: A time window-based analysis—0
KKT Conditions, First-Order and Second-Order Optimization, and Distributed Optimization: Tutorial and Survey—0
Convergence and Dynamical Behavior of the ADAM Algorithm for Non-Convex Stochastic Optimization—0
A risk measurement approach from risk-averse stochastic optimization of score functions—0
Fractal Structure and Generalization Properties of Stochastic Optimization Algorithms—0
Online Label Aggregation: A Variational Bayesian Approach—0
Formal Uncertainty Propagation for Stochastic Dynamical Systems with Additive Noise—0
Accelerated Gradient Methods for Stochastic Optimization and Online Learning—0
Langevin Dynamics with Continuous Tempering for Training Deep Neural Networks—0
Larger is Better: The Effect of Learning Rates Enjoyed by Stochastic Optimization with Progressive Variance Reduction—0
Large-Scale Approximate Kernel Canonical Correlation Analysis—0
Large Scale Many-Objective Optimization Driven by Distributional Adversarial Networks—0
Copula variational inference—0
Last-iterate convergence analysis of stochastic momentum methods for neural networks—0
Stochastic Collapsed Variational Inference for Structured Gaussian Process Regression Network—0
Last iterate convergence of SGD for Least-Squares in the Interpolation regime.—0
Latent Dirichlet Allocation in Generative Adversarial Networks—0
A Comparison of Monte Carlo Tree Search and Mathematical Optimization for Large Scale Dynamic Resource Allocation—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