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 501–550 of 1387 papers

TitleStatusHype
A Unified Approach to Adaptive Regularization in Online and Stochastic Optimization—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
Distributed Evolution Strategies for Black-box Stochastic Optimization—0
Fast Stochastic Algorithms for Low-rank and Nonsmooth Matrix Problems—0
Distributed Delayed Stochastic Optimization—0
f-Divergence Variational Inference—0
Distributed and Stochastic Optimization Methods with Gradient Compression and Local Steps—0
Dissimilarity Coefficient based Weakly Supervised Object Detection—0
A Unified Analysis of Stochastic Optimization Methods Using Jump System Theory and Quadratic Constraints—0
A Unified Analysis on the Subgradient Upper Bounds for the Subgradient Methods Minimizing Composite Nonconvex, Nonsmooth and Non-Lipschitz Functions—0
Disentangled Representation Learning and Generation with Manifold Optimization—0
Discovering Knowledge Deficiencies of Language Models on Massive Knowledge Base—0
Augmentation Invariant Manifold Learning—0
A General Stochastic Optimization Framework for Convergence Bidding—0
Direct Acceleration of SAGA using Sampled Negative Momentum—0
A Two-Time-Scale Stochastic Optimization Framework with Applications in Control and Reinforcement Learning—0
Dimensionality Reduction for Stationary Time Series via Stochastic Nonconvex Optimization—0
Gamifying the Vehicle Routing Problem with Stochastic Requests—0
A Generalized Version of Chung's Lemma and its Applications—0
Adaptive First- and Second-Order Algorithms for Large-Scale Machine Learning—0
Accelerating SGD for Distributed Deep-Learning Using Approximated Hessian Matrix—0
Accelerated, Optimal, and Parallel: Some Results on Model-Based Stochastic Optimization—0
Efficient End-to-End Learning for Decision-Making: A Meta-Optimization Approach—0
Differential Private Stochastic Optimization with Heavy-tailed Data: Towards Optimal Rates—0
Differentially Private Stochastic Optimization: New Results in Convex and Non-Convex Settings—0
Asynchronous Stochastic Variational Inference—0
Differentially Private Non-convex Learning for Multi-layer Neural Networks—0
Differentially Private Gradient-Tracking-Based Distributed Stochastic Optimization over Directed Graphs—0
Asynchronous Stochastic Optimization Robust to Arbitrary Delays—0
A Generalized Stochastic Variational Bayesian Hyperparameter Learning Framework for Sparse Spectrum Gaussian Process Regression—0
Differentially Private Distributed Stochastic Optimization with Time-Varying Sample Sizes—0
Differentially Private Distributed Nonconvex Stochastic Optimization with Quantized Communication—0
Differentially Private Algorithms for the Stochastic Saddle Point Problem with Optimal Rates for the Strong Gap—0
Asynchronous stochastic convex optimization: the noise is in the noise and SGD don't care—0
An Adaptive Cost-Sensitive Learning and Recursive Denoising Framework for Imbalanced SVM Classification—0
Differentiable Annealed Importance Sampling and the Perils of Gradient Noise—0
Asynchronous Stochastic Block Coordinate Descent with Variance Reduction—0
Developing a Hybrid Data-Driven, Mechanistic Virtual Flow Meter -- a Case Study—0
Derivatives of Stochastic Gradient Descent in parametric optimization—0
Asynchronous Federated Stochastic Optimization for Heterogeneous Objectives Under Arbitrary Delays—0
A Functional Model Method for Nonconvex Nonsmooth Conditional Stochastic Optimization—0
Delivery Optimized Discovery in Behavioral User Segmentation under Budget Constraint—0
Asynchronous decentralized accelerated stochastic gradient descent—0
Asymptotic regularity of a generalised stochastic Halpern scheme with applications—0
A fully data-driven approach to minimizing CVaR for portfolio of assets via SGLD with discontinuous updating—0
Accelerating Minibatch Stochastic Gradient Descent using Typicality Sampling—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