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

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Showing 501–550 of 1387 papers

TitleStatusHype
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
A Novel Ranking Scheme for the Performance Analysis of Stochastic Optimization Algorithms using the Principles of Severity—0
Adaptive Variance Reduction for Stochastic Optimization under Weaker Assumptions—0
Competing Adaptive Networks—0
Comparison of metaheuristics for the firebreak placement problem: a simulation-based optimization approach—0
A novel Deep Neural Network architecture for non-linear system identification—0
A Note On The Popularity of Stochastic Optimization Algorithms in Different Fields: A Quantitative Analysis from 2007 to 2017—0
Comparative analysis of criteria for filtering time series of word usage frequencies—0
Adaptive SVRG Methods under Error Bound Conditions with Unknown Growth Parameter—0
A Continuous-time Stochastic Gradient Descent Method for Continuous Data—0
Gradient Sparsification for Communication-Efficient Distributed Optimization—0
Community Detection for Power Systems Network Aggregation Considering Renewable Variability—0
Communication-Efficient Variance-Reduced Decentralized Stochastic Optimization over Time-Varying Directed Graphs—0
A General Reduction for High-Probability Analysis with General Light-Tailed Distributions—0
A Nonparametric Conjugate Prior Distribution for the Maximizing Argument of a Noisy Function—0
Communication-Efficient Distributed Optimization of Self-Concordant Empirical Loss—0
Adaptive Submodularity: Theory and Applications in Active Learning and Stochastic Optimization—0
Gradient-free stochastic optimization for additive models—0
Gradient Clipping Helps in Non-Smooth Stochastic Optimization with Heavy-Tailed Noise—0
Adaptive Strategies in Non-convex Optimization—0
Gradient Descent, Stochastic Optimization, and Other Tales—0
A Computational Efficient Pumped Storage Hydro Optimization in the Look-ahead Unit Commitment and Real-time Market Dispatch Under Uncertainty—0
A Non-asymptotic comparison of SVRG and SGD: tradeoffs between compute and speed—0
Accelerated zero-order SGD under high-order smoothness and overparameterized regime—0
Gradient flows and proximal splitting methods: A unified view on accelerated and stochastic optimization—0
Gradient Sparification for Asynchronous Distributed Training—0
Gradient Sparsification for Efficient Wireless Federated Learning with Differential Privacy—0
Fundamental Bias in Inverting Random Sampling Matrices with Application to Sub-sampled Newton—0
Function Norms and Regularization in Deep Networks—0
Comments on the proof of adaptive submodular function minimization—0
Combining resampling and reweighting for faithful stochastic optimization—0
From Reinforcement Learning to Optimal Control: A unified framework for sequential decisions—0
Adaptive Stochastic Optimization: From Sets to Paths—0
Fundamental Limits of Online and Distributed Algorithms for Statistical Learning and Estimation—0
Fusion of Image Segmentation Algorithms using Consensus Clustering—0
Global Convergence and Stability of Stochastic Gradient Descent—0
Generalization Bounds of Surrogate Policies for Combinatorial Optimization Problems—0
Generalization Bounds using Lower Tail Exponents in Stochastic Optimizers—0
Communication-Efficient Algorithms for Decentralized and Stochastic Optimization—0
Communication-Efficient Device Scheduling for Federated Learning Using Stochastic Optimization—0
From Gradient Clipping to Normalization for Heavy Tailed SGD—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