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 551–600 of 1387 papers

TitleStatusHype
Communication-Efficient Distributed Optimization of Self-Concordant Empirical Loss—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
Global Convergence of Stochastic Gradient Hamiltonian Monte Carlo for Non-Convex Stochastic Optimization: Non-Asymptotic Performance Bounds and Momentum-Based Acceleration—0
Global-Order GFlowNets—0
Goal-Oriented Communication for Edge Learning based on the Information Bottleneck—0
Gradient Clipping Helps in Non-Smooth Stochastic Optimization with Heavy-Tailed Noise—0
Comparative analysis of criteria for filtering time series of word usage frequencies—0
Gradient Descent, Stochastic Optimization, and Other Tales—0
Gradient flows and proximal splitting methods: A unified view on accelerated and stochastic optimization—0
Gradient-free stochastic optimization for additive models—0
Gradient Sparification for Asynchronous Distributed Training—0
Gradient Sparsification for Communication-Efficient Distributed Optimization—0
Gradient Sparsification for Efficient Wireless Federated Learning with Differential Privacy—0
Gradient-Variation Online Learning under Generalized Smoothness—0
Graph-Homomorphic Perturbations for Private Decentralized Learning—0
Graphical Convergence of Subgradients in Nonconvex Optimization and Learning—0
Graph Oracle Models, Lower Bounds, and Gaps for Parallel Stochastic Optimization—0
Complexity Lower Bounds of Adaptive Gradient Algorithms for Non-convex Stochastic Optimization under Relaxed Smoothness—0
From Reinforcement Learning to Optimal Control: A unified framework for sequential decisions—0
Gray-box inference for structured Gaussian process models—0
Guaranteed Sufficient Decrease for Stochastic Variance Reduced Gradient Optimization—0
Guaranteed Sufficient Decrease for Variance Reduced Stochastic Gradient Descent—0
Adaptive Stochastic Optimization: From Sets to Paths—0
Heavy-Tail Phenomenon in Decentralized SGD—0
Hedging Complexity in Generalization via a Parametric Distributionally Robust Optimization Framework—0
Hessian based analysis of SGD for Deep Nets: Dynamics and Generalization—0
Improved Langevin Monte Carlo for stochastic optimization via landscape modification—0
Hierarchical Policy Blending as Inference for Reactive Robot Control—0
High Confidence Level Inference is Almost Free using Parallel Stochastic Optimization—0
High Dimensional Differentially Private Stochastic Optimization with Heavy-tailed Data—0
From Gradient Clipping to Normalization for Heavy Tailed SGD—0
High Probability Analysis for Non-Convex Stochastic Optimization with Clipping—0
High-probability Bounds for Non-Convex Stochastic Optimization with Heavy Tails—0
High-Probability Bounds for Stochastic Optimization and Variational Inequalities: the Case of Unbounded Variance—0
Macroscopic Traffic Flow Modeling with Physics Regularized Gaussian Process: Generalized Formulations—0
On Stationary-Point Hitting Time and Ergodicity of Stochastic Gradient Langevin Dynamics—0
How Free is Parameter-Free Stochastic Optimization?—0
How to effectively use machine learning models to predict the solutions for optimization problems: lessons from loss function—0
A New Random Reshuffling Method for Nonsmooth Nonconvex Finite-sum Optimization—0
Huber-energy measure quantization—0
Hybrid Offline-Online Design for Reconfigurable Intelligent Surface Aided UAV Communication—0
Hybrid Stochastic Gradient Descent Algorithms for Stochastic Nonconvex Optimization—0
Hydroassets Portfolio Management for Intraday Electricity Trading from a Discrete Time Stochastic Optimization Perspective—0
Constrained Online Two-stage Stochastic Optimization: Algorithm with (and without) Predictions—0
Hyperlink Regression via Bregman Divergence—0
Implicit Parameter-free Online Learning with Truncated Linear Models—0
Importance Sampled Stochastic Optimization for Variational Inference—0
Fractal Structure and Generalization Properties of Stochastic Optimization Algorithms—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